From e2f7a043ddd7706178ff1815bcd475603f59c7a1 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 21:16:26 +0500
Subject: [PATCH 01/30] test(qwen3): committed non-circular golden generator +
 fixtures

---
 .../test/golden/qwen3/bpe_cases.json          |   1 +
 .../test/golden/qwen3/embed_text.npy          | Bin 0 -> 65664 bytes
 .../test/golden/qwen3/frame0.json             |   1 +
 .../test/golden/qwen3/frames.json             |   1 +
 .../test/golden/qwen3/ids.json                |   1 +
 .../test/golden/qwen3/meta.json               |   1 +
 .../test/golden/qwen3/prompt.npz              | Bin 0 -> 78586 bytes
 .../test/golden/qwen3/tokenizer.json.gz       | Bin 0 -> 2059919 bytes
 .../test/golden/qwen3/voices/demo_speaker.npy | Bin 0 -> 4224 bytes
 .../test/golden/qwen3/waveform_f32.bin        | Bin 0 -> 199680 bytes
 .../tool/qwen3/gen_qwen3_goldens.py           |  67 ++++++++++++++++++
 11 files changed, 72 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/bpe_cases.json
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/embed_text.npy
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/frame0.json
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/frames.json
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/ids.json
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/meta.json
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/prompt.npz
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/tokenizer.json.gz
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/voices/demo_speaker.npy
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/waveform_f32.bin
 create mode 100644 packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py

diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/bpe_cases.json b/packages/flutter_gemma_speech/test/golden/qwen3/bpe_cases.json
new file mode 100644
index 00000000..eb4a21f9
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/golden/qwen3/bpe_cases.json
@@ -0,0 +1 @@
+{"Hello, world!": [9707, 11, 1879, 0], "It's 3:47 PM \u2014 don't wait.": [2132, 594, 220, 18, 25, 19, 22, 5851, 1959, 1513, 944, 3783, 13], "Gr\u00fc\u00dfe aus M\u00fcnchen": [6464, 2391, 23455, 9421, 89266], "a   b\tc\nd": [64, 256, 293, 1444, 198, 67], "1234567890": [16, 17, 18, 19, 20, 21, 22, 23, 24, 15], "na\u00efve caf\u00e9": [3376, 37572, 586, 51950], "\u4f60\u597d\uff0c\u4e16\u754c": [108386, 3837, 99489], "<|im_start|>plain</s>": [151644, 20772, 522, 82, 29]}
\ No newline at end of file
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/embed_text.npy b/packages/flutter_gemma_speech/test/golden/qwen3/embed_text.npy
new file mode 100644
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diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/frame0.json b/packages/flutter_gemma_speech/test/golden/qwen3/frame0.json
new file mode 100644
index 00000000..354654b0
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/golden/qwen3/frame0.json
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\ No newline at end of file
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/frames.json b/packages/flutter_gemma_speech/test/golden/qwen3/frames.json
new file mode 100644
index 00000000..5ed587b3
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/golden/qwen3/frames.json
@@ -0,0 +1 @@
+{"frames": [[1342, 1555, 702, 1154, 1344, 980, 912, 1720, 1673, 302, 1999, 765, 15, 1601, 846, 1774], [1014, 286, 592, 81, 375, 1264, 82, 851, 1690, 628, 1356, 1662, 1277, 153, 286, 2000], [1119, 1122, 829, 1747, 1628, 1715, 107, 297, 469, 551, 1341, 301, 1250, 626, 861, 1509], [1119, 1909, 2019, 212, 567, 396, 497, 310, 660, 581, 1995, 510, 175, 1779, 206, 204], [1866, 0, 824, 993, 306, 1642, 489, 395, 1729, 34, 1163, 771, 861, 284, 1744, 349], [1257, 1628, 319, 1343, 33, 769, 207, 1056, 186, 3, 1340, 511, 13, 1172, 1387, 935], [550, 1198, 1794, 1408, 604, 1166, 1754, 1297, 1781, 52, 131, 367, 1724, 75, 364, 729], [550, 474, 1832, 135, 1285, 1965, 452, 1304, 1447, 781, 431, 50, 271, 1408, 626, 1527], [1550, 381, 1386, 1492, 288, 2035, 1069, 210, 1609, 168, 1806, 84, 841, 1600, 956, 1647], [709, 890, 1322, 634, 324, 5, 1671, 475, 780, 2013, 1163, 1836, 71, 1957, 70, 277], [1179, 1500, 548, 452, 991, 1360, 1553, 1649, 138, 251, 1015, 386, 1695, 1079, 1694, 94], [1788, 1371, 1857, 1379, 996, 1225, 1987, 1878, 940, 157, 676, 1843, 1135, 1729, 1888, 117], [1412, 798, 1828, 567, 1492, 1790, 107, 438, 245, 120, 1148, 892, 855, 625, 25, 1291], [1250, 304, 379, 1642, 824, 575, 1545, 176, 507, 1960, 841, 199, 1567, 1691, 784, 337], [545, 340, 565, 1192, 1548, 362, 1949, 15, 1835, 106, 282, 835, 466, 273, 1065, 174], [1514, 1378, 608, 1538, 408, 1029, 603, 889, 510, 156, 1050, 1916, 36, 150, 1701, 1290], [388, 1991, 1856, 428, 1990, 770, 895, 683, 688, 62, 876, 2047, 99, 955, 1657, 410], [19, 125, 398, 1700, 996, 666, 283, 383, 2037, 56, 1516, 1991, 1268, 1495, 808, 1527], [187, 1841, 473, 977, 1031, 1111, 267, 267, 1683, 359, 341, 664, 1594, 263, 241, 1], [1062, 996, 1393, 327, 1315, 1335, 66, 1140, 636, 303, 519, 1057, 1213, 797, 366, 1274], [1467, 976, 1949, 819, 171, 415, 343, 1835, 47, 1252, 917, 1142, 32, 1442, 815, 1235], [357, 2004, 1054, 1118, 571, 1542, 1767, 153, 993, 460, 1102, 1504, 232, 1280, 587, 401], [2028, 1651, 1717, 1852, 712, 604, 1155, 108, 706, 1854, 614, 68, 363, 467, 1954, 796], [1118, 844, 473, 149, 1020, 881, 831, 1059, 564, 1200, 511, 1238, 1115, 890, 192, 32], [609, 1009, 1093, 241, 625, 121, 1300, 1202, 1025, 1673, 743, 146, 527, 1838, 85, 1668], [1543, 1009, 1972, 1572, 2024, 121, 77, 108, 810, 1625, 743, 903, 527, 1838, 85, 901]]}
\ No newline at end of file
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/ids.json b/packages/flutter_gemma_speech/test/golden/qwen3/ids.json
new file mode 100644
index 00000000..91639120
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/golden/qwen3/ids.json
@@ -0,0 +1 @@
+{"template": "<|im_start|>assistant\nHello from on device text to speech.<|im_end|>\n<|im_start|>assistant\n", "ids": [151644, 77091, 198, 9707, 504, 389, 3671, 1467, 311, 8806, 13, 151645, 198, 151644, 77091, 198]}
\ No newline at end of file
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/meta.json b/packages/flutter_gemma_speech/test/golden/qwen3/meta.json
new file mode 100644
index 00000000..a138f520
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/golden/qwen3/meta.json
@@ -0,0 +1 @@
+{"text": "Hello from on device text to speech.", "language": "english", "talker": "fp32", "greedy": true, "speaker": "demo_speaker", "num_frames": 26, "sample_rate": 24000}
\ No newline at end of file
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/prompt.npz b/packages/flutter_gemma_speech/test/golden/qwen3/prompt.npz
new file mode 100644
index 0000000000000000000000000000000000000000..dbdc82dac037ab8a91c6f398ff8f54b3859dc03b
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diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/tokenizer.json.gz b/packages/flutter_gemma_speech/test/golden/qwen3/tokenizer.json.gz
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diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/voices/demo_speaker.npy b/packages/flutter_gemma_speech/test/golden/qwen3/voices/demo_speaker.npy
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diff --git a/packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py b/packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py
new file mode 100644
index 00000000..02d154a3
--- /dev/null
+++ b/packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py
@@ -0,0 +1,67 @@
+# gen_qwen3_goldens.py — run once; commits fixtures. Needs the recipe on PYTHONPATH
+# and the talker_fp32 snapshot. Usage:
+#   python gen_qwen3_goldens.py --recipe .../text_to_speech_lm/python --model_dir <snap> --out ../../test/golden/qwen3
+import argparse, json, sys, time, numpy as np
+
+def synthesize_logging(pipe, q, text, speaker, language, out):
+    """Verbatim copy of Qwen3TtsPipeline.synthesize (greedy) that also logs
+    every frame and the frame-0 (hidden, cb0, residual)."""
+    prefill, trailing, tts_pad = pipe._build_prompt(text, speaker, language)
+    kv = {n: np.zeros(pipe._decode.get_input_details()[n]['shape'], np.float32) for n in pipe._kv_names}
+    kv = pipe._run_prefill(kv, prefill)
+    pos = prefill.shape[1] - 1
+    logits, hidden, kv = pipe._run_decode(kv, prefill[0, -1], pos)
+    suppress = np.zeros(q._CODEC_VOCAB, np.float32); suppress[2048:] = q._NEG_INF; suppress[q._CODEC_EOS] = 0.0
+    frames, history, frame0 = [], set(), None
+    while len(frames) < 512:
+        scores = logits + suppress
+        if len(frames) < 2: scores[q._CODEC_EOS] = q._NEG_INF
+        for t in history:
+            scores[t] = scores[t] / 1.05 if scores[t] > 0 else scores[t] * 1.05
+        cb0 = int(np.argmax(scores)); history.add(cb0)
+        if cb0 == q._CODEC_EOS: break
+        residual = pipe._run_mtp(hidden, cb0, False, 50, 0.9, None)
+        if frame0 is None:
+            frame0 = {'hidden': [float(x) for x in hidden], 'cb0': cb0, 'residual': [int(x) for x in residual]}
+        frames.append([cb0] + residual)
+        embed = pipe._codec_emb[cb0] + pipe._mtp_emb[np.arange(15), residual].sum(0)
+        step = len(frames) - 1
+        embed += trailing[step] if step < len(trailing) else tts_pad
+        pos += 1
+        logits, hidden, kv = pipe._run_decode(kv, embed, pos)
+    wav = pipe._decode_codes(np.array(frames, np.int32))
+    json.dump({'frames': frames}, open(f'{out}/frames.json','w'))
+    json.dump(frame0, open(f'{out}/frame0.json','w'))
+    wav.astype(np.float32).tofile(f'{out}/waveform_f32.bin')
+    return wav, len(frames)
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument('--recipe', required=True); ap.add_argument('--model_dir', required=True)
+    ap.add_argument('--out', required=True); ap.add_argument('--text', default='Hello from on device text to speech.')
+    a = ap.parse_args(); sys.path.insert(0, a.recipe)
+    import qwen3_tts_pipeline as q
+    pipe = q.Qwen3TtsPipeline(a.model_dir, talker_file='talker_fp32.tflite', num_threads=8)
+    speaker = np.load(f'{a.model_dir}/voices/demo_speaker.npy')
+
+    tmpl = f'<|im_start|>assistant\n{a.text}<|im_end|>\n<|im_start|>assistant\n'
+    ids = list(map(int, pipe._tokenizer.encode(tmpl).ids))
+    json.dump({'template': tmpl, 'ids': ids}, open(f'{a.out}/ids.json','w'))
+
+    # diverse BPE goldens — numbers, punctuation, unicode, contractions, multi-space, CJK
+    cases = ["Hello, world!", "It's 3:47 PM — don't wait.", "Grüße aus München",
+             "a   b\tc\nd", "1234567890", "naïve café", "你好，世界", "<|im_start|>plain</s>"]
+    json.dump({c: list(map(int, pipe._tokenizer.encode(c).ids)) for c in cases},
+              open(f'{a.out}/bpe_cases.json','w'))
+
+    prefill, trailing, tts_pad = pipe._build_prompt(a.text, speaker, 'english')
+    np.savez(f'{a.out}/prompt.npz', prefill=prefill.astype(np.float32),
+             trailing=np.asarray(trailing, np.float32), tts_pad=tts_pad.astype(np.float32))
+    np.save(f'{a.out}/embed_text.npy', pipe._embed_text(np.array(ids)).astype(np.float32))  # [len(ids)*? -> reshape [n,1024]]
+
+    wav, nframes = synthesize_logging(pipe, q, a.text, speaker, 'english', a.out)
+    json.dump({'text': a.text, 'language':'english', 'talker':'fp32', 'greedy':True,
+               'speaker':'demo_speaker', 'num_frames': int(nframes), 'sample_rate': 24000},
+              open(f'{a.out}/meta.json','w'))
+
+if __name__ == '__main__': main()

From 2dcda55b8ecbd6d18fe512bc52b104faa4b01d3f Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 21:26:01 +0500
Subject: [PATCH 02/30] feat(qwen3): npy/npz reader with fp16 row-lookup

---
 .../lib/src/qwen3/npy_reader.dart             | 336 ++++++++++++++++++
 .../test/golden/qwen3/npy/f2_4x5.npy          | Bin 0 -> 168 bytes
 .../test/golden/qwen3/npy/f4_2x3.npy          | Bin 0 -> 152 bytes
 .../test/qwen3/npy_reader_test.dart           |  42 +++
 4 files changed, 378 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/npy_reader.dart
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/npy/f2_4x5.npy
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/npy/f4_2x3.npy
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/npy_reader_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/npy_reader.dart b/packages/flutter_gemma_speech/lib/src/qwen3/npy_reader.dart
new file mode 100644
index 00000000..e6210054
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/npy_reader.dart
@@ -0,0 +1,336 @@
+// .npy / .npz reader for the Qwen3-TTS host tables (embedding tables,
+// projection matrices, prompt caches) shipped as NumPy arrays.
+//
+// Supports:
+//  - whole-array reads of `<f4` (float32) and `<f2` (float16, up-cast to
+//    float32) arrays,
+//  - single-row lookup by byte offset into a 2-D `<f2` array (avoids loading
+//    the whole table into memory for a single embedding lookup),
+//  - `.npz` archives (a ZIP of `.npy` members) — STORED entries only, as
+//    produced by `numpy.savez` for these tables.
+//
+// Format reference: .npy v1 = 6-byte magic `\x93NUMPY`, 1 byte major
+// version, 1 byte minor version, a 2-byte little-endian header length, then
+// an ASCII Python-dict literal header (e.g.
+// `{'descr': '<f4', 'fortran_order': False, 'shape': (2, 3), }`) padded with
+// spaces (and a trailing `\n`) so that `10 + headerLength` is a multiple of
+// 64, followed by the raw little-endian array data.
+//
+// This file is pure Dart (`dart:io` + `dart:typed_data`) — no Flutter, no
+// FFI, no native dependency — so it can be unit-tested without a device.
+
+import 'dart:convert';
+import 'dart:io';
+import 'dart:typed_data';
+
+/// Parsed `.npy` header: array shape, NumPy dtype string (e.g. `'<f4'`,
+/// `'<f2'`), and the byte offset in the file where raw array data begins.
+class NpyHeader {
+  const NpyHeader({
+    required this.shape,
+    required this.dtype,
+    required this.dataOffset,
+  });
+
+  final List<int> shape;
+  final String dtype;
+  final int dataOffset;
+}
+
+const int _npyMagicAndVersionLength = 8; // 6-byte magic + major + minor.
+
+/// Parses the `.npy` v1 header from an already-open [RandomAccessFile].
+/// Leaves the file position at [NpyHeader.dataOffset] on return.
+NpyHeader parseNpyHeader(RandomAccessFile f) {
+  f.setPositionSync(0);
+  final magicAndVersion = f.readSync(_npyMagicAndVersionLength);
+  if (magicAndVersion.length != _npyMagicAndVersionLength ||
+      magicAndVersion[0] != 0x93 ||
+      String.fromCharCodes(magicAndVersion.sublist(1, 6)) != 'NUMPY') {
+    throw const FormatException('not a .npy file (bad magic)');
+  }
+  final major = magicAndVersion[6];
+  if (major != 1) {
+    throw FormatException('unsupported .npy version: $major');
+  }
+
+  final headerLenBytes = f.readSync(2);
+  final headerLen = ByteData.sublistView(
+    headerLenBytes,
+  ).getUint16(0, Endian.little);
+  final headerBytes = f.readSync(headerLen);
+  final headerStr = ascii.decode(headerBytes);
+
+  final dtype = _extractDictString(headerStr, 'descr');
+  final shape = _extractShape(headerStr);
+
+  final dataOffset = _npyMagicAndVersionLength + 2 + headerLen;
+  f.setPositionSync(dataOffset);
+  return NpyHeader(shape: shape, dtype: dtype, dataOffset: dataOffset);
+}
+
+String _extractDictString(String header, String key) {
+  final match = RegExp("'$key'\\s*:\\s*'([^']*)'").firstMatch(header);
+  if (match == null) {
+    throw FormatException(".npy header missing '$key': $header");
+  }
+  return match.group(1)!;
+}
+
+List<int> _extractShape(String header) {
+  final match = RegExp(r"'shape'\s*:\s*\(([^)]*)\)").firstMatch(header);
+  if (match == null) {
+    throw FormatException('.npy header missing shape: $header');
+  }
+  final inner = match.group(1)!.trim();
+  if (inner.isEmpty) return const [];
+  return inner
+      .split(',')
+      .map((s) => s.trim())
+      .where((s) => s.isNotEmpty)
+      .map(int.parse)
+      .toList(growable: false);
+}
+
+int _elementCount(List<int> shape) =>
+    shape.isEmpty ? 1 : shape.reduce((a, b) => a * b);
+
+/// Reads a whole `<f4` (little-endian float32) `.npy` array into a flat
+/// [Float32List] (row-major / C order).
+Float32List readNpyF32(String path) {
+  final f = File(path).openSync();
+  try {
+    final h = parseNpyHeader(f);
+    if (h.dtype != '<f4') {
+      throw StateError(
+        'readNpyF32: expected dtype <f4, got ${h.dtype} ($path)',
+      );
+    }
+    final count = _elementCount(h.shape);
+    final bytes = f.readSync(count * 4);
+    if (bytes.length != count * 4) {
+      throw StateError(
+        'readNpyF32: truncated file $path (expected ${count * 4} bytes, '
+        'got ${bytes.length})',
+      );
+    }
+    return Float32List.view(_copyToAlignedBuffer(bytes).buffer);
+  } finally {
+    f.closeSync();
+  }
+}
+
+/// Reads a whole `<f2` (little-endian float16) `.npy` array, up-cast
+/// element-wise to a flat [Float32List] (row-major / C order).
+Float32List readNpyF16AsF32(String path) {
+  final f = File(path).openSync();
+  try {
+    final h = parseNpyHeader(f);
+    if (h.dtype != '<f2') {
+      throw StateError(
+        'readNpyF16AsF32: expected dtype <f2, got ${h.dtype} ($path)',
+      );
+    }
+    final count = _elementCount(h.shape);
+    final bytes = f.readSync(count * 2);
+    if (bytes.length != count * 2) {
+      throw StateError(
+        'readNpyF16AsF32: truncated file $path (expected ${count * 2} '
+        'bytes, got ${bytes.length})',
+      );
+    }
+    final view = ByteData.sublistView(_copyToAlignedBuffer(bytes));
+    final out = Float32List(count);
+    for (var i = 0; i < count; i++) {
+      out[i] = _halfToFloat(view.getUint16(i * 2, Endian.little));
+    }
+    return out;
+  } finally {
+    f.closeSync();
+  }
+}
+
+/// Reads a single row of a 2-D `<f2` `.npy` array by seeking directly to its
+/// byte offset (`header.dataOffset + row * cols * 2`), avoiding a whole-array
+/// load. [h] must have been produced by [parseNpyHeader] on [f].
+Float32List npyRowF16AsF32(RandomAccessFile f, NpyHeader h, int row) {
+  if (h.dtype != '<f2') {
+    throw StateError('npyRowF16AsF32: expected dtype <f2, got ${h.dtype}');
+  }
+  if (h.shape.length != 2) {
+    throw StateError(
+      'npyRowF16AsF32: expected a 2-D array, got shape ${h.shape}',
+    );
+  }
+  final rows = h.shape[0];
+  final cols = h.shape[1];
+  if (row < 0 || row >= rows) {
+    throw RangeError.range(row, 0, rows - 1, 'row');
+  }
+  final offset = h.dataOffset + row * cols * 2;
+  f.setPositionSync(offset);
+  final bytes = f.readSync(cols * 2);
+  if (bytes.length != cols * 2) {
+    throw StateError(
+      'npyRowF16AsF32: truncated file at row $row (expected ${cols * 2} '
+      'bytes, got ${bytes.length})',
+    );
+  }
+  final view = ByteData.sublistView(_copyToAlignedBuffer(bytes));
+  final out = Float32List(cols);
+  for (var i = 0; i < cols; i++) {
+    out[i] = _halfToFloat(view.getUint16(i * 2, Endian.little));
+  }
+  return out;
+}
+
+/// Copies [bytes] into a fresh, 0-offset [Uint8List] so it is safe to wrap
+/// with [Float32List.view] / [ByteData.sublistView] regardless of the
+/// underlying buffer's alignment or offset (`RandomAccessFile.readSync`
+/// results are not guaranteed to start at a buffer offset divisible by 4).
+Uint8List _copyToAlignedBuffer(Uint8List bytes) => Uint8List.fromList(bytes);
+
+/// IEEE-754 binary16 -> IEEE-754 binary64 (Dart `double`) conversion,
+/// handling zero, subnormals, normals, infinities, and NaN.
+double _halfToFloat(int h) {
+  final s = (h >> 15) & 1;
+  final e = (h >> 10) & 0x1f;
+  final m = h & 0x3ff;
+  if (e == 0) {
+    // Zero (m == 0) or subnormal: value = m * 2^-24.
+    return (s == 1 ? -1 : 1) * m * 5.9604644775390625e-8;
+  }
+  if (e == 31) {
+    if (m == 0) {
+      return s == 1 ? double.negativeInfinity : double.infinity;
+    }
+    return double.nan;
+  }
+  return (s == 1 ? -1 : 1) * (1 + m / 1024.0) * _pow2(e - 15);
+}
+
+double _pow2(int exp) => exp >= 0 ? (1 << exp).toDouble() : 1.0 / (1 << -exp);
+
+// --- Minimal ZIP reader for .npz (STORED entries only) ----------------
+
+/// Reads every member of a `.npz` archive (a ZIP of `.npy` files, as
+/// produced by `numpy.savez`) and up-casts each to a flat [Float32List],
+/// keyed by member name without the `.npy` suffix.
+///
+/// Only STORED (uncompressed) entries are supported — `numpy.savez` (as
+/// opposed to `savez_compressed`) always writes STORED entries. A DEFLATE
+/// member throws a [StateError] rather than being silently misread.
+Map<String, Float32List> readNpzF32(String path) {
+  final bytes = File(path).readAsBytesSync();
+  final entries = _readZipStoredEntries(bytes);
+  final out = <String, Float32List>{};
+  for (final entry in entries.entries) {
+    var name = entry.key;
+    if (name.endsWith('.npy')) {
+      name = name.substring(0, name.length - '.npy'.length);
+    }
+    out[name] = _npyBytesToF32(entry.value, name);
+  }
+  return out;
+}
+
+Float32List _npyBytesToF32(Uint8List npyBytes, String memberName) {
+  final byteData = ByteData.sublistView(npyBytes);
+  if (npyBytes.length < 10 ||
+      byteData.getUint8(0) != 0x93 ||
+      String.fromCharCodes(npyBytes.sublist(1, 6)) != 'NUMPY') {
+    throw FormatException('npz member $memberName: not a .npy file');
+  }
+  final headerLen = byteData.getUint16(8, Endian.little);
+  final headerStr = ascii.decode(npyBytes.sublist(10, 10 + headerLen));
+  final dtype = _extractDictString(headerStr, 'descr');
+  final shape = _extractShape(headerStr);
+  final dataOffset = 10 + headerLen;
+  final count = _elementCount(shape);
+
+  if (dtype == '<f4') {
+    final data = npyBytes.sublist(dataOffset, dataOffset + count * 4);
+    return Float32List.view(_copyToAlignedBuffer(data).buffer);
+  } else if (dtype == '<f2') {
+    final view = ByteData.sublistView(npyBytes, dataOffset);
+    final out = Float32List(count);
+    for (var i = 0; i < count; i++) {
+      out[i] = _halfToFloat(view.getUint16(i * 2, Endian.little));
+    }
+    return out;
+  }
+  throw StateError('npz member $memberName: unsupported dtype $dtype');
+}
+
+/// Reads the ZIP End Of Central Directory record and Central Directory of
+/// [bytes], returning the raw (uncompressed) data of every STORED member,
+/// keyed by filename. Throws [StateError] on any non-STORED (compressed)
+/// member.
+Map<String, Uint8List> _readZipStoredEntries(Uint8List bytes) {
+  const eocdSignature = 0x06054b50;
+  const centralDirSignature = 0x02014b50;
+  const localHeaderSignature = 0x04034b50;
+  const storedMethod = 0;
+
+  // The EOCD record is at least 22 bytes and sits at the end of the file,
+  // optionally preceded by a variable-length comment — scan backward for
+  // its signature (comment is capped at 65535 bytes by the ZIP spec, so this
+  // terminates quickly).
+  var eocdOffset = -1;
+  final maxCommentLen = bytes.length < 65557 ? bytes.length - 22 : 65535;
+  for (var back = 0; back <= maxCommentLen; back++) {
+    final pos = bytes.length - 22 - back;
+    if (pos < 0) break;
+    final data = ByteData.sublistView(bytes, pos, pos + 4);
+    if (data.getUint32(0, Endian.little) == eocdSignature) {
+      eocdOffset = pos;
+      break;
+    }
+  }
+  if (eocdOffset < 0) {
+    throw const FormatException('.npz: End Of Central Directory not found');
+  }
+
+  final eocd = ByteData.sublistView(bytes, eocdOffset, eocdOffset + 22);
+  final entryCount = eocd.getUint16(10, Endian.little);
+  final centralDirOffset = eocd.getUint32(16, Endian.little);
+
+  final out = <String, Uint8List>{};
+  var pos = centralDirOffset;
+  for (var i = 0; i < entryCount; i++) {
+    final header = ByteData.sublistView(bytes, pos, pos + 46);
+    if (header.getUint32(0, Endian.little) != centralDirSignature) {
+      throw const FormatException('.npz: malformed central directory entry');
+    }
+    final compressionMethod = header.getUint16(10, Endian.little);
+    final compressedSize = header.getUint32(20, Endian.little);
+    final nameLen = header.getUint16(28, Endian.little);
+    final extraLen = header.getUint16(30, Endian.little);
+    final commentLen = header.getUint16(32, Endian.little);
+    final localHeaderOffset = header.getUint32(42, Endian.little);
+    final name = utf8.decode(bytes.sublist(pos + 46, pos + 46 + nameLen));
+
+    if (compressionMethod != storedMethod) {
+      throw StateError('npz member $name is DEFLATE; STORED expected');
+    }
+
+    // Parse the local file header to find where the raw data actually
+    // starts (its filename/extra-field lengths can differ in principle from
+    // the central directory's, even though numpy writes them identically).
+    final localHeader = ByteData.sublistView(
+      bytes,
+      localHeaderOffset,
+      localHeaderOffset + 30,
+    );
+    if (localHeader.getUint32(0, Endian.little) != localHeaderSignature) {
+      throw FormatException('.npz: malformed local file header for $name');
+    }
+    final localNameLen = localHeader.getUint16(26, Endian.little);
+    final localExtraLen = localHeader.getUint16(28, Endian.little);
+    final dataStart = localHeaderOffset + 30 + localNameLen + localExtraLen;
+    out[name] = bytes.sublist(dataStart, dataStart + compressedSize);
+
+    pos += 46 + nameLen + extraLen + commentLen;
+  }
+  return out;
+}
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/npy/f2_4x5.npy b/packages/flutter_gemma_speech/test/golden/qwen3/npy/f2_4x5.npy
new file mode 100644
index 0000000000000000000000000000000000000000..84c434d0e11596ba1f764b739390ca3f18199ec7
GIT binary patch
literal 168
zcmbR27wQ`j$;eQ~P_3SlTAW;@Zl$1ZlV+r@qoAIaUsO_*m=~X4l#&V(cT3DEP6dh=
zXCxM+0{I#yItr$mItsN4WCJb+1_m1j2L>kw7Y0`bHwJeGj|LA0&jwEhuLds$?*?xM
L9|xZXp94MsCd4E@

literal 0
HcmV?d00001

diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/npy/f4_2x3.npy b/packages/flutter_gemma_speech/test/golden/qwen3/npy/f4_2x3.npy
new file mode 100644
index 0000000000000000000000000000000000000000..9816daca054e50626e2e8a009e6df26b0cdbd1f1
GIT binary patch
literal 152
zcmbR27wQ`j$;eQ~P_3SlTAW;@Zl$1ZlV+l>qoAIaUsO_*m=~X4l#&V(cT3DEP6dh=
mXCxM+0{I$7Its>`ItsN4WCJb+Flev`QVu`_#0@~azySaQtsaX2

literal 0
HcmV?d00001

diff --git a/packages/flutter_gemma_speech/test/qwen3/npy_reader_test.dart b/packages/flutter_gemma_speech/test/qwen3/npy_reader_test.dart
new file mode 100644
index 00000000..88bd0d73
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/npy_reader_test.dart
@@ -0,0 +1,42 @@
+// Tests for the .npy / .npz reader used by the Qwen3-TTS pipeline to load
+// host-side model tables (embedding tables, projection matrices, prompt
+// caches) shipped as NumPy arrays.
+//
+// Fixtures live under test/golden/qwen3/npy/ (generated via numpy, see
+// task-1.1-brief.md for the exact generation snippet) and
+// test/golden/qwen3/prompt.npz (committed in Task 0 — do not regenerate).
+
+import 'dart:io';
+
+import 'package:flutter_gemma_speech/src/qwen3/npy_reader.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+void main() {
+  group('readNpyF32', () {
+    test('reads <f4 npy whole', () {
+      final a = readNpyF32('test/golden/qwen3/npy/f4_2x3.npy');
+      expect(a, orderedEquals([0, 1, 2, 3, 4, 5].map((e) => e.toDouble())));
+    });
+  });
+
+  group('parseNpyHeader / readNpyF16AsF32 / npyRowF16AsF32', () {
+    test('reads <f2 npy row by offset == whole-array row', () {
+      final f = File('test/golden/qwen3/npy/f2_4x5.npy').openSync();
+      final h = parseNpyHeader(f);
+      expect(h.shape, [4, 5]);
+      expect(h.dtype, '<f2');
+
+      final whole = readNpyF16AsF32('test/golden/qwen3/npy/f2_4x5.npy');
+      final row2 = npyRowF16AsF32(f, h, 2);
+      expect(row2, orderedEquals(whole.sublist(10, 15)));
+      f.closeSync();
+    });
+  });
+
+  group('readNpzF32', () {
+    test('reads npz members', () {
+      final m = readNpzF32('test/golden/qwen3/prompt.npz');
+      expect(m.keys, containsAll(['prefill', 'trailing', 'tts_pad']));
+    });
+  });
+}

From 4937707639c92173f9688959310486927f6aaa07 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 21:37:59 +0500
Subject: [PATCH 03/30] feat(qwen3): Qwen2 byte-level BPE encoder

Net-new text->ids encoder for the Qwen3-TTS text frontend (HfTokenizer is
decode-only). Reproduces the HF tokenizers pipeline: NFC pass-through,
atomic longest-match added-token splitting, the Qwen2 Split regex (Dart
RegExp supports the inline (?i:...) group and \p{L}/\p{N} directly),
GPT-2 byte<->unicode mapping, and rank-ordered BPE merges.

Verified against Task 0's HF-tokenizers golden fixtures: the templated
prompt (16 ids), 8 diverse bpe_cases (contractions, German/French
accents, CJK, whitespace runs, digits, a literal special-token string),
and atomic special-token ids -- all pass without any NFC normalization.
---
 .../lib/src/qwen3/qwen2_bpe_encoder.dart      | 304 ++++++++++++++++++
 .../test/qwen3/qwen2_bpe_encoder_test.dart    |  78 +++++
 2 files changed, 382 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/qwen2_bpe_encoder.dart
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen2_bpe_encoder_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen2_bpe_encoder.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen2_bpe_encoder.dart
new file mode 100644
index 00000000..8e8f2f8f
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen2_bpe_encoder.dart
@@ -0,0 +1,304 @@
+// Qwen2 byte-level BPE ENCODER (text -> token ids) for the Qwen3-TTS text
+// frontend. Companion to `Gpt2ByteLevelBpeTokenizer`
+// (`../tokenizer/gpt2_byte_level_bpe_tokenizer.dart`), which is DECODE-only
+// for Whisper's ids -> text; `HfTokenizer`/that decoder has no encoder, so
+// this is net-new. Same byte-level BPE family (GPT-2's byte<->unicode map +
+// rank-ordered merges), but reproduces Qwen2's specific pre-tokenizer
+// pipeline as recorded in `tokenizer.json`:
+//
+//   NFC normalize
+//     -> split out added/special tokens atomically (longest match first)
+//     -> for each remaining span, the Qwen2 pre-tokenizer `Split` regex
+//        (behavior "Isolated", `add_prefix_space=false`)
+//     -> ByteLevel: map each UTF-8 byte of every piece to its GPT-2
+//        byte<->unicode character
+//     -> BPE merge each byte-level piece (rank-ordered, from `model.merges`)
+//     -> vocab lookup (`model.vocab`) for the final merged symbols.
+//
+// Pure Dart (`dart:convert` + `dart:io`) -- no Flutter import -- so this runs
+// headless in `dart test` / `flutter test` without a device.
+//
+// NFC: this encoder does NOT perform explicit Unicode NFC normalization.
+// Dart's core libraries have no built-in NFC implementation, and adding one
+// would mean a new third-party dependency -- not done unilaterally here. In
+// practice this is a pass-through: text authored in a normal editor/source
+// file is already NFC, and the golden coverage (contractions, German/French
+// accented Latin, CJK, whitespace runs, digits, a literal special-token
+// string) all encode correctly without it. Known v1 limitation: arbitrary
+// non-NFC input (e.g. combining-character sequences from some IMEs or
+// pasted text) is not renormalized before encoding and may diverge from the
+// reference HF tokenizer for that specific input.
+library;
+
+import 'dart:convert';
+import 'dart:io';
+
+/// Byte-level BPE encoder for the Qwen2 tokenizer family, driving the
+/// Qwen3-TTS text frontend (text prompt -> token ids fed to the LLM core).
+class Qwen2BpeEncoder {
+  Qwen2BpeEncoder._({
+    required this._vocab,
+    required this._mergeRanks,
+    required List<_AddedToken> addedTokens,
+  }) : _addedTokenById = {for (final t in addedTokens) t.content: t.id},
+       _addedTokenPattern = _buildAddedTokenPattern(addedTokens);
+
+  final Map<String, int> _vocab;
+  final Map<String, int> _mergeRanks;
+  final Map<String, int> _addedTokenById;
+  final RegExp? _addedTokenPattern;
+
+  /// GPT-2's byte<->unicode map: every raw byte 0..255 -> a printable
+  /// unicode code point, so arbitrary UTF-8 bytes round-trip through a BPE
+  /// vocab of "characters". Ports the same table as
+  /// `Gpt2ByteLevelBpeTokenizer._gpt2ByteToUnicode()` (private there, so
+  /// duplicated here rather than reused across libraries); see that file's
+  /// doc comment for the byte-range rationale.
+  static final Map<int, int> _byteToUnicode = _buildByteToUnicode();
+
+  static Map<int, int> _buildByteToUnicode() {
+    final bytes = <int>[
+      for (var b = 0x21; b <= 0x7E; b++) b,
+      for (var b = 0xA1; b <= 0xAC; b++) b,
+      for (var b = 0xAE; b <= 0xFF; b++) b,
+    ];
+    final selfMapped = bytes.toSet();
+    final codepoints = <int>[...bytes];
+    var n = 0;
+    for (var b = 0; b < 256; b++) {
+      if (!selfMapped.contains(b)) {
+        bytes.add(b);
+        codepoints.add(256 + n);
+        n++;
+      }
+    }
+    return {for (var i = 0; i < bytes.length; i++) bytes[i]: codepoints[i]};
+  }
+
+  /// The Qwen2 pre-tokenizer's `Split` regex, taken verbatim from
+  /// `tokenizer.json`'s `pre_tokenizer.pretokenizers[0].pattern.Regex`
+  /// (a `Sequence` of `Split(behavior=Isolated, invert=false)` then
+  /// `ByteLevel(add_prefix_space=false, use_regex=false)`). The pattern
+  /// alone tiles the whole input (contractions / letter runs / lone digits
+  /// / punctuation runs / newline-terminated whitespace / trailing
+  /// whitespace / any other whitespace), so `allMatches` over it is
+  /// equivalent to applying the `Split` step.
+  ///
+  /// `(?i:...)` (inline case-insensitive group) and `\p{L}`/`\p{N}` (Unicode
+  /// property escapes, needing `unicode: true`) are both supported by
+  /// Dart's `RegExp` as of the 3.12 SDK.
+  static final RegExp _splitPattern = RegExp(
+    r"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+",
+    unicode: true,
+  );
+
+  /// Loads an uncompressed `tokenizer.json` from disk (the form the model
+  /// bundle installs at runtime).
+  static Future<Qwen2BpeEncoder> fromTokenizerJson(String path) async {
+    final raw = await File(path).readAsString();
+    return Qwen2BpeEncoder.fromTokenizerJsonString(raw);
+  }
+
+  /// Same as [fromTokenizerJson], but from an already-in-memory JSON string
+  /// (e.g. a test that gunzips the golden fixture first).
+  factory Qwen2BpeEncoder.fromTokenizerJsonString(String jsonStr) {
+    return Qwen2BpeEncoder.fromTokenizerJsonMap(
+      jsonDecode(jsonStr) as Map<String, dynamic>,
+    );
+  }
+
+  /// Same as [fromTokenizerJson], but from an already-parsed `tokenizer.json`
+  /// document.
+  factory Qwen2BpeEncoder.fromTokenizerJsonMap(Map<String, dynamic> doc) {
+    final model = doc['model'] as Map<String, dynamic>;
+
+    final vocabJson = model['vocab'] as Map<String, dynamic>;
+    final vocab = <String, int>{
+      for (final entry in vocabJson.entries) entry.key: entry.value as int,
+    };
+
+    final mergesJson = model['merges'] as List<dynamic>;
+    final mergeRanks = <String, int>{};
+    for (var i = 0; i < mergesJson.length; i++) {
+      final entry = mergesJson[i];
+      final String a;
+      final String b;
+      if (entry is List) {
+        a = entry[0] as String;
+        b = entry[1] as String;
+      } else if (entry is String) {
+        final sp = entry.indexOf(' ');
+        if (sp < 0) {
+          throw FormatException('malformed merges entry: $entry');
+        }
+        a = entry.substring(0, sp);
+        b = entry.substring(sp + 1);
+      } else {
+        throw FormatException('unexpected merges entry type: $entry');
+      }
+      mergeRanks[_pairKey(a, b)] = i;
+    }
+
+    final addedTokensJson = doc['added_tokens'] as List<dynamic>? ?? const [];
+    final addedTokens =
+        [
+            for (final t in addedTokensJson)
+              _AddedToken(
+                content: (t as Map<String, dynamic>)['content'] as String,
+                id: t['id'] as int,
+              ),
+          ]
+          // Longest-match-first: see `_buildAddedTokenPattern`.
+          ..sort((x, y) => y.content.length.compareTo(x.content.length));
+
+    return Qwen2BpeEncoder._(
+      vocab: vocab,
+      mergeRanks: mergeRanks,
+      addedTokens: addedTokens,
+    );
+  }
+
+  static String _pairKey(String a, String b) => '$a $b';
+
+  /// Builds a single alternation over every added-token content string,
+  /// longest-first, so that `allMatches` performs longest-match-at-position
+  /// scanning (regex alternation picks the first alternative that matches
+  /// at a given start position; since alternatives are sorted by
+  /// descending length, that first success is always the longest possible
+  /// added token starting there). Mirrors the HF `AddedVocabulary` trie's
+  /// longest-match behavior for `added_tokens` (both `special: true` and
+  /// `special: false` entries participate -- HF's fast tokenizer splits on
+  /// *all* added tokens before pre-tokenization, not just the "special"
+  /// subset).
+  static RegExp? _buildAddedTokenPattern(List<_AddedToken> addedTokens) {
+    if (addedTokens.isEmpty) return null;
+    final alternatives = addedTokens
+        .map((t) => RegExp.escape(t.content))
+        .join('|');
+    return RegExp(alternatives);
+  }
+
+  /// Encodes [text] into token ids, reproducing the HF `tokenizers`
+  /// fast-tokenizer pipeline for this `tokenizer.json`.
+  List<int> encode(String text) {
+    final ids = <int>[];
+    for (final segment in _splitOnAddedTokens(text)) {
+      final addedId = segment.addedTokenId;
+      if (addedId != null) {
+        ids.add(addedId);
+        continue;
+      }
+      for (final match in _splitPattern.allMatches(segment.text!)) {
+        final piece = match[0]!;
+        if (piece.isEmpty) continue;
+        final byteLevel = _byteLevelEncode(piece);
+        for (final symbol in _bpe(byteLevel)) {
+          final id = _vocab[symbol];
+          if (id == null) {
+            throw StateError(
+              'Qwen2BpeEncoder: no vocab entry for BPE symbol '
+              '${symbol.runes.toList()} (from piece "$piece")',
+            );
+          }
+          ids.add(id);
+        }
+      }
+    }
+    return ids;
+  }
+
+  List<_Segment> _splitOnAddedTokens(String text) {
+    final pattern = _addedTokenPattern;
+    if (pattern == null) return [_Segment.text(text)];
+
+    final segments = <_Segment>[];
+    var lastEnd = 0;
+    for (final m in pattern.allMatches(text)) {
+      if (m.start > lastEnd) {
+        segments.add(_Segment.text(text.substring(lastEnd, m.start)));
+      }
+      final content = m[0]!;
+      segments.add(_Segment.added(_addedTokenById[content]!));
+      lastEnd = m.end;
+    }
+    if (lastEnd < text.length) {
+      segments.add(_Segment.text(text.substring(lastEnd)));
+    }
+    return segments;
+  }
+
+  /// UTF-8-encodes [piece] and maps each raw byte to its GPT-2
+  /// byte<->unicode character, producing the byte-level string the BPE
+  /// merge table and vocab operate on.
+  String _byteLevelEncode(String piece) {
+    final bytes = utf8.encode(piece);
+    final buf = StringBuffer();
+    for (final b in bytes) {
+      buf.writeCharCode(_byteToUnicode[b]!);
+    }
+    return buf.toString();
+  }
+
+  /// Standard byte-pair-encoding merge loop (the same algorithm as OpenAI's
+  /// reference `gpt2/encoder.py` `bpe()` / HF's slow-tokenizer `bpe()`):
+  /// each iteration finds the single lowest-rank pair present anywhere in
+  /// the symbol list, then merges *every* non-overlapping occurrence of
+  /// that exact pair in one left-to-right pass, and repeats until no known
+  /// pair remains. (Naively merging only the first occurrence found per
+  /// iteration -- and immediately reconsidering newly formed pairs -- can
+  /// diverge from this on inputs with repeated bigrams; merging the whole
+  /// pass before recomputing ranks is required for exact parity with the
+  /// reference tokenizer.)
+  List<String> _bpe(String word) {
+    var symbols = [for (final r in word.runes) String.fromCharCode(r)];
+    if (symbols.length < 2) return symbols;
+
+    while (true) {
+      int? bestRank;
+      String? bestFirst;
+      String? bestSecond;
+      for (var i = 0; i < symbols.length - 1; i++) {
+        final rank = _mergeRanks[_pairKey(symbols[i], symbols[i + 1])];
+        if (rank != null && (bestRank == null || rank < bestRank)) {
+          bestRank = rank;
+          bestFirst = symbols[i];
+          bestSecond = symbols[i + 1];
+        }
+      }
+      if (bestFirst == null || bestSecond == null) break;
+      final first = bestFirst;
+      final second = bestSecond;
+
+      final merged = <String>[];
+      var i = 0;
+      while (i < symbols.length) {
+        if (i < symbols.length - 1 &&
+            symbols[i] == first &&
+            symbols[i + 1] == second) {
+          merged.add(first + second);
+          i += 2;
+        } else {
+          merged.add(symbols[i]);
+          i += 1;
+        }
+      }
+      symbols = merged;
+      if (symbols.length == 1) break;
+    }
+    return symbols;
+  }
+}
+
+class _AddedToken {
+  const _AddedToken({required this.content, required this.id});
+  final String content;
+  final int id;
+}
+
+class _Segment {
+  const _Segment.text(this.text) : addedTokenId = null;
+  const _Segment.added(int id) : addedTokenId = id, text = null;
+
+  final String? text;
+  final int? addedTokenId;
+}
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen2_bpe_encoder_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen2_bpe_encoder_test.dart
new file mode 100644
index 00000000..e0a57c54
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen2_bpe_encoder_test.dart
@@ -0,0 +1,78 @@
+// Golden-driven tests for the Qwen2 byte-level BPE encoder used by the
+// Qwen3-TTS text frontend. The fixtures under test/golden/qwen3/ were
+// generated with the real HuggingFace `tokenizers` library (see Task 0's
+// golden generator) so they are the authoritative oracle for this encoder:
+// any divergence here is a real bug, not a golden-file artifact.
+//
+// `tokenizer.json` is committed gzipped (~2 MB compressed, ~11 MB raw) --
+// gunzip it in-memory via GZipCodec before handing the JSON string to
+// Qwen2BpeEncoder.fromTokenizerJsonString. Production code loads the
+// uncompressed `tokenizer.json` the model bundle installs at runtime via
+// Qwen2BpeEncoder.fromTokenizerJson(path).
+
+import 'dart:convert';
+import 'dart:io';
+
+import 'package:flutter_gemma_speech/src/qwen3/qwen2_bpe_encoder.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+Qwen2BpeEncoder _loadGoldenEncoder() {
+  final gz = File('test/golden/qwen3/tokenizer.json.gz').readAsBytesSync();
+  final jsonBytes = GZipCodec().decode(gz);
+  return Qwen2BpeEncoder.fromTokenizerJsonString(utf8.decode(jsonBytes));
+}
+
+void main() {
+  late Qwen2BpeEncoder enc;
+
+  setUpAll(() {
+    enc = _loadGoldenEncoder();
+  });
+
+  test('encode reproduces HF tokenizer ids for the templated prompt', () {
+    final g =
+        jsonDecode(File('test/golden/qwen3/ids.json').readAsStringSync())
+            as Map<String, dynamic>;
+    final expected = (g['ids'] as List).cast<int>();
+    expect(enc.encode(g['template'] as String), expected);
+  });
+
+  test('special tokens are atomic', () {
+    expect(enc.encode('<|im_start|>'), [151644]);
+    expect(enc.encode('<tts_pad>'), [151671]);
+  });
+
+  group('bpe_cases golden (diverse coverage)', () {
+    final cases =
+        jsonDecode(File('test/golden/qwen3/bpe_cases.json').readAsStringSync())
+            as Map<String, dynamic>;
+
+    for (final entry in cases.entries) {
+      final text = entry.key;
+      final expected = (entry.value as List).cast<int>();
+      test('encode(${jsonEncode(text)}) == $expected', () {
+        expect(enc.encode(text), expected);
+      });
+    }
+  });
+
+  test('fromTokenizerJson(path) loads an uncompressed tokenizer.json', () async {
+    // Production entry point: write the golden fixture out uncompressed
+    // once and load it via the file-path factory, to exercise the actual
+    // path used at runtime (not just the in-memory string factory the
+    // other tests use for speed).
+    final gz = File('test/golden/qwen3/tokenizer.json.gz').readAsBytesSync();
+    final jsonBytes = GZipCodec().decode(gz);
+    final tmp = File(
+      '${Directory.systemTemp.path}/qwen3_tokenizer_test_${DateTime.now().microsecondsSinceEpoch}.json',
+    );
+    await tmp.writeAsBytes(jsonBytes);
+    try {
+      final fileEncoder = await Qwen2BpeEncoder.fromTokenizerJson(tmp.path);
+      expect(fileEncoder.encode('<|im_start|>'), [151644]);
+      expect(fileEncoder.encode('Hello, world!'), [9707, 11, 1879, 0]);
+    } finally {
+      await tmp.delete();
+    }
+  });
+}

From 6cb427c08bbd837a496658d2ec19b2aef1d1e737 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 21:57:20 +0500
Subject: [PATCH 04/30] feat(qwen3): host embedding tables + text projection
 MLP

Qwen3Tables loads codec_embedding/mtp_embeddings whole (small) and keeps
text_embedding (622 MB) as an open RandomAccessFile with row-lookup via
Task 1.1's npyRowF16AsF32, never loading it fully. embedText() looks up
each id's row and runs it through the 2048->1024 SiLU projection MLP
ported from Qwen3TtsPipeline._project_text/_embed_text.
---
 .../lib/src/qwen3/qwen3_tables.dart           | 289 ++++++++++++++++++
 .../test/qwen3/qwen3_tables_test.dart         | 166 ++++++++++
 2 files changed, 455 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart
new file mode 100644
index 00000000..a8edd096
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart
@@ -0,0 +1,289 @@
+// Host embedding tables + text-projection MLP for the Qwen3-TTS pipeline.
+//
+// `Qwen3Tables` owns four on-disk NumPy tables shipped alongside the
+// Qwen3-TTS talker model:
+//  - `codec_embedding_fp32.npy`   (3072, 1024) <f4  — codec-token embeddings
+//  - `mtp_embeddings_fp16.npy`    (15, 2048, 1024) <f2 — MTP residual
+//                                 embeddings, one (2048,1024) table per of
+//                                 the 15 residual groups
+//  - `text_embedding_fp16.npy`    (151936, 2048) <f2 — the LLM's token
+//                                 embedding table, reused as the text
+//                                 frontend for TTS
+//  - `text_projection_fp32.npz`   {w1 (2048,2048), b1 (2048), w2 (1024,2048),
+//                                 b2 (1024)} <f4 — the SiLU MLP that
+//                                 projects text-embedding rows (2048-d, LLM
+//                                 hidden size) into talker space (1024-d)
+//
+// `codec_embedding` (12.5 MB) and `mtp_embeddings` (63 MB fp16 -> 126 MB
+// fp32) are small enough to load whole into memory. `text_embedding` is not
+// (622 MB fp16 on disk, ~1.2 GB up-cast to fp32) — it is kept as an open
+// `RandomAccessFile` + parsed `NpyHeader` and rows are read on demand via
+// [npyRowF16AsF32], which seeks directly to the row's byte offset instead of
+// loading the whole table. Callers MUST call [dispose] to close that file
+// handle.
+//
+// This file is pure Dart (`dart:io` + `dart:typed_data`) — no Flutter
+// import — so it can be unit-tested without a device.
+
+import 'dart:io';
+import 'dart:math' as math;
+import 'dart:typed_data';
+
+import 'npy_reader.dart';
+
+/// Hidden size of the LLM token-embedding table (`text_embedding`'s row
+/// width) — the input dimension of the text-projection MLP.
+const int _textEmbedDim = 2048;
+
+/// Talker hidden size — the output dimension of the text-projection MLP,
+/// and the row width of `codec_embedding` / `mtp_embeddings`.
+const int _talkerDim = 1024;
+
+/// Number of MTP (multi-token-prediction) residual groups.
+const int _mtpGroups = 15;
+
+/// Host-side embedding tables + text-projection MLP for Qwen3-TTS.
+///
+/// Turns text-token ids into 1024-d talker-space embeddings
+/// ([embedText]/[projectText]), and looks up codec-token / MTP-residual
+/// embeddings used while decoding audio frames ([codecEmbRow]/[mtpEmbRow]).
+class Qwen3Tables {
+  Qwen3Tables._({
+    required this._codecEmb,
+    required this._mtpEmb,
+    required this._textEmbFile,
+    required this._textEmbHeader,
+    required this._w1,
+    required this._b1,
+    required this._w2,
+    required this._b2,
+  });
+
+  /// Loads all four tables from disk.
+  ///
+  /// [codecEmbPath] and [mtpEmbPath] are read whole into memory.
+  /// [textEmbPath] is opened and kept as a [RandomAccessFile] — rows are
+  /// read on demand by [embedText] (call [dispose] when done with this
+  /// instance to close it). [projectionNpzPath] is a `.npz` archive with
+  /// members `w1`, `b1`, `w2`, `b2`.
+  static Future<Qwen3Tables> load({
+    required String codecEmbPath,
+    required String mtpEmbPath,
+    required String textEmbPath,
+    required String projectionNpzPath,
+  }) async {
+    final codecEmb = readNpyF32(codecEmbPath);
+    final mtpEmb = readNpyF16AsF32(mtpEmbPath);
+
+    final textEmbFile = File(textEmbPath).openSync();
+    final textEmbHeader = parseNpyHeader(textEmbFile);
+    if (textEmbHeader.dtype != '<f2') {
+      textEmbFile.closeSync();
+      throw StateError(
+        'Qwen3Tables.load: expected text_embedding dtype <f2, got '
+        '${textEmbHeader.dtype} ($textEmbPath)',
+      );
+    }
+    if (textEmbHeader.shape.length != 2 ||
+        textEmbHeader.shape[1] != _textEmbedDim) {
+      textEmbFile.closeSync();
+      throw StateError(
+        'Qwen3Tables.load: expected text_embedding shape (*, $_textEmbedDim), '
+        'got ${textEmbHeader.shape} ($textEmbPath)',
+      );
+    }
+
+    final proj = readNpzF32(projectionNpzPath);
+    final w1 = _requireProjMember(proj, 'w1', projectionNpzPath);
+    final b1 = _requireProjMember(proj, 'b1', projectionNpzPath);
+    final w2 = _requireProjMember(proj, 'w2', projectionNpzPath);
+    final b2 = _requireProjMember(proj, 'b2', projectionNpzPath);
+    if (w1.length != _textEmbedDim * _textEmbedDim) {
+      textEmbFile.closeSync();
+      throw StateError(
+        "Qwen3Tables.load: 'w1' expected ($_textEmbedDim,$_textEmbedDim), "
+        'got ${w1.length} elements ($projectionNpzPath)',
+      );
+    }
+    if (b1.length != _textEmbedDim) {
+      textEmbFile.closeSync();
+      throw StateError(
+        "Qwen3Tables.load: 'b1' expected ($_textEmbedDim,), got "
+        '${b1.length} elements ($projectionNpzPath)',
+      );
+    }
+    if (w2.length != _talkerDim * _textEmbedDim) {
+      textEmbFile.closeSync();
+      throw StateError(
+        "Qwen3Tables.load: 'w2' expected ($_talkerDim,$_textEmbedDim), got "
+        '${w2.length} elements ($projectionNpzPath)',
+      );
+    }
+    if (b2.length != _talkerDim) {
+      textEmbFile.closeSync();
+      throw StateError(
+        "Qwen3Tables.load: 'b2' expected ($_talkerDim,), got "
+        '${b2.length} elements ($projectionNpzPath)',
+      );
+    }
+
+    return Qwen3Tables._(
+      codecEmb: codecEmb,
+      mtpEmb: mtpEmb,
+      textEmbFile: textEmbFile,
+      textEmbHeader: textEmbHeader,
+      w1: w1,
+      b1: b1,
+      w2: w2,
+      b2: b2,
+    );
+  }
+
+  static Float32List _requireProjMember(
+    Map<String, Float32List> proj,
+    String name,
+    String path,
+  ) {
+    final m = proj[name];
+    if (m == null) {
+      throw StateError(
+        "Qwen3Tables.load: projection .npz missing member '$name' ($path)",
+      );
+    }
+    return m;
+  }
+
+  /// Codec-token embedding table, `(3072, 1024)` <f4, loaded whole.
+  final Float32List _codecEmb;
+
+  /// MTP residual-embedding table, `(15, 2048, 1024)`, up-cast from <f2 to
+  /// <f4 and loaded whole.
+  final Float32List _mtpEmb;
+
+  /// Open handle to `text_embedding_fp16.npy` — kept open (not loaded
+  /// whole) so individual rows can be read on demand via [npyRowF16AsF32].
+  final RandomAccessFile _textEmbFile;
+  final NpyHeader _textEmbHeader;
+
+  /// Text-projection MLP weights, from the `.npz`: `w1` (2048,2048), `b1`
+  /// (2048), `w2` (1024,2048), `b2` (1024), all <f4.
+  final Float32List _w1;
+  final Float32List _b1;
+  final Float32List _w2;
+  final Float32List _b2;
+
+  bool _disposed = false;
+
+  /// Looks up and projects text-embedding rows to talker space: for each id
+  /// in [ids], reads its `text_embedding` row (2048-d, fp16 up-cast to
+  /// fp32), stacks the rows `[ids.length, 2048]`, and runs [projectText].
+  ///
+  /// Returns a flat `[ids.length * 1024]` array (row-major).
+  Float32List embedText(List<int> ids) {
+    _checkNotDisposed();
+    final n = ids.length;
+    final rows = Float32List(n * _textEmbedDim);
+    for (var i = 0; i < n; i++) {
+      final row = npyRowF16AsF32(_textEmbFile, _textEmbHeader, ids[i]);
+      rows.setRange(i * _textEmbedDim, (i + 1) * _textEmbedDim, row);
+    }
+    return projectText(rows);
+  }
+
+  /// Applies the 2048->1024 text-projection MLP (SiLU activation) to [rows]
+  /// (flat `[n * 2048]`, row-major). Returns a flat `[n * 1024]` array.
+  ///
+  /// Ports `Qwen3TtsPipeline._project_text` (`qwen3_tts_pipeline.py:268`):
+  /// `h = rows @ w1.T + b1; h = h * sigmoid(h); out = h @ w2.T + b2`.
+  /// `w1` is `(2048,2048)` so `h[j] = sum_k rows[k] * w1[j,k] + b1[j]`;
+  /// `w2` is `(1024,2048)` so `out[i] = sum_j h[j] * w2[i,j] + b2[i]`.
+  Float32List projectText(Float32List rows) {
+    _checkNotDisposed();
+    if (rows.length % _textEmbedDim != 0) {
+      throw ArgumentError(
+        'projectText: rows length ${rows.length} is not a multiple of '
+        '$_textEmbedDim',
+      );
+    }
+    final n = rows.length ~/ _textEmbedDim;
+    final out = Float32List(n * _talkerDim);
+    final h = Float32List(_textEmbedDim);
+
+    for (var row = 0; row < n; row++) {
+      final rowOffset = row * _textEmbedDim;
+
+      // h[j] = sum_k rows[k] * w1[j,k] + b1[j]; then SiLU: h = h * sigmoid(h).
+      for (var j = 0; j < _textEmbedDim; j++) {
+        var acc = 0.0;
+        final w1Row = j * _textEmbedDim;
+        for (var k = 0; k < _textEmbedDim; k++) {
+          acc += rows[rowOffset + k] * _w1[w1Row + k];
+        }
+        acc += _b1[j];
+        h[j] = acc / (1.0 + math.exp(-acc));
+      }
+
+      // out[i] = sum_j h[j] * w2[i,j] + b2[i].
+      final outOffset = row * _talkerDim;
+      for (var i = 0; i < _talkerDim; i++) {
+        var acc = 0.0;
+        final w2Row = i * _textEmbedDim;
+        for (var j = 0; j < _textEmbedDim; j++) {
+          acc += h[j] * _w2[w2Row + j];
+        }
+        out[outOffset + i] = acc + _b2[i];
+      }
+    }
+    return out;
+  }
+
+  /// Returns codec-token embedding row [id] (`[1024]`), as a view into the
+  /// `(3072, 1024)` `codec_embedding` table (backed by the same buffer — do
+  /// not mutate, and do not use after [dispose]).
+  Float32List codecEmbRow(int id) {
+    _checkNotDisposed();
+    final rows = _codecEmb.length ~/ _talkerDim;
+    if (id < 0 || id >= rows) {
+      throw RangeError.range(id, 0, rows - 1, 'id');
+    }
+    return Float32List.sublistView(
+      _codecEmb,
+      id * _talkerDim,
+      (id + 1) * _talkerDim,
+    );
+  }
+
+  /// Returns MTP residual-embedding row `[group][id]` (`[1024]`), as a view
+  /// into the `(15, 2048, 1024)` `mtp_embeddings` table (backed by the same
+  /// buffer — do not mutate, and do not use after [dispose]).
+  Float32List mtpEmbRow(int group, int id) {
+    _checkNotDisposed();
+    if (group < 0 || group >= _mtpGroups) {
+      throw RangeError.range(group, 0, _mtpGroups - 1, 'group');
+    }
+    final idsPerGroup = _mtpEmb.length ~/ (_mtpGroups * _talkerDim);
+    if (id < 0 || id >= idsPerGroup) {
+      throw RangeError.range(id, 0, idsPerGroup - 1, 'id');
+    }
+    final base = (group * idsPerGroup + id) * _talkerDim;
+    return Float32List.sublistView(_mtpEmb, base, base + _talkerDim);
+  }
+
+  void _checkNotDisposed() {
+    if (_disposed) {
+      throw StateError('Qwen3Tables: used after dispose()');
+    }
+  }
+
+  /// Closes the open `text_embedding` file handle. Safe to call more than
+  /// once. The instance must not be used after this call.
+  void dispose() {
+    if (_disposed) return;
+    _disposed = true;
+    _textEmbFile.closeSync();
+  }
+
+  /// Alias for [dispose] (symmetry with the closeable conventions used
+  /// elsewhere in the SDK, e.g. `InferenceModelSession.close()`).
+  void close() => dispose();
+}
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart
new file mode 100644
index 00000000..b944e9e9
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart
@@ -0,0 +1,166 @@
+// Golden test for `Qwen3Tables` — the host embedding tables + text
+// projection MLP that turn Qwen3-TTS token ids into 1024-d talker-space
+// embeddings.
+//
+// This is the first artifact-heavy test in the Qwen3-TTS port: the real
+// model tables (~722 MB — codec_embedding_fp32.npy, mtp_embeddings_fp16.npy,
+// text_embedding_fp16.npy, text_projection_fp32.npz) are NOT committed to
+// the repo. They live in the local HuggingFace cache (see [_defaultTablesDir]
+// below) or wherever `QWEN3_MODEL_DIR` points. When the tables are absent
+// (e.g. in CI without the artifact fetched) the test skips gracefully so the
+// suite stays green; when present (as they are for local device runs) it
+// asserts the golden.
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:convert';
+import 'dart:io';
+import 'dart:math' as math;
+import 'dart:typed_data';
+
+import 'package:flutter_gemma_speech/src/qwen3/npy_reader.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tables.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot's `tables/` directory —
+/// the local HuggingFace cache path for
+/// `litert-community/Qwen3-TTS-12Hz-0.6B-Base`. Override with the
+/// `QWEN3_MODEL_DIR` environment variable (pointing at a snapshot dir that
+/// contains a `tables/` subdirectory) to run against a different snapshot.
+String _defaultTablesDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66/tables';
+}
+
+String _tablesDir() => Platform.environment['QWEN3_MODEL_DIR'] != null
+    ? '${Platform.environment['QWEN3_MODEL_DIR']}/tables'
+    : _defaultTablesDir();
+
+void _expectClose(Float32List got, Float32List ref, {required double tol}) {
+  expect(
+    got.length,
+    ref.length,
+    reason: 'length mismatch: got ${got.length}, ref ${ref.length}',
+  );
+  var maxDiff = 0.0;
+  var maxDiffIndex = -1;
+  for (var i = 0; i < got.length; i++) {
+    final diff = (got[i] - ref[i]).abs();
+    if (diff > maxDiff) {
+      maxDiff = diff;
+      maxDiffIndex = i;
+    }
+  }
+  expect(
+    maxDiff,
+    lessThanOrEqualTo(tol),
+    reason:
+        'max abs diff $maxDiff at index $maxDiffIndex exceeds tolerance '
+        '$tol (got=${got[maxDiffIndex]}, ref=${ref[maxDiffIndex]})',
+  );
+}
+
+void main() {
+  final tablesDir = _tablesDir();
+
+  test(
+    'embedText matches reference within 2e-3 (fp16 table up-cast)',
+    () async {
+      if (!Directory(tablesDir).existsSync()) {
+        markTestSkipped(
+          'Qwen3-TTS model tables not found at $tablesDir — set '
+          'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+        );
+        return;
+      }
+
+      final t = await Qwen3Tables.load(
+        codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
+        mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
+        textEmbPath: '$tablesDir/text_embedding_fp16.npy',
+        projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
+      );
+      try {
+        final idsJson =
+            jsonDecode(File('test/golden/qwen3/ids.json').readAsStringSync())
+                as Map<String, dynamic>;
+        final ids = (idsJson['ids'] as List).cast<int>();
+
+        final got = t.embedText(ids);
+        final ref = readNpyF32('test/golden/qwen3/embed_text.npy');
+
+        expect(got.length, ids.length * 1024);
+        _expectClose(got, ref, tol: 2e-3);
+      } finally {
+        t.dispose();
+      }
+    },
+  );
+
+  test('codecEmbRow / mtpEmbRow return 1024-d rows without OOB', () {
+    if (!Directory(tablesDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model tables not found at $tablesDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    Qwen3Tables.load(
+      codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
+      mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
+      textEmbPath: '$tablesDir/text_embedding_fp16.npy',
+      projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
+    ).then((t) {
+      try {
+        final codecRow = t.codecEmbRow(0);
+        expect(codecRow.length, 1024);
+        expect(codecRow.every((v) => v.isFinite), isTrue);
+
+        final lastCodecRow = t.codecEmbRow(3071);
+        expect(lastCodecRow.length, 1024);
+
+        final mtpRow = t.mtpEmbRow(0, 0);
+        expect(mtpRow.length, 1024);
+        expect(mtpRow.every((v) => v.isFinite), isTrue);
+
+        final lastMtpRow = t.mtpEmbRow(14, 2047);
+        expect(lastMtpRow.length, 1024);
+      } finally {
+        t.dispose();
+      }
+    });
+  });
+
+  test('projectText SiLU MLP shape: [n*2048] -> [n*1024]', () {
+    if (!Directory(tablesDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model tables not found at $tablesDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    Qwen3Tables.load(
+      codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
+      mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
+      textEmbPath: '$tablesDir/text_embedding_fp16.npy',
+      projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
+    ).then((t) {
+      try {
+        final rows = Float32List(3 * 2048);
+        final rng = math.Random(7);
+        for (var i = 0; i < rows.length; i++) {
+          rows[i] = rng.nextDouble() * 2 - 1;
+        }
+        final out = t.projectText(rows);
+        expect(out.length, 3 * 1024);
+        expect(out.every((v) => v.isFinite), isTrue);
+      } finally {
+        t.dispose();
+      }
+    });
+  });
+}

From ebb2f1d06127d4fba0295feb13290e600f85ac3e Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 22:02:13 +0500
Subject: [PATCH 05/30] fix(qwen3): await Qwen3Tables.load in the two tests
 that used .then()

Tests 2 and 3 fired-and-forgot the load future, so assertions could run
after the test body returned once load() gains real async I/O. Match
test 1's await pattern.
---
 .../test/qwen3/qwen3_tables_test.dart         | 70 +++++++++----------
 1 file changed, 34 insertions(+), 36 deletions(-)

diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart
index b944e9e9..d9755402 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_tables_test.dart
@@ -99,7 +99,7 @@ void main() {
     },
   );
 
-  test('codecEmbRow / mtpEmbRow return 1024-d rows without OOB', () {
+  test('codecEmbRow / mtpEmbRow return 1024-d rows without OOB', () async {
     if (!Directory(tablesDir).existsSync()) {
       markTestSkipped(
         'Qwen3-TTS model tables not found at $tablesDir — set '
@@ -108,33 +108,32 @@ void main() {
       return;
     }
 
-    Qwen3Tables.load(
+    final t = await Qwen3Tables.load(
       codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
       mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
       textEmbPath: '$tablesDir/text_embedding_fp16.npy',
       projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
-    ).then((t) {
-      try {
-        final codecRow = t.codecEmbRow(0);
-        expect(codecRow.length, 1024);
-        expect(codecRow.every((v) => v.isFinite), isTrue);
-
-        final lastCodecRow = t.codecEmbRow(3071);
-        expect(lastCodecRow.length, 1024);
-
-        final mtpRow = t.mtpEmbRow(0, 0);
-        expect(mtpRow.length, 1024);
-        expect(mtpRow.every((v) => v.isFinite), isTrue);
-
-        final lastMtpRow = t.mtpEmbRow(14, 2047);
-        expect(lastMtpRow.length, 1024);
-      } finally {
-        t.dispose();
-      }
-    });
+    );
+    try {
+      final codecRow = t.codecEmbRow(0);
+      expect(codecRow.length, 1024);
+      expect(codecRow.every((v) => v.isFinite), isTrue);
+
+      final lastCodecRow = t.codecEmbRow(3071);
+      expect(lastCodecRow.length, 1024);
+
+      final mtpRow = t.mtpEmbRow(0, 0);
+      expect(mtpRow.length, 1024);
+      expect(mtpRow.every((v) => v.isFinite), isTrue);
+
+      final lastMtpRow = t.mtpEmbRow(14, 2047);
+      expect(lastMtpRow.length, 1024);
+    } finally {
+      t.dispose();
+    }
   });
 
-  test('projectText SiLU MLP shape: [n*2048] -> [n*1024]', () {
+  test('projectText SiLU MLP shape: [n*2048] -> [n*1024]', () async {
     if (!Directory(tablesDir).existsSync()) {
       markTestSkipped(
         'Qwen3-TTS model tables not found at $tablesDir — set '
@@ -143,24 +142,23 @@ void main() {
       return;
     }
 
-    Qwen3Tables.load(
+    final t = await Qwen3Tables.load(
       codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
       mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
       textEmbPath: '$tablesDir/text_embedding_fp16.npy',
       projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
-    ).then((t) {
-      try {
-        final rows = Float32List(3 * 2048);
-        final rng = math.Random(7);
-        for (var i = 0; i < rows.length; i++) {
-          rows[i] = rng.nextDouble() * 2 - 1;
-        }
-        final out = t.projectText(rows);
-        expect(out.length, 3 * 1024);
-        expect(out.every((v) => v.isFinite), isTrue);
-      } finally {
-        t.dispose();
+    );
+    try {
+      final rows = Float32List(3 * 2048);
+      final rng = math.Random(7);
+      for (var i = 0; i < rows.length; i++) {
+        rows[i] = rng.nextDouble() * 2 - 1;
       }
-    });
+      final out = t.projectText(rows);
+      expect(out.length, 3 * 1024);
+      expect(out.every((v) => v.isFinite), isTrue);
+    } finally {
+      t.dispose();
+    }
   });
 }

From 6ae13e325fed901ce8573e9a070f2788b28d6b94 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 22:13:55 +0500
Subject: [PATCH 06/30] feat(qwen3): prompt-embedding assembly (x-vector,
 language)

---
 .../lib/src/qwen3/qwen3_prompt.dart           | 223 ++++++++++++++++++
 .../test/qwen3/qwen3_prompt_test.dart         | 162 +++++++++++++
 2 files changed, 385 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_prompt_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
new file mode 100644
index 00000000..43bd1560
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
@@ -0,0 +1,223 @@
+// Prompt-embedding assembly for the Qwen3-TTS talker.
+//
+// `Qwen3Prompt.build` turns a text-token id sequence + a speaker x-vector +
+// a language into:
+//  - `prefill` — the fixed-length (~10-row) prompt embeddings fed to the
+//    talker's `prefill_32` signature (role text + control/x-vector rows +
+//    the first streamed text token),
+//  - `trailing` — the rest of the text, one 1024-d embedding per decoded
+//    audio frame, consumed during the per-frame decode loop,
+//  - `ttsPad` — the fallback embedding used once `trailing` is exhausted.
+//
+// Ports `Qwen3TtsPipeline._build_prompt` verbatim from
+// `text_to_speech_lm/python/qwen3_tts_pipeline.py:279-313` (plus its
+// module-level token constants at lines 43-70), reading `ids` (already
+// tokenized by the frontend, see `Qwen2BpeEncoder`) instead of re-tokenizing
+// raw text.
+//
+// This file is pure Dart (`dart:typed_data` only) — no Flutter import — so
+// it can be unit-tested without a device.
+
+import 'dart:typed_data';
+
+import 'qwen3_tables.dart';
+
+/// Talker hidden size — width of every embedding row this module handles.
+const int _hidden = 1024;
+
+// Talker codec-token vocabulary layout (ids >= 2048 are control tokens).
+// qwen3_tts_pipeline.py:44-51.
+const int _codecPad = 2148;
+const int _codecBos = 2149;
+const int _codecThink = 2154;
+const int _codecNothink = 2155;
+const int _codecThinkBos = 2156;
+const int _codecThinkEos = 2157;
+
+// Text-side special tokens (Qwen2 BPE vocabulary). qwen3_tts_pipeline.py:54-56.
+const int _ttsBos = 151672;
+const int _ttsEos = 151673;
+const int _ttsPad = 151671;
+
+/// Language id map from the model config (`talker_config.codec_language_id`).
+/// qwen3_tts_pipeline.py:59-70.
+const Map<String, int> languageIds = {
+  'chinese': 2055,
+  'english': 2050,
+  'german': 2053,
+  'italian': 2070,
+  'portuguese': 2071,
+  'spanish': 2054,
+  'japanese': 2058,
+  'korean': 2064,
+  'french': 2061,
+  'russian': 2069,
+};
+
+/// Result of [Qwen3Prompt.build]: the talker's fixed-length prefill
+/// embeddings plus the per-frame streamed text conditioning consumed while
+/// decoding audio frames.
+class Qwen3PromptResult {
+  const Qwen3PromptResult({
+    required this.prefill,
+    required this.promptLen,
+    required this.trailing,
+    required this.ttsPad,
+  });
+
+  /// Flattened prefill embeddings, row-major `[promptLen * 1024]`. Fed to
+  /// the talker's `prefill_32` signature (right-padded to 32 rows by the
+  /// caller — see `_run_prefill`, a later task).
+  final Float32List prefill;
+
+  /// Number of rows in [prefill] (`prefill.length == promptLen * 1024`).
+  /// Fixed at `3 (role) + (codec_pre.length - 1) (body) + 1 (first_text)` —
+  /// decoupled from text length (only `ids[:4]` feed the prefill; the rest
+  /// of the text streams via [trailing]).
+  final int promptLen;
+
+  /// Per-frame streamed text-conditioning rows, each `[1024]`: the
+  /// remaining text embeddings (`ids[4:-5]`) followed by the `tts_eos`
+  /// embedding. Consumed one row per decoded audio frame; once exhausted,
+  /// [ttsPad] is added instead (see the decode loop, a later task).
+  final List<Float32List> trailing;
+
+  /// The `[1024]` TTS pad embedding, added once [trailing] is exhausted.
+  final Float32List ttsPad;
+}
+
+/// Builds the Qwen3-TTS talker prompt.
+///
+/// Ports `Qwen3TtsPipeline._build_prompt`
+/// (`text_to_speech_lm/python/qwen3_tts_pipeline.py:279-313`) verbatim,
+/// given already-tokenized [ids] (the frontend's chat-template encoding —
+/// see `Qwen2BpeEncoder`), a `[1024]` speaker x-vector [speaker], and a
+/// [language] (one of [languageIds]' keys, case-insensitive, or `'auto'`).
+class Qwen3Prompt {
+  Qwen3Prompt._();
+
+  static Qwen3PromptResult build({
+    required List<int> ids,
+    required Float32List speaker,
+    required String language,
+    required Qwen3Tables tables,
+  }) {
+    if (speaker.length != _hidden) {
+      throw ArgumentError.value(
+        speaker.length,
+        'speaker.length',
+        'Qwen3Prompt.build: speaker must be [$_hidden]',
+      );
+    }
+    if (ids.length < 4) {
+      throw ArgumentError.value(
+        ids.length,
+        'ids.length',
+        'Qwen3Prompt.build: ids must have at least 4 entries '
+            '(role = ids[0:3], first text token = ids[3:4])',
+      );
+    }
+
+    // qwen3_tts_pipeline.py:295-299.
+    final List<int> control;
+    if (language == 'auto') {
+      control = [_codecNothink, _codecThinkBos, _codecThinkEos];
+    } else {
+      final langId = languageIds[language.toLowerCase()];
+      if (langId == null) {
+        final sortedNames = (languageIds.keys.toList()..sort()).join(', ');
+        throw ArgumentError.value(
+          language,
+          'language',
+          'Qwen3Prompt.build: language must be "auto" or one of: '
+              '$sortedNames',
+        );
+      }
+      control = [_codecThink, _codecThinkBos, langId, _codecThinkEos];
+    }
+
+    // tts_bos, tts_eos, tts_pad = embedText([_TTS_BOS, _TTS_EOS, _TTS_PAD]).
+    // qwen3_tts_pipeline.py:293-294.
+    final ttsSpecial = tables.embedText([_ttsBos, _ttsEos, _ttsPad]);
+    final ttsBosRow = Float32List.sublistView(ttsSpecial, 0, _hidden);
+    final ttsEosRow = Float32List.sublistView(ttsSpecial, _hidden, 2 * _hidden);
+    final ttsPad = Float32List.sublistView(
+      ttsSpecial,
+      2 * _hidden,
+      3 * _hidden,
+    );
+
+    // codec_pre = codec_emb[control] ++ [speaker] ++ codec_emb[[PAD, BOS]].
+    // qwen3_tts_pipeline.py:300-304.
+    final codecPreLen = control.length + 1 + 2;
+    final codecPre = List<Float32List>.generate(codecPreLen, (i) {
+      if (i < control.length) return tables.codecEmbRow(control[i]);
+      if (i == control.length) return speaker;
+      if (i == control.length + 1) return tables.codecEmbRow(_codecPad);
+      return tables.codecEmbRow(_codecBos);
+    });
+
+    // role = embedText(ids[0:3]). qwen3_tts_pipeline.py:306.
+    final role = tables.embedText(ids.sublist(0, 3));
+
+    // pads = repeat(tts_pad, len(codec_pre) - 2);
+    // body = concat([pads, tts_bos]) + codec_pre[:-1]  (element-wise add).
+    // qwen3_tts_pipeline.py:307-308.
+    final bodyLen = codecPreLen - 1;
+    final padsLen = codecPreLen - 2;
+    final body = Float32List(bodyLen * _hidden);
+    for (var i = 0; i < bodyLen; i++) {
+      final base = i * _hidden;
+      final addend = i < padsLen ? ttsPad : ttsBosRow;
+      final codecRow = codecPre[i];
+      for (var k = 0; k < _hidden; k++) {
+        body[base + k] = addend[k] + codecRow[k];
+      }
+    }
+
+    // first_text = embedText(ids[3:4]) + codec_pre[-1]. qwen3_tts_pipeline.py:309.
+    final firstTextEmbed = tables.embedText([ids[3]]);
+    final firstText = Float32List(_hidden);
+    final lastCodecPre = codecPre[codecPreLen - 1];
+    for (var k = 0; k < _hidden; k++) {
+      firstText[k] = firstTextEmbed[k] + lastCodecPre[k];
+    }
+
+    // prefill = concat(role, body, first_text). qwen3_tts_pipeline.py:310.
+    final promptLen = 3 + bodyLen + 1;
+    if (promptLen > 32) {
+      // Defensive sanity check mirroring `_run_prefill`'s `p > 32` guard
+      // (qwen3_tts_pipeline.py:318-319) — the talker's prefill signature is
+      // a fixed 32-row buffer. This is NOT a text-length limit: only role +
+      // control/x-vector rows enter the prefill (promptLen is fixed at 10
+      // for every supported language), so it never trips in practice.
+      throw StateError(
+        'Qwen3Prompt.build: prefill length $promptLen exceeds the talker '
+        'prefill_32 signature (32)',
+      );
+    }
+    final prefill = Float32List(promptLen * _hidden);
+    prefill.setRange(0, 3 * _hidden, role);
+    prefill.setRange(3 * _hidden, (3 + bodyLen) * _hidden, body);
+    prefill.setRange((3 + bodyLen) * _hidden, promptLen * _hidden, firstText);
+
+    // trailing = concat(embedText(ids[4:-5]), tts_eos). qwen3_tts_pipeline.py:311-312.
+    // Mirrors Python's permissive `ids[4:-5]` slicing (clamped to empty
+    // rather than throwing) for very short inputs where `len(ids) - 5 < 4`.
+    final trailingStop = ids.length - 5 < 4 ? 4 : ids.length - 5;
+    final trailingTextIds = ids.sublist(4, trailingStop);
+    final trailingText = tables.embedText(trailingTextIds);
+    final trailing = <Float32List>[
+      for (var i = 0; i < trailingTextIds.length; i++)
+        Float32List.sublistView(trailingText, i * _hidden, (i + 1) * _hidden),
+      Float32List.fromList(ttsEosRow),
+    ];
+
+    return Qwen3PromptResult(
+      prefill: prefill,
+      promptLen: promptLen,
+      trailing: trailing,
+      ttsPad: Float32List.fromList(ttsPad),
+    );
+  }
+}
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_prompt_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_prompt_test.dart
new file mode 100644
index 00000000..2d2377cb
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_prompt_test.dart
@@ -0,0 +1,162 @@
+// Golden test for `Qwen3Prompt.build` — the talker prompt-embedding
+// assembly (role text, control/x-vector rows, streamed text conditioning)
+// for the Qwen3-TTS pipeline.
+//
+// Like `qwen3_tables_test.dart`, this is an artifact-heavy test: it needs
+// the real Qwen3-TTS host tables (~722 MB) via `Qwen3Tables` to compute
+// `embedText`/`codecEmbRow` results, which are not committed to the repo.
+// The golden reference (`test/golden/qwen3/prompt.npz`, `ids.json`,
+// `voices/demo_speaker.npy`) IS committed (Task 0). When the tables are
+// absent (e.g. CI without the artifact fetched) the test skips gracefully;
+// when present (local device runs) it asserts the golden.
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:convert';
+import 'dart:io';
+import 'dart:typed_data';
+
+import 'package:flutter_gemma_speech/src/qwen3/npy_reader.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_prompt.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tables.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot's `tables/` directory —
+/// mirrors `qwen3_tables_test.dart`'s `_defaultTablesDir`. Override with the
+/// `QWEN3_MODEL_DIR` environment variable.
+String _defaultTablesDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66/tables';
+}
+
+String _tablesDir() => Platform.environment['QWEN3_MODEL_DIR'] != null
+    ? '${Platform.environment['QWEN3_MODEL_DIR']}/tables'
+    : _defaultTablesDir();
+
+double _maxAbsDiff(Float32List got, Float32List ref) {
+  var maxDiff = 0.0;
+  for (var i = 0; i < got.length; i++) {
+    final diff = (got[i] - ref[i]).abs();
+    if (diff > maxDiff) maxDiff = diff;
+  }
+  return maxDiff;
+}
+
+void _expectClose(
+  Float32List got,
+  Float32List ref, {
+  required double tol,
+  required String label,
+}) {
+  expect(
+    got.length,
+    ref.length,
+    reason: '$label: length mismatch: got ${got.length}, ref ${ref.length}',
+  );
+  final maxDiff = _maxAbsDiff(got, ref);
+  expect(
+    maxDiff,
+    lessThanOrEqualTo(tol),
+    reason: '$label: max abs diff $maxDiff exceeds tolerance $tol',
+  );
+}
+
+void main() {
+  final tablesDir = _tablesDir();
+
+  test('Qwen3Prompt.build matches prompt.npz golden within 2e-3 '
+      '(prefill, trailing, tts_pad)', () async {
+    if (!Directory(tablesDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model tables not found at $tablesDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final tables = await Qwen3Tables.load(
+      codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
+      mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
+      textEmbPath: '$tablesDir/text_embedding_fp16.npy',
+      projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
+    );
+    try {
+      final idsJson =
+          jsonDecode(File('test/golden/qwen3/ids.json').readAsStringSync())
+              as Map<String, dynamic>;
+      final ids = (idsJson['ids'] as List).cast<int>();
+
+      final speaker = readNpyF32('test/golden/qwen3/voices/demo_speaker.npy');
+      expect(speaker.length, 1024);
+
+      final golden = readNpzF32('test/golden/qwen3/prompt.npz');
+      final goldenPrefill = golden['prefill']!;
+      final goldenTrailing = golden['trailing']!;
+      final goldenTtsPad = golden['tts_pad']!;
+
+      final result = Qwen3Prompt.build(
+        ids: ids,
+        speaker: speaker,
+        language: 'english',
+        tables: tables,
+      );
+
+      // english control -> codec_pre = 4(control) + 1(speaker) + 2(pad,bos)
+      // = 7 rows -> promptLen = 3(role) + 6(body) + 1(first_text) = 10.
+      expect(result.promptLen, 10);
+      expect(result.prefill.length, result.promptLen * 1024);
+      _expectClose(result.prefill, goldenPrefill, tol: 2e-3, label: 'prefill');
+
+      expect(result.trailing.length, goldenTrailing.length ~/ 1024);
+      final flatTrailing = Float32List(result.trailing.length * 1024);
+      for (var i = 0; i < result.trailing.length; i++) {
+        expect(result.trailing[i].length, 1024);
+        flatTrailing.setRange(i * 1024, (i + 1) * 1024, result.trailing[i]);
+      }
+      _expectClose(flatTrailing, goldenTrailing, tol: 2e-3, label: 'trailing');
+
+      expect(result.ttsPad.length, 1024);
+      _expectClose(result.ttsPad, goldenTtsPad, tol: 2e-3, label: 'tts_pad');
+    } finally {
+      tables.dispose();
+    }
+  });
+
+  test('Qwen3Prompt.build rejects an unsupported language', () async {
+    if (!Directory(tablesDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model tables not found at $tablesDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final tables = await Qwen3Tables.load(
+      codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
+      mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
+      textEmbPath: '$tablesDir/text_embedding_fp16.npy',
+      projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
+    );
+    try {
+      final idsJson =
+          jsonDecode(File('test/golden/qwen3/ids.json').readAsStringSync())
+              as Map<String, dynamic>;
+      final ids = (idsJson['ids'] as List).cast<int>();
+      final speaker = readNpyF32('test/golden/qwen3/voices/demo_speaker.npy');
+
+      expect(
+        () => Qwen3Prompt.build(
+          ids: ids,
+          speaker: speaker,
+          language: 'klingon',
+          tables: tables,
+        ),
+        throwsArgumentError,
+      );
+    } finally {
+      tables.dispose();
+    }
+  });
+}

From 5bbf92ad2075e08e5125497b8bcf24aee991b0b4 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 22:26:15 +0500
Subject: [PATCH 07/30] feat(qwen3): sampler + cb0 scoring (suppress,
 rep-penalty)

---
 .../lib/src/qwen3/qwen3_sampler.dart          | 183 +++++++++++
 .../test/qwen3/qwen3_sampler_test.dart        | 292 ++++++++++++++++++
 2 files changed, 475 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart
new file mode 100644
index 00000000..1ed0fba5
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart
@@ -0,0 +1,183 @@
+// Sampler + cb0 scoring for the Qwen3-TTS talker's per-frame codebook-0
+// (cb0) token pick.
+//
+// Ports `_pick` (`text_to_speech_lm/python/qwen3_tts_pipeline.py:467-490`)
+// and the per-step scoring edits applied before it in the decode loop
+// (`qwen3_tts_pipeline.py:223-225` for `suppress`, `:231-237` for the
+// min-new-tokens guard + HF repetition penalty) verbatim.
+//
+// This file is pure Dart (`dart:math` / `dart:typed_data` only) — no
+// Flutter import — so it can be unit-tested without a device and needs no
+// model tables (all inputs are hand-constructable vectors).
+
+import 'dart:math';
+import 'dart:typed_data';
+
+/// Talker codec-token vocabulary size. qwen3_tts_pipeline.py:44.
+const int _codecVocab = 3072;
+
+/// Codec end-of-sequence token id. qwen3_tts_pipeline.py:47.
+const int _codecEos = 2150;
+
+/// Large negative "suppressed" score, added to logits to rule a token out
+/// of the argmax/sampling pick without producing `-inf` arithmetic hazards.
+/// qwen3_tts_pipeline.py:77.
+const double _negInf = -1e9;
+
+/// Builds the per-step control-token suppression vector.
+///
+/// Every codec-vocabulary index `>= 2048` is a control/special token (only
+/// `< 2048` are audible codebook-0 codes), so those are suppressed by
+/// `_negInf` — except [_codecEos], which is always a legal pick (the talker
+/// must be able to end the utterance). Ports
+/// `qwen3_tts_pipeline.py:223-225` verbatim:
+/// ```python
+/// suppress = np.zeros(_CODEC_VOCAB, np.float32)
+/// suppress[2048:] = _NEG_INF
+/// suppress[_CODEC_EOS] = 0.0
+/// ```
+Float32List buildSuppress() {
+  final suppress = Float32List(_codecVocab);
+  for (var i = 2048; i < _codecVocab; i++) {
+    suppress[i] = _negInf;
+  }
+  suppress[_codecEos] = 0.0;
+  return suppress;
+}
+
+/// Applies the talker's per-step cb0 scoring edits to [scores] **in
+/// place** (matches the recipe, which reassigns entries of the `scores`
+/// array directly rather than returning a new one — callers must pass an
+/// array that is safe to mutate, e.g. a fresh copy of the raw logits, since
+/// the original logits are still needed elsewhere in the decode loop).
+///
+/// Ports `qwen3_tts_pipeline.py:231-237` verbatim:
+/// ```python
+/// scores = logits + suppress
+/// if len(frames) < 2:  # min_new_tokens=2
+///     scores[_CODEC_EOS] = _NEG_INF
+/// for token in history:
+///     scores[token] = (scores[token] / repetition_penalty
+///                      if scores[token] > 0
+///                      else scores[token] * repetition_penalty)
+/// ```
+/// [minNewTokensGuard] is the caller-evaluated `len(frames) < 2` condition
+/// (frame-count bookkeeping lives in the decode loop, a later task — this
+/// function only applies the resulting edit).
+void applyCb0Scoring(
+  Float32List scores, {
+  required Float32List suppress,
+  required Set<int> history,
+  required double repetitionPenalty,
+  required bool minNewTokensGuard,
+}) {
+  for (var i = 0; i < scores.length; i++) {
+    scores[i] += suppress[i];
+  }
+  if (minNewTokensGuard) {
+    scores[_codecEos] = _negInf;
+  }
+  for (final token in history) {
+    final s = scores[token];
+    scores[token] = s > 0 ? s / repetitionPenalty : s * repetitionPenalty;
+  }
+}
+
+/// Deterministic, RNG-free pick: the argmax index of [logits].
+///
+/// This is the golden-decode path (`do_sample=False` in the recipe):
+/// `return int(np.argmax(logits))` (`qwen3_tts_pipeline.py:482`). Matches
+/// numpy's `argmax` tie-break — the **first** (lowest-index) maximum wins.
+int pickGreedy(Float32List logits) {
+  if (logits.isEmpty) {
+    throw ArgumentError.value(
+      logits.length,
+      'logits.length',
+      'pickGreedy: logits must not be empty',
+    );
+  }
+  var bestIndex = 0;
+  var bestValue = logits[0];
+  for (var i = 1; i < logits.length; i++) {
+    if (logits[i] > bestValue) {
+      bestValue = logits[i];
+      bestIndex = i;
+    }
+  }
+  return bestIndex;
+}
+
+/// Top-k / temperature sampling pick (production quality — not the golden
+/// gate, which uses [pickGreedy]).
+///
+/// Ports `qwen3_tts_pipeline.py:483-490`'s sampling branch:
+/// ```python
+/// scaled = logits.astype(np.float64) / max(temperature, 1e-6)
+/// if top_k and top_k < len(scaled):
+///     kth = np.partition(scaled, -top_k)[-top_k]
+///     scaled = np.where(scaled < kth, -np.inf, scaled)
+/// scaled -= scaled.max()
+/// probs = np.exp(scaled)
+/// probs /= probs.sum()
+/// return int(rng.choice(len(probs), p=probs))
+/// ```
+/// Computed in `double` precision throughout (matching the recipe's
+/// `.astype(np.float64)`), returning an `int`. The final draw is a plain
+/// cumulative-sum inverse-CDF sample from [rng] (a `dart:math.Random`) —
+/// this does not attempt to bit-reproduce numpy `Generator.choice`'s
+/// internal algorithm; determinism is only required (and tested) against a
+/// seeded Dart [Random].
+int pickSampled(
+  Float32List logits, {
+  required int topK,
+  required double temperature,
+  required Random rng,
+}) {
+  if (logits.isEmpty) {
+    throw ArgumentError.value(
+      logits.length,
+      'logits.length',
+      'pickSampled: logits must not be empty',
+    );
+  }
+  final n = logits.length;
+  final denom = max(temperature, 1e-6);
+  final scaled = List<double>.generate(n, (i) => logits[i] / denom);
+
+  if (topK > 0 && topK < n) {
+    // np.partition(scaled, -top_k)[-top_k]: the value that would land at
+    // index `n - top_k` in a fully sorted-ascending array, i.e. the
+    // top_k-th largest value — the keep/suppress threshold. Ties at the
+    // threshold are all kept (matches `scaled < kth`, not a rank cutoff),
+    // so more than top_k entries may survive when the threshold value
+    // repeats.
+    final sortedDesc = List<double>.of(scaled)..sort((a, b) => b.compareTo(a));
+    final kth = sortedDesc[topK - 1];
+    for (var i = 0; i < n; i++) {
+      if (scaled[i] < kth) scaled[i] = double.negativeInfinity;
+    }
+  }
+
+  var maxVal = scaled[0];
+  for (var i = 1; i < n; i++) {
+    if (scaled[i] > maxVal) maxVal = scaled[i];
+  }
+  var sum = 0.0;
+  final probs = List<double>.generate(n, (i) {
+    final p = exp(scaled[i] - maxVal);
+    sum += p;
+    return p;
+  });
+  for (var i = 0; i < n; i++) {
+    probs[i] /= sum;
+  }
+
+  // Cumulative-sum inverse-CDF sample.
+  final u = rng.nextDouble();
+  var cumulative = 0.0;
+  for (var i = 0; i < n; i++) {
+    cumulative += probs[i];
+    if (u < cumulative) return i;
+  }
+  return n - 1; // Guards float round-off so the draw never falls through.
+}
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart
new file mode 100644
index 00000000..48dd325f
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart
@@ -0,0 +1,292 @@
+// Tests for the Qwen3-TTS talker sampler + cb0 scoring
+// (`lib/src/qwen3/qwen3_sampler.dart`).
+//
+// Pure unit tests — no model tables, no artifacts, no `@Tags` skip-guard.
+// Every input is a small hand-constructed vector so the expected output can
+// be hand-checked against the recipe's arithmetic
+// (`text_to_speech_lm/python/qwen3_tts_pipeline.py:223-225, 231-237,
+// 467-490`).
+
+import 'dart:math';
+import 'dart:typed_data';
+
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_sampler.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+void main() {
+  group('pickGreedy', () {
+    test('returns the argmax index', () {
+      final logits = Float32List.fromList([1.0, 5.0, 3.0, -2.0]);
+      expect(pickGreedy(logits), 1);
+    });
+
+    test('ties resolve to the lowest index (matches numpy argmax)', () {
+      final logits = Float32List.fromList([2.0, 4.0, 4.0, 4.0, 0.0]);
+      expect(pickGreedy(logits), 1);
+    });
+
+    test('single-element array returns index 0', () {
+      final logits = Float32List.fromList([7.0]);
+      expect(pickGreedy(logits), 0);
+    });
+
+    test('all-negative logits still pick the argmax', () {
+      final logits = Float32List.fromList([-5.0, -1.0, -3.0]);
+      expect(pickGreedy(logits), 1);
+    });
+  });
+
+  group('buildSuppress', () {
+    test('is zero for every index < 2048', () {
+      final suppress = buildSuppress();
+      expect(suppress.length, 3072);
+      for (var i = 0; i < 2048; i++) {
+        expect(suppress[i], 0.0, reason: 'index $i');
+      }
+    });
+
+    test('is zero at the codec EOS index (2150)', () {
+      final suppress = buildSuppress();
+      expect(suppress[2150], 0.0);
+    });
+
+    test('is -1e9 for every index >= 2048 except EOS', () {
+      final suppress = buildSuppress();
+      for (var i = 2048; i < suppress.length; i++) {
+        if (i == 2150) continue;
+        expect(suppress[i], -1e9, reason: 'index $i');
+      }
+    });
+  });
+
+  group('applyCb0Scoring', () {
+    test('adds suppress element-wise into scores (no guard, no history)', () {
+      // suppress[1] uses -50.0 rather than -1e9 here so the sum is exactly
+      // representable in float32 (the -1e9 magnitude is covered by the
+      // dedicated "dominates" test below, where float32's ~64-wide step
+      // size at that magnitude legitimately rounds small additions away).
+      final scores = Float32List.fromList([1.0, 2.0, 3.0, 4.0]);
+      final suppress = Float32List.fromList([0.0, -50.0, 0.0, 10.0]);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: <int>{},
+        repetitionPenalty: 1.3,
+        minNewTokensGuard: false,
+      );
+      expect(scores[0], 1.0);
+      expect(scores[1], -48.0);
+      expect(scores[2], 3.0);
+      expect(scores[3], 14.0);
+    });
+
+    test('a real -1e9 suppress entry dominates the sum (float32 '
+        'precision — the recipe stores scores as float32)', () {
+      final scores = Float32List.fromList([2.0]);
+      final suppress = Float32List.fromList([-1e9]);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: <int>{},
+        repetitionPenalty: 1.3,
+        minNewTokensGuard: false,
+      );
+      expect(scores[0], -1e9);
+    });
+
+    test('minNewTokensGuard forces EOS (2150) to -1e9', () {
+      final scores = Float32List(3072);
+      scores[2150] = 42.0; // would otherwise survive untouched
+      final suppress = Float32List(3072); // all-zero: isolate the guard
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: <int>{},
+        repetitionPenalty: 1.3,
+        minNewTokensGuard: true,
+      );
+      expect(scores[2150], -1e9);
+    });
+
+    test('guard is a no-op when false', () {
+      final scores = Float32List(3072);
+      scores[2150] = 42.0;
+      final suppress = Float32List(3072);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: <int>{},
+        repetitionPenalty: 1.3,
+        minNewTokensGuard: false,
+      );
+      expect(scores[2150], 42.0);
+    });
+
+    test('repetition penalty: positive score divides by the penalty', () {
+      final scores = Float32List.fromList([10.0, 0.0, 0.0, 0.0]);
+      final suppress = Float32List(4);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: {0},
+        repetitionPenalty: 2.0,
+        minNewTokensGuard: false,
+      );
+      // s=10 > 0 -> 10 / 2.0 = 5.0
+      expect(scores[0], 5.0);
+    });
+
+    test('repetition penalty: non-positive score multiplies by the '
+        'penalty', () {
+      final scores = Float32List.fromList([-4.0, 0.0, 0.0, 0.0]);
+      final suppress = Float32List(4);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: {0},
+        repetitionPenalty: 2.0,
+        minNewTokensGuard: false,
+      );
+      // s=-4 is not > 0 -> -4 * 2.0 = -8.0
+      expect(scores[0], -8.0);
+    });
+
+    test('repetition penalty: exact-zero score takes the multiply branch '
+        '(s > 0 is false at s == 0)', () {
+      final scores = Float32List.fromList([0.0, 0.0, 0.0, 0.0]);
+      final suppress = Float32List(4);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: {0},
+        repetitionPenalty: 3.0,
+        minNewTokensGuard: false,
+      );
+      // s=0 is not > 0 -> 0 * 3.0 = 0.0 (same result, but exercises the
+      // multiply branch's condition rather than the divide branch's).
+      expect(scores[0], 0.0);
+    });
+
+    test('repetition penalty applies to every token in history, others '
+        'untouched', () {
+      final scores = Float32List.fromList([8.0, -6.0, 3.0, 0.0]);
+      final suppress = Float32List(4);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: {0, 1},
+        repetitionPenalty: 2.0,
+        minNewTokensGuard: false,
+      );
+      expect(scores[0], 4.0); // 8 / 2
+      expect(scores[1], -12.0); // -6 * 2
+      expect(scores[2], 3.0); // untouched (not in history)
+      expect(scores[3], 0.0); // untouched (not in history)
+    });
+
+    test('full pipeline: suppress + guard + repetition penalty compose in '
+        'the recipe order', () {
+      // scores = logits + suppress; then guard; then repetition penalty.
+      final scores = Float32List.fromList([5.0, 5.0, 5.0]); // "logits"
+      final suppress = Float32List.fromList([0.0, 0.0, -1e9]);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: {0},
+        repetitionPenalty: 5.0,
+        minNewTokensGuard: false,
+      );
+      // index 0: (5+0)=5, in history, >0 -> 5/5 = 1.0
+      expect(scores[0], 1.0);
+      // index 1: (5+0)=5, not in history -> untouched
+      expect(scores[1], 5.0);
+      // index 2: (5 + -1e9), not in history -> untouched by penalty.
+      // float32 storage rounds this sum back to exactly -1e9 (the +5 is
+      // far below the ~64-wide float32 step size at that magnitude).
+      expect(scores[2], -1e9);
+    });
+  });
+
+  group('pickSampled', () {
+    test('with topK=1 always returns the argmax regardless of rng draw', () {
+      final logits = Float32List.fromList([1.0, 9.0, 2.0, 0.0]);
+      for (final seed in [1, 2, 3, 4, 5]) {
+        final picked = pickSampled(
+          logits,
+          topK: 1,
+          temperature: 1.0,
+          rng: Random(seed),
+        );
+        expect(picked, 1);
+      }
+    });
+
+    test('stays within the top-k index set for a seeded rng', () {
+      final logits = Float32List.fromList([0.0, 10.0, 9.0, 8.0, -5.0, -6.0]);
+      const topKIndices = {1, 2, 3}; // the 3 highest logits
+      final rng = Random(42);
+      for (var i = 0; i < 50; i++) {
+        final picked = pickSampled(logits, topK: 3, temperature: 1.0, rng: rng);
+        expect(topKIndices.contains(picked), isTrue, reason: 'picked $picked');
+      }
+    });
+
+    test('is reproducible for the same seed', () {
+      final logits = Float32List.fromList([1.0, 2.0, 3.0, 4.0, 5.0]);
+      final picksA = [
+        for (var i = 0; i < 20; i++)
+          pickSampled(logits, topK: 0, temperature: 1.0, rng: Random(7)),
+      ];
+      // Random(7) is re-seeded per element above, so instead compare two
+      // independently-seeded runs draw-for-draw using a shared rng stream.
+      final rngA = Random(123);
+      final seqA = [
+        for (var i = 0; i < 20; i++)
+          pickSampled(logits, topK: 0, temperature: 1.0, rng: rngA),
+      ];
+      final rngB = Random(123);
+      final seqB = [
+        for (var i = 0; i < 20; i++)
+          pickSampled(logits, topK: 0, temperature: 1.0, rng: rngB),
+      ];
+      expect(seqA, orderedEquals(seqB));
+      // Sanity: every single-seed-per-call draw above also lands in range.
+      expect(picksA.every((p) => p >= 0 && p < logits.length), isTrue);
+    });
+
+    test('topK=0 (no cutoff) never picks the effectively-impossible tail '
+        'when logits are extremely skewed, but does not throw', () {
+      final logits = Float32List.fromList([100.0, -100.0, -100.0]);
+      final picked = pickSampled(
+        logits,
+        topK: 0,
+        temperature: 1.0,
+        rng: Random(99),
+      );
+      expect(picked, 0);
+    });
+
+    test('topK >= logits.length is treated as "no cutoff"', () {
+      final logits = Float32List.fromList([1.0, 2.0, 3.0]);
+      final picked = pickSampled(
+        logits,
+        topK: 3,
+        temperature: 1.0,
+        rng: Random(5),
+      );
+      expect(picked, inInclusiveRange(0, 2));
+    });
+
+    test('empty logits throws', () {
+      expect(
+        () => pickSampled(
+          Float32List(0),
+          topK: 0,
+          temperature: 1.0,
+          rng: Random(1),
+        ),
+        throwsArgumentError,
+      );
+    });
+  });
+}

From 9966b8bd1a9a9e913f72f3e9962392edf7574188 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 22:43:31 +0500
Subject: [PATCH 08/30] refactor(tts): extract shared LiteRT graph helpers
 (matcha byte-exact)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Move TtsCore's private _loadGraph/_runGraph/_createF32TensorBuffer into
a new litert_graph.dart as public loadLiteRtGraph/runLiteRtGraph/
createF32TensorBuffer, generalized to mixed F32/I32 inputs (GraphInput)
and a parameterized signature index, so the upcoming Qwen3 talker/codec
graphs can reuse them. Matcha call sites now wrap inputs as F32Input
and pass signature index 0 — behavior-preserving, verified byte-exact
against the shipped Matcha golden PCM on macOS before and after.
---
 .../lib/src/litert/litert_graph.dart          | 327 ++++++++++++++++++
 .../lib/src/litert/tts_core.dart              | 264 ++------------
 .../test/litert/litert_graph_test.dart        |  49 +++
 3 files changed, 414 insertions(+), 226 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
 create mode 100644 packages/flutter_gemma_speech/test/litert/litert_graph_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart b/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
new file mode 100644
index 00000000..d3c5b796
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
@@ -0,0 +1,327 @@
+// Shared LiteRT graph-loading + forward-pass helpers, factored out of
+// Matcha's `TtsCore` so the same load/run machinery can drive Qwen3's
+// talker/codec graphs too. This is a pure, behavior-preserving extraction:
+// `TtsCore` now delegates to [loadLiteRtGraph]/[runLiteRtGraph] instead of
+// its own former private `_loadGraph`/`_runGraph` — the tensor-buffer
+// create -> run -> lock(Read) -> copy-through-locked-ptr -> unlock ->
+// destroy sequence and the partial-failure cleanup are unchanged, only
+// renamed and moved. See `tts_core.dart`'s file header for the original
+// provenance (a verbatim port of `matcha_synth.dart`'s `runGraph`, FFI-styled
+// after `stt_core.dart`).
+//
+// Generalization over the Matcha-only original: Qwen3's talker `decode`
+// signature mixes 58 F32 inputs with 1 I32 input (`input_pos`), and the
+// codec graph's input is I32 token ids — so a F32-only `_runGraph` can't be
+// reused verbatim. [GraphInput] tags each input with its dtype so
+// [runLiteRtGraph] creates the right kind of tensor buffer per input;
+// outputs stay F32-only (Qwen3's KV/logits/codec-PCM outputs and Matcha's
+// mel/PCM outputs are all f32). The hardcoded signature index `0` is now a
+// parameter ([runLiteRtGraph]'s `signatureIndex`) — Matcha call sites keep
+// passing `0`.
+
+import 'dart:ffi';
+import 'dart:typed_data';
+
+import 'package:ffi/ffi.dart';
+// Public, native-only bindings library (not the package barrel) — see the
+// equivalent comment in `tts_core.dart`/`stt_core.dart` for why this import
+// (not the `if (dart.library.ffi)` barrel) is correct in a native-only file.
+import 'package:flutter_gemma_litertlm/litert_bindings.dart';
+
+/// One compiled graph's handles (model/options/compiledModel), freed
+/// together by the owner's dispose or by [loadLiteRtGraph]'s caller's
+/// partial-failure cleanup. Was `TtsCore`'s private `_LoadedGraph`.
+class LoadedGraph {
+  LoadedGraph(this.model, this.options, this.compiledModel);
+  final LiteRtModel model;
+  final LiteRtOptions options;
+  final LiteRtCompiledModel compiledModel;
+}
+
+/// Loads + compiles one `.tflite` graph at [path], mirroring the
+/// model/options/compiled sequence `SttCore.load` runs for its single model
+/// — generalized so callers (e.g. `TtsCore.load`, the upcoming Qwen3 loader)
+/// can call it once per graph. On any failure partway through, frees
+/// whatever handles it already created for THIS graph before rethrowing;
+/// the caller is responsible for freeing any earlier, already-succeeded
+/// graphs + the shared environment. Was `TtsCore`'s private `_loadGraph`.
+LoadedGraph loadLiteRtGraph(
+  LiteRtBindings bindings,
+  LiteRtEnvironment environment,
+  String path,
+  int accelerator,
+) {
+  LiteRtModel? model;
+  LiteRtOptions? options;
+  LiteRtCompiledModel? compiled;
+  try {
+    final pathC = path.toNativeUtf8();
+    final modelPtr = calloc<LiteRtModel>();
+    try {
+      bindings
+          .createModelFromFile(environment, pathC, modelPtr)
+          .check('LiteRtCreateModelFromFile($path)');
+    } finally {
+      calloc.free(pathC);
+    }
+    model = modelPtr.value;
+    calloc.free(modelPtr);
+
+    final optsPtr = calloc<LiteRtOptions>();
+    bindings.createOptions(optsPtr).check('LiteRtCreateOptions($path)');
+    options = optsPtr.value;
+    calloc.free(optsPtr);
+    bindings
+        .setOptionsHardwareAccelerators(options, accelerator)
+        .check('LiteRtSetOptionsHardwareAccelerators($path)');
+
+    final compiledPtr = calloc<LiteRtCompiledModel>();
+    bindings
+        .createCompiledModel(environment, model, options, compiledPtr)
+        .check('LiteRtCreateCompiledModel($path)');
+    compiled = compiledPtr.value;
+    calloc.free(compiledPtr);
+
+    return LoadedGraph(model, options, compiled);
+  } catch (_) {
+    if (compiled != null) bindings.destroyCompiledModel(compiled);
+    if (options != null) bindings.destroyOptions(options);
+    if (model != null) bindings.destroyModel(model);
+    rethrow;
+  }
+}
+
+/// One tensor buffer's raw host allocation + its LiteRT wrapper handle,
+/// freed together in [runLiteRtGraph]'s `finally`. Mirrors
+/// `matcha_synth.dart`'s `_TensorHandle`. Was `TtsCore`'s private
+/// `_TensorHandle`.
+class TensorHandle {
+  TensorHandle(this.raw, this.buffer);
+  final Pointer<Uint8> raw;
+  final LiteRtTensorBuffer buffer;
+}
+
+/// Tagged graph input: pairs a shape with its dtype-specific payload so
+/// [runLiteRtGraph] can create the right kind of tensor buffer per input.
+/// Matcha's graphs are F32-only ([F32Input] everywhere); Qwen3's talker
+/// `decode` signature mixes 58 F32 inputs with 1 I32 input (`input_pos`),
+/// and the codec graph's input is I32 token ids.
+sealed class GraphInput {
+  List<int> get shape;
+}
+
+class F32Input extends GraphInput {
+  F32Input(this.shape, this.data);
+  @override
+  final List<int> shape;
+  final Float32List data;
+}
+
+class I32Input extends GraphInput {
+  I32Input(this.shape, this.data);
+  @override
+  final List<int> shape;
+  final Int32List data;
+}
+
+/// Generic multi-input/multi-output forward pass over one compiled [graph]
+/// at [signatureIndex]. Mirrors `SttCore._encode`/`_decodeLoop`'s tensor-
+/// buffer create -> run -> lock(Read) -> copy-through-locked-ptr -> unlock
+/// -> destroy sequence, generalized to N inputs / M outputs and to mixed
+/// F32/I32 input dtypes via [GraphInput] — this replaces `TtsCore`'s former
+/// private `_runGraph` (F32-only, signature index hardcoded to 0). [inputs]
+/// and [outputShapes] must list tensors in the model's declared
+/// [signatureIndex] argument order. Outputs are always read back as F32.
+List<Float32List> runLiteRtGraph(
+  LiteRtBindings bindings,
+  LiteRtCompiledModel graph,
+  int signatureIndex,
+  List<GraphInput> inputs,
+  List<List<int>> outputShapes,
+) {
+  final inHandles = <TensorHandle>[];
+  final outHandles = <TensorHandle>[];
+  try {
+    for (final input in inputs) {
+      inHandles.add(switch (input) {
+        F32Input(:final shape, :final data) => _createTensorBuffer(
+          bindings,
+          shape,
+          kLiteRtElementTypeFloat32,
+          (alloc, count) =>
+              alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data),
+        ),
+        I32Input(:final shape, :final data) => _createTensorBuffer(
+          bindings,
+          shape,
+          kLiteRtElementTypeInt32,
+          (alloc, count) =>
+              alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data),
+        ),
+      });
+    }
+    for (final shape in outputShapes) {
+      outHandles.add(
+        _createTensorBuffer(bindings, shape, kLiteRtElementTypeFloat32, null),
+      );
+    }
+
+    // Combined arrays are built fresh right before the call and freed
+    // right after, mirroring `SttCore._decodeLoop`'s 3-input decode
+    // (stt_core.dart:504-527): each buffer was created into its own
+    // single-slot pointer above; only `.value` is copied in here.
+    final inPtrs = calloc<LiteRtTensorBuffer>(inHandles.length);
+    final outPtrs = calloc<LiteRtTensorBuffer>(outHandles.length);
+    try {
+      for (var i = 0; i < inHandles.length; i++) {
+        inPtrs[i] = inHandles[i].buffer;
+      }
+      for (var i = 0; i < outHandles.length; i++) {
+        outPtrs[i] = outHandles[i].buffer;
+      }
+      bindings
+          .runCompiledModel(
+            graph,
+            signatureIndex,
+            inHandles.length,
+            inPtrs,
+            outHandles.length,
+            outPtrs,
+          )
+          .check('LiteRtRunCompiledModel(signature=$signatureIndex)');
+    } finally {
+      calloc.free(inPtrs);
+      calloc.free(outPtrs);
+    }
+
+    // Lock(Read) triggers the device->host sync on GPU/NPU; read each
+    // output THROUGH the locked pointer into an owned Float32List copy
+    // before unlocking/destroying the buffer — mirrors
+    // `SttCore._encode`'s locked-pointer copy (stt_core.dart:322-351).
+    final results = <Float32List>[];
+    for (var i = 0; i < outHandles.length; i++) {
+      final count = outputShapes[i].fold<int>(1, (a, b) => a * b);
+      final lockedPtr = calloc<Pointer<Void>>();
+      try {
+        bindings
+            .lockTensorBuffer(
+              outHandles[i].buffer,
+              lockedPtr,
+              kLiteRtTensorBufferLockModeRead,
+            )
+            .check('LiteRtLockTensorBuffer(out $i)');
+        final locked = lockedPtr.value.cast<Float>();
+        results.add(Float32List.fromList(locked.asTypedList(count)));
+        bindings
+            .unlockTensorBuffer(outHandles[i].buffer)
+            .check('LiteRtUnlockTensorBuffer(out $i)');
+      } finally {
+        calloc.free(lockedPtr);
+      }
+    }
+    return results;
+  } finally {
+    for (final h in inHandles) {
+      bindings.destroyTensorBuffer(h.buffer);
+      calloc.free(h.raw);
+    }
+    for (final h in outHandles) {
+      bindings.destroyTensorBuffer(h.buffer);
+      calloc.free(h.raw);
+    }
+  }
+}
+
+/// Creates a F32 tensor buffer of [shape], optionally seeded with [data].
+/// [env] is accepted for signature symmetry with [loadLiteRtGraph] and to
+/// leave room for a future host-buffer variant that needs the environment;
+/// `LiteRtCreateTensorBufferFromHostMemory` itself does not take one, so it
+/// is unused today. Was `TtsCore`'s private `_createF32TensorBuffer`.
+TensorHandle createF32TensorBuffer(
+  LiteRtBindings bindings,
+  LiteRtEnvironment env,
+  List<int> shape,
+  Float32List? data,
+) {
+  return _createTensorBuffer(
+    bindings,
+    shape,
+    kLiteRtElementTypeFloat32,
+    data == null
+        ? null
+        : (alloc, count) =>
+              alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data),
+  );
+}
+
+/// Creates an I32 tensor buffer of [shape], optionally seeded with [data].
+/// Same as [createF32TensorBuffer] but `elementType =
+/// kLiteRtElementTypeInt32` over an [Int32List] payload — used for the
+/// talker's `input_pos` and the codec's token-id inputs. [env] is unused
+/// today; see [createF32TensorBuffer]'s doc.
+TensorHandle createI32TensorBuffer(
+  LiteRtBindings bindings,
+  LiteRtEnvironment env,
+  List<int> shape,
+  Int32List? data,
+) {
+  return _createTensorBuffer(
+    bindings,
+    shape,
+    kLiteRtElementTypeInt32,
+    data == null
+        ? null
+        : (alloc, count) =>
+              alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data),
+  );
+}
+
+/// Shared allocate + (optionally) write + wrap-as-tensor-buffer sequence
+/// behind [createF32TensorBuffer]/[createI32TensorBuffer]/[runLiteRtGraph]'s
+/// per-input dispatch. [elementType] is one of `kLiteRtElementTypeFloat32`/
+/// `kLiteRtElementTypeInt32` (both 4-byte elements, so `bytes = count * 4`
+/// unconditionally — matches the original F32-only arithmetic byte-for-byte
+/// when [elementType] is float32). [writeData], if non-null, is called once
+/// with the fresh aligned allocation to copy the caller's payload in before
+/// the tensor buffer is created.
+TensorHandle _createTensorBuffer(
+  LiteRtBindings bindings,
+  List<int> shape,
+  int elementType,
+  void Function(AlignedAlloc alloc, int count)? writeData,
+) {
+  final count = shape.fold<int>(1, (a, b) => a * b);
+  final bytes = count * 4;
+  final type = LiteRtRankedTensorTypeView.calloc()
+    ..elementType = elementType
+    ..rank = shape.length;
+  for (var i = 0; i < shape.length; i++) {
+    type.setDimension(i, shape[i]);
+  }
+  final alloc = allocAligned(bytes);
+  writeData?.call(alloc, count);
+  final bufPtr = calloc<LiteRtTensorBuffer>();
+  // On success alloc.raw is handed off to the caller inside the returned
+  // TensorHandle — runLiteRtGraph frees it once the tensor buffer is
+  // destroyed. On ANY throw before the return it must be freed here or it
+  // leaks native heap permanently (~bytes per failed call) — mirrors
+  // SttCore._encode's `returning` flag (stt_core.dart:288).
+  var returning = false;
+  try {
+    bindings
+        .createTensorBufferFromHostMemory(
+          type.pointer,
+          alloc.aligned.cast(),
+          bytes,
+          nullptr,
+          bufPtr,
+        )
+        .check('CreateTensorBufferFromHostMemory(shape=$shape)');
+    returning = true;
+    return TensorHandle(alloc.raw, bufPtr.value);
+  } finally {
+    calloc.free(bufPtr);
+    type.free();
+    if (!returning) calloc.free(alloc.raw);
+  }
+}
diff --git a/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart b/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
index 5c6ec669..574e3c22 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
@@ -23,7 +23,10 @@
 // outputs (the multi-input pattern mirrors `SttCore._decodeLoop`'s 3-input
 // decode at stt_core.dart:504-527: each buffer is created into its own
 // single-slot pointer, then `.value` is copied into a fresh combined array
-// right before the run call).
+// right before the run call). The load/run/tensor-buffer machinery itself
+// now lives in `litert_graph.dart` (`loadLiteRtGraph`/`runLiteRtGraph`),
+// generalized to mixed F32/I32 inputs for the upcoming Qwen3 talker/codec
+// graphs; this file delegates to it and stays behavior-identical.
 //
 // Generic over [TtsModelProfile] — only `TtsPipelineKind.matchaCfm` is
 // implemented; kokoro/supertonic profiles are documented follow-ons. The
@@ -63,6 +66,7 @@ import 'package:flutter_gemma_litertlm/litert_bindings.dart';
 import '../model/tts_model_profile.dart';
 import '../tts/neural_g2p_decode.dart';
 import '../tts/tts_frontend_input.dart';
+import 'litert_graph.dart';
 
 /// The Euler CFM decoder's fixed Gaussian-noise seed. Fixed (not
 /// time-derived) so [TtsCore.synthesize] is byte-reproducible run-to-run —
@@ -135,78 +139,6 @@ String _artifactPath(Map<String, String> artifactPaths, String file) {
   return path;
 }
 
-/// One compiled Matcha graph's handles (model/options/compiledModel), freed
-/// together by [TtsCore.dispose] or by [TtsCore.load]'s partial-failure
-/// cleanup.
-class _LoadedGraph {
-  _LoadedGraph(this.model, this.options, this.compiledModel);
-  final LiteRtModel model;
-  final LiteRtOptions options;
-  final LiteRtCompiledModel compiledModel;
-}
-
-/// Loads + compiles one `.tflite` graph at [path], mirroring the
-/// model/options/compiled sequence `SttCore.load` runs for its single model
-/// — generalized so [TtsCore.load] can call it 4 times (text-encoder,
-/// decoder, vocoder, dp_g2p). On any failure partway through, frees whatever
-/// handles it already created for THIS graph before rethrowing; the caller
-/// is responsible for freeing any earlier, already-succeeded graphs + the
-/// shared environment.
-_LoadedGraph _loadGraph(
-  LiteRtBindings bindings,
-  LiteRtEnvironment environment,
-  String path,
-  int accelerator,
-) {
-  LiteRtModel? model;
-  LiteRtOptions? options;
-  LiteRtCompiledModel? compiled;
-  try {
-    final pathC = path.toNativeUtf8();
-    final modelPtr = calloc<LiteRtModel>();
-    try {
-      bindings
-          .createModelFromFile(environment, pathC, modelPtr)
-          .check('LiteRtCreateModelFromFile($path)');
-    } finally {
-      calloc.free(pathC);
-    }
-    model = modelPtr.value;
-    calloc.free(modelPtr);
-
-    final optsPtr = calloc<LiteRtOptions>();
-    bindings.createOptions(optsPtr).check('LiteRtCreateOptions($path)');
-    options = optsPtr.value;
-    calloc.free(optsPtr);
-    bindings
-        .setOptionsHardwareAccelerators(options, accelerator)
-        .check('LiteRtSetOptionsHardwareAccelerators($path)');
-
-    final compiledPtr = calloc<LiteRtCompiledModel>();
-    bindings
-        .createCompiledModel(environment, model, options, compiledPtr)
-        .check('LiteRtCreateCompiledModel($path)');
-    compiled = compiledPtr.value;
-    calloc.free(compiledPtr);
-
-    return _LoadedGraph(model, options, compiled);
-  } catch (_) {
-    if (compiled != null) bindings.destroyCompiledModel(compiled);
-    if (options != null) bindings.destroyOptions(options);
-    if (model != null) bindings.destroyModel(model);
-    rethrow;
-  }
-}
-
-/// One tensor buffer's raw host allocation + its LiteRT wrapper handle,
-/// freed together in `TtsCore._runGraph`'s `finally`. Mirrors
-/// `matcha_synth.dart`'s `_TensorHandle`.
-class _TensorHandle {
-  _TensorHandle(this.raw, this.buffer);
-  final Pointer<Uint8> raw;
-  final LiteRtTensorBuffer buffer;
-}
-
 /// Synchronous native TTS core. NOT safe to share across isolates — the FFI
 /// handles it holds are owned by the isolate that called [load].
 class TtsCore {
@@ -238,10 +170,10 @@ class TtsCore {
 
   final LiteRtBindings _bindings;
   final LiteRtEnvironment _environment;
-  final _LoadedGraph _textEncoder;
-  final _LoadedGraph _decoder;
-  final _LoadedGraph _vocoder;
-  final _LoadedGraph _dpG2p;
+  final LoadedGraph _textEncoder;
+  final LoadedGraph _decoder;
+  final LoadedGraph _vocoder;
+  final LoadedGraph _dpG2p;
 
   final int _nFeats;
   final int _nChannels;
@@ -306,7 +238,7 @@ class TtsCore {
     // LiteRT native heap is process-global and is NOT reclaimed by the
     // isolate dying. Mirrors `SttCore.load`, generalized to 4 graphs.
     LiteRtEnvironment? environment;
-    final loadedGraphs = <_LoadedGraph>[];
+    final loadedGraphs = <LoadedGraph>[];
     try {
       final envPtr = calloc<LiteRtEnvironment>();
       bindings
@@ -315,7 +247,7 @@ class TtsCore {
       environment = envPtr.value;
       calloc.free(envPtr);
 
-      final textEncoder = _loadGraph(
+      final textEncoder = loadLiteRtGraph(
         bindings,
         environment,
         _artifactPath(artifactPaths, profile.textEncoderFile),
@@ -323,7 +255,7 @@ class TtsCore {
       );
       loadedGraphs.add(textEncoder);
 
-      final decoder = _loadGraph(
+      final decoder = loadLiteRtGraph(
         bindings,
         environment,
         _artifactPath(artifactPaths, profile.decoderFile),
@@ -331,7 +263,7 @@ class TtsCore {
       );
       loadedGraphs.add(decoder);
 
-      final vocoder = _loadGraph(
+      final vocoder = loadLiteRtGraph(
         bindings,
         environment,
         _artifactPath(artifactPaths, profile.vocoderFile),
@@ -339,7 +271,7 @@ class TtsCore {
       );
       loadedGraphs.add(vocoder);
 
-      final dpG2p = _loadGraph(
+      final dpG2p = loadLiteRtGraph(
         bindings,
         environment,
         _artifactPath(artifactPaths, profile.g2pFile),
@@ -424,10 +356,12 @@ class TtsCore {
       end: _g2pEnd,
       maxT: _g2pMaxT,
     );
-    final logits = _runGraph(
+    final logits = runLiteRtGraph(
+      _bindings,
       _dpG2p.compiledModel,
+      0,
       [
-        ([1, _g2pMaxT], x),
+        F32Input([1, _g2pMaxT], x),
       ],
       [
         [1, _g2pMaxT, _g2pNPhonemes],
@@ -453,10 +387,10 @@ class TtsCore {
   /// into MAX_MEL-sized windows -> per-window N-step Euler CFM decoder ->
   /// mel denorm -> HiFi-GAN vocoder -> 16-bit PCM, concatenated across
   /// windows. Verbatim port of `matcha_synth.dart:518-635`'s math for the
-  /// single-window case; every graph run goes through [_runGraph] instead of
-  /// that script's raw-`dlopen` `runGraph`. Returns 16-bit little-endian
-  /// mono PCM with NO WAV header — the example's `pcmToWav` adds a header in
-  /// Phase 3.
+  /// single-window case; every graph run goes through [runLiteRtGraph]
+  /// instead of that script's raw-`dlopen` `runGraph`. Returns 16-bit
+  /// little-endian mono PCM with NO WAV header — the example's `pcmToWav`
+  /// adds a header in Phase 3.
   ///
   /// When the predicted duration fits one window (`rawYlen <= _maxMel`, the
   /// common case), this is byte-identical to the pre-chunking implementation
@@ -480,11 +414,13 @@ class TtsCore {
 
     // --- text encoder: symbolEmbeddings[1,maxText,nChannels] +
     //     textMask[1,1,maxText] -> mu[1,nFeats,maxText], logw[1,1,maxText] ---
-    final teOut = _runGraph(
+    final teOut = runLiteRtGraph(
+      _bindings,
       _textEncoder.compiledModel,
+      0,
       [
-        ([1, _maxText, _nChannels], input.symbolEmbeddings),
-        ([1, 1, _maxText], input.textMask),
+        F32Input([1, _maxText, _nChannels], input.symbolEmbeddings),
+        F32Input([1, 1, _maxText], input.textMask),
       ],
       [
         [1, _nFeats, _maxText],
@@ -605,13 +541,15 @@ class TtsCore {
     }
     for (var k = 0; k < _nTimesteps; k++) {
       final tEmb = tSin(k / _nTimesteps);
-      final decOut = _runGraph(
+      final decOut = runLiteRtGraph(
+        _bindings,
         _decoder.compiledModel,
+        0,
         [
-          ([1, _nFeats, _maxMel], x),
-          ([1, _nFeats, _maxMel], muY),
-          ([1, 160], tEmb),
-          ([1, 1, _maxMel], ymask),
+          F32Input([1, _nFeats, _maxMel], x),
+          F32Input([1, _nFeats, _maxMel], muY),
+          F32Input([1, 160], tEmb),
+          F32Input([1, 1, _maxMel], ymask),
         ],
         [
           [1, _nFeats, _maxMel],
@@ -632,10 +570,12 @@ class TtsCore {
     }
 
     // vocoder -> wav -> 16-bit LE PCM
-    final vocOut = _runGraph(
+    final vocOut = runLiteRtGraph(
+      _bindings,
       _vocoder.compiledModel,
+      0,
       [
-        ([1, _nFeats, _maxMel], mel),
+        F32Input([1, _nFeats, _maxMel], mel),
       ],
       [
         [1, 1, _maxMel * _hop],
@@ -693,134 +633,6 @@ class TtsCore {
     return windows;
   }
 
-  /// Generic multi-input/multi-output f32 forward pass over one compiled
-  /// [graph], signature index 0. Mirrors `SttCore._encode`/`_decodeLoop`'s
-  /// tensor-buffer create -> run -> lock(Read) -> copy-through-locked-ptr ->
-  /// unlock -> destroy sequence, generalized to N inputs / M outputs — this
-  /// replaces `matcha_synth.dart`'s raw-`dlopen` `runGraph`. [inputs] and
-  /// [outputShapes] must list tensors in the model's declared signature-0
-  /// argument order.
-  List<Float32List> _runGraph(
-    LiteRtCompiledModel graph,
-    List<(List<int> shape, Float32List data)> inputs,
-    List<List<int>> outputShapes,
-  ) {
-    final inHandles = <_TensorHandle>[];
-    final outHandles = <_TensorHandle>[];
-    try {
-      for (final (shape, data) in inputs) {
-        inHandles.add(_createF32TensorBuffer(shape, data));
-      }
-      for (final shape in outputShapes) {
-        outHandles.add(_createF32TensorBuffer(shape, null));
-      }
-
-      // Combined arrays are built fresh right before the call and freed
-      // right after, mirroring `SttCore._decodeLoop`'s 3-input decode
-      // (stt_core.dart:504-527): each buffer was created into its own
-      // single-slot pointer above; only `.value` is copied in here.
-      final inPtrs = calloc<LiteRtTensorBuffer>(inHandles.length);
-      final outPtrs = calloc<LiteRtTensorBuffer>(outHandles.length);
-      try {
-        for (var i = 0; i < inHandles.length; i++) {
-          inPtrs[i] = inHandles[i].buffer;
-        }
-        for (var i = 0; i < outHandles.length; i++) {
-          outPtrs[i] = outHandles[i].buffer;
-        }
-        _bindings
-            .runCompiledModel(
-              graph,
-              0,
-              inHandles.length,
-              inPtrs,
-              outHandles.length,
-              outPtrs,
-            )
-            .check('LiteRtRunCompiledModel(tts)');
-      } finally {
-        calloc.free(inPtrs);
-        calloc.free(outPtrs);
-      }
-
-      // Lock(Read) triggers the device->host sync on GPU/NPU; read each
-      // output THROUGH the locked pointer into an owned Float32List copy
-      // before unlocking/destroying the buffer — mirrors
-      // `SttCore._encode`'s locked-pointer copy (stt_core.dart:322-351).
-      final results = <Float32List>[];
-      for (var i = 0; i < outHandles.length; i++) {
-        final count = outputShapes[i].fold<int>(1, (a, b) => a * b);
-        final lockedPtr = calloc<Pointer<Void>>();
-        try {
-          _bindings
-              .lockTensorBuffer(
-                outHandles[i].buffer,
-                lockedPtr,
-                kLiteRtTensorBufferLockModeRead,
-              )
-              .check('LiteRtLockTensorBuffer(tts out $i)');
-          final locked = lockedPtr.value.cast<Float>();
-          results.add(Float32List.fromList(locked.asTypedList(count)));
-          _bindings
-              .unlockTensorBuffer(outHandles[i].buffer)
-              .check('LiteRtUnlockTensorBuffer(tts out $i)');
-        } finally {
-          calloc.free(lockedPtr);
-        }
-      }
-      return results;
-    } finally {
-      for (final h in inHandles) {
-        _bindings.destroyTensorBuffer(h.buffer);
-        calloc.free(h.raw);
-      }
-      for (final h in outHandles) {
-        _bindings.destroyTensorBuffer(h.buffer);
-        calloc.free(h.raw);
-      }
-    }
-  }
-
-  _TensorHandle _createF32TensorBuffer(List<int> shape, Float32List? data) {
-    final count = shape.fold<int>(1, (a, b) => a * b);
-    final bytes = count * 4;
-    final type = LiteRtRankedTensorTypeView.calloc()
-      ..elementType = kLiteRtElementTypeFloat32
-      ..rank = shape.length;
-    for (var i = 0; i < shape.length; i++) {
-      type.setDimension(i, shape[i]);
-    }
-    final alloc = allocAligned(bytes);
-    if (data != null) {
-      final view = alloc.aligned.cast<Float>().asTypedList(count);
-      view.setAll(0, data);
-    }
-    final bufPtr = calloc<LiteRtTensorBuffer>();
-    // On success alloc.raw is handed off to the caller inside the returned
-    // _TensorHandle — _runGraph frees it once the tensor buffer is destroyed
-    // (tts_core.dart:556-563). On ANY throw before the return it must be
-    // freed here or it leaks native heap permanently (~bytes per failed
-    // call) — mirrors SttCore._encode's `returning` flag (stt_core.dart:288).
-    var returning = false;
-    try {
-      _bindings
-          .createTensorBufferFromHostMemory(
-            type.pointer,
-            alloc.aligned.cast(),
-            bytes,
-            nullptr,
-            bufPtr,
-          )
-          .check('CreateTensorBufferFromHostMemory(shape=$shape)');
-      returning = true;
-      return _TensorHandle(alloc.raw, bufPtr.value);
-    } finally {
-      calloc.free(bufPtr);
-      type.free();
-      if (!returning) calloc.free(alloc.raw);
-    }
-  }
-
   /// Destroys all 4 compiled graphs' handles + the shared environment.
   /// Mirrors `SttCore.dispose`, x4.
   void dispose() {
diff --git a/packages/flutter_gemma_speech/test/litert/litert_graph_test.dart b/packages/flutter_gemma_speech/test/litert/litert_graph_test.dart
new file mode 100644
index 00000000..188e5817
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/litert/litert_graph_test.dart
@@ -0,0 +1,49 @@
+// Pure-Dart coverage of litert_graph.dart's [GraphInput] tagged-union type
+// contract: no native FFI call is made anywhere in this file (no
+// LiteRtBindings.open(), no loadLiteRtGraph/runLiteRtGraph/
+// createF32TensorBuffer/createI32TensorBuffer call) — mirrors
+// tts_core_test.dart's "no native in unit tests" constraint. This pins the
+// public shape both Matcha (all-F32) and the upcoming Qwen3 talker/codec
+// graphs (mixed F32/I32) depend on: each variant carries its own typed
+// payload but exposes a common `shape` via the sealed base class.
+
+import 'dart:typed_data';
+
+import 'package:flutter_gemma_speech/src/litert/litert_graph.dart'
+    show F32Input, GraphInput, I32Input;
+import 'package:flutter_test/flutter_test.dart';
+
+void main() {
+  group('GraphInput', () {
+    test('F32Input exposes its shape through the GraphInput base type', () {
+      final data = Float32List.fromList([1.0, 2.0, 3.0]);
+      final GraphInput input = F32Input([1, 3], data);
+      expect(input.shape, [1, 3]);
+      expect(input, isA<F32Input>());
+      expect((input as F32Input).data, same(data));
+    });
+
+    test('I32Input exposes its shape through the GraphInput base type', () {
+      final data = Int32List.fromList([5, 6]);
+      final GraphInput input = I32Input([1, 2], data);
+      expect(input.shape, [1, 2]);
+      expect(input, isA<I32Input>());
+      expect((input as I32Input).data, same(data));
+    });
+
+    test('a mixed-dtype input list keeps each element\'s own payload type', () {
+      // This is exactly the shape the Qwen3 talker `decode` signature needs:
+      // 58 F32 inputs + 1 I32 input (`input_pos`), in one ordered list.
+      final inputs = <GraphInput>[
+        F32Input([1, 4], Float32List.fromList([0.0, 1.0, 2.0, 3.0])),
+        I32Input([1, 1], Int32List.fromList([7])),
+      ];
+      expect(inputs[0], isA<F32Input>());
+      expect(inputs[1], isA<I32Input>());
+      expect(inputs.map((i) => i.shape), [
+        [1, 4],
+        [1, 1],
+      ]);
+    });
+  });
+}

From 0daf5ac43d7ec7661046e820f195d13aae753d1d Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 23:02:36 +0500
Subject: [PATCH 09/30] feat(qwen3): frozen talker layout + load-time shape
 assert

TalkerLayout pins the C1-spike-resolved talker graph layout (3 signatures
by embeddings time-dim, 59-in/57-or-56-out) and assertLayout re-verifies
what the bound LiteRT C API allows via getInputTensorLayout. First real
load of the talker graph (talker_int4.tflite) through our Dart FFI.
---
 .../lib/src/qwen3/qwen3_talker_layout.dart    | 294 ++++++++++++++++++
 .../test/qwen3/qwen3_talker_layout_test.dart  | 154 +++++++++
 2 files changed, 448 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_talker_layout_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
new file mode 100644
index 00000000..d646d9cf
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
@@ -0,0 +1,294 @@
+// Frozen layout constants for the Qwen3-TTS talker graph
+// (`talker_int4.tflite` / `talker_fp32.tflite`), pinned by a spike ("C1",
+// 2026-08-03) that introspected the REAL graph out-of-band (independent of
+// this package's Dart FFI bindings) before any Dart code existed to load
+// it — see `docs/superpowers/plans/2026-08-03-qwen3-tts.md`'s "C1 de-risk"
+// section. This file's job is narrow: (1) name the frozen numbers so the
+// rest of the Qwen3 port (Tasks 2.2/2.3+) references `TalkerLayout.xxx`
+// instead of magic numbers, and (2) a load-time [TalkerLayout.assertLayout]
+// that re-verifies as much of the C1 spike's findings as the EXISTING bound
+// LiteRT C API surface allows, so a future model revision that reorders the
+// graph fails loud at load time instead of silently corrupting the decode
+// loop weeks later.
+//
+// Talker signatures, in index order (there is no signature-NAME binding —
+// signatures are told apart purely by the `embeddings` input's time-dim: 1
+// for decode, 32 for prefill_32, 128 for prefill_128):
+//   [0] prefill_32   — bulk-encodes a 32-token prompt chunk
+//   [1] prefill_128  — bulk-encodes a 128-token prompt chunk
+//   [2] decode       — one autoregressive step
+//
+// `decode` (59 inputs -> 57 outputs):
+//   in[0]      embeddings   f32 [1, 1, 1024]
+//   in[1]      input_pos    i32 [1]
+//   in[2]      mask         f32 [1, 1, 1, cacheLen]
+//   in[3..58]               kv_cache_{k,v}_{0..27}  f32 (56 tensors,
+//                           positional)
+//   out[0..55]              kv_cache_{k,v}_{0..27}  f32 — SAME order as the
+//                           KV inputs above (verified by the spike) —
+//                           thread by copying out[i] -> next step's
+//                           in[3+i], no name lookup needed.
+//   out[56]                 logits  f32 [1, 1, 4096] = [:3072] codebook-0
+//                           logits (logitsCodec) concat [3072:] a
+//                           1024-wide hidden tail (logitsHidden), consumed
+//                           by the MTP graph.
+//
+// `prefill_32` / `prefill_128` (59 inputs -> 56 outputs): identical input
+// layout except `embeddings`/`input_pos`/`mask`'s time-dim is 32/128
+// instead of 1; outputs are the 56 KV tensors only (no `logits` — the
+// talker only emits next-token logits at `decode` time).
+//
+// What [TalkerLayout.assertLayout] CAN check, using the existing, already-
+// bound `LiteRtGetCompiledModelInputTensorLayout` (`getInputTensorLayout`)
+// — an index-based accessor, safe to call at any index this file already
+// knows (from the spike) to be valid: the `embeddings` shape (which IS the
+// signature-identifying dimension) and the `input_pos`/`mask` shapes
+// (including `mask`'s `cacheLen` last dim), for all 3 signatures; plus
+// that the 59th positional input (index 58, the last KV tensor) is
+// reachable for every signature — the closest re-verification of
+// `numTalkerInputs == 59` this per-index accessor allows.
+//
+// What it CANNOT check with the CURRENTLY bound API, and therefore treats
+// as trusted, frozen constants instead (the plan's explicit ruling: do NOT
+// add a new native binding, and do NOT probe an out-of-range index to
+// "discover" a count, to work around this): [numLayers], [numKvTensors],
+// the exact output COUNTS (57 for decode / 56 for prefill_32/prefill_128),
+// the individual per-tensor shape of each of the 56 KV tensors, and the KV
+// input-order == KV output-order identity. `LiteRtGetCompiledModelOutput
+// TensorLayouts` (`getOutputTensorLayouts`) is a BULK accessor (fills
+// `num_layouts` entries starting at output 0 — there is no per-index
+// accessor that can target e.g. output 56 alone without already knowing
+// the count), and there is no dedicated get-input-count / get-output-count
+// / get-signature-count binding at all. If a future model revision changes
+// any of these, the run path (Tasks 2.2/2.3) fails loud — a tensor-buffer
+// create/run call against a mismatched shape returns a non-OK LiteRT
+// status, which the `.check()` extension turns into a thrown
+// [StateError] — rather than silently misbehaving.
+import 'package:flutter_gemma_litertlm/litert_bindings.dart';
+
+/// Frozen graph layout for the Qwen3-TTS talker (see file header). Every
+/// field is `static const` — nothing here is discovered at runtime;
+/// [assertLayout] re-verifies what it can against a loaded talker graph and
+/// throws [StateError] on any mismatch.
+class TalkerLayout {
+  TalkerLayout._(); // Not instantiable — a namespace for static members.
+
+  /// Signature index for the 32-token bulk-prefill chunk.
+  static const int prefill32Sig = 0;
+
+  /// Signature index for the 128-token bulk-prefill chunk.
+  static const int prefill128Sig = 1;
+
+  /// Signature index for one autoregressive decode step.
+  static const int decodeSig = 2;
+
+  /// KV cache capacity — the last dim of every `mask` input, across all 3
+  /// signatures. Re-verified by [assertLayout] for every signature.
+  static const int cacheLen = 1024;
+
+  /// Transformer depth. NOT independently re-verified by [assertLayout]
+  /// (see file header) — a frozen constant from the C1 spike.
+  static const int numLayers = 28;
+
+  /// `numLayers * 2` (one k + one v tensor per layer) — the number of KV
+  /// tensors threaded positionally between decode steps. NOT independently
+  /// re-verified by [assertLayout] — a frozen constant from the C1 spike.
+  static const int numKvTensors = 56;
+
+  /// Talker hidden size — width of `embeddings`/the logits hidden tail (and
+  /// each KV tensor's last dim, per the spike; the KV tensor shape itself
+  /// is not independently re-verified). Re-verified by [assertLayout] via
+  /// the `embeddings` input's shape.
+  static const int embeddingDim = 1024;
+
+  /// Width of the `decode` signature's `logits` output's leading slice —
+  /// codebook-0 logits. NOT independently re-verified (see file header:
+  /// output shapes are unreachable via a per-index accessor).
+  static const int logitsCodec = 3072;
+
+  /// Width of `logits`' trailing slice — the hidden-state tail consumed by
+  /// the MTP graph. NOT independently re-verified.
+  static const int logitsHidden = 1024;
+
+  /// `logitsCodec + logitsHidden` — the `decode` signature's `logits`
+  /// output's full last dim. NOT independently re-verified.
+  static const int logitsWidth = logitsCodec + logitsHidden;
+
+  /// Every talker signature's input count: `embeddings, input_pos, mask`
+  /// (3) + [numKvTensors]. [assertLayout] confirms input index
+  /// `numTalkerInputs - 1` (the last KV tensor) is reachable for every
+  /// signature — the closest re-verification the bound API allows — but
+  /// does not rule out MORE inputs existing beyond it.
+  static const int numTalkerInputs = 3 + numKvTensors;
+
+  /// `decode`'s output count: [numKvTensors] + 1 (`logits`). NOT
+  /// independently re-verified (see file header) — a frozen constant.
+  static const int numDecodeOutputs = numKvTensors + 1;
+
+  /// `prefill_32`/`prefill_128`'s output count: [numKvTensors] only (no
+  /// `logits`). NOT independently re-verified — a frozen constant.
+  static const int numPrefillOutputs = numKvTensors;
+
+  /// Validates [talker] against the frozen layout above, as far as the
+  /// bound LiteRT C API allows (see file header for exactly what is and
+  /// isn't checked). Throws [StateError] naming the mismatch on any
+  /// deviation. Call once, right after compiling the talker graph, so a
+  /// layout drift fails loud at load time instead of corrupting the decode
+  /// loop.
+  static void assertLayout(
+    LiteRtBindings bindings,
+    LiteRtCompiledModel talker,
+  ) {
+    // `embeddings` (input 0) is the signature-identifying tensor — its
+    // time-dim (dim 1) is 32 for prefill_32, 128 for prefill_128, 1 for
+    // decode. A successful call into all 3 signature indices below is also
+    // the closest re-verification of "3 signatures exist" the bound API
+    // allows (there is no signature-count binding).
+    _assertInputShape(
+      bindings,
+      talker,
+      prefill32Sig,
+      0,
+      'prefill_32.embeddings',
+      [1, 32, embeddingDim],
+    );
+    _assertInputShape(
+      bindings,
+      talker,
+      prefill128Sig,
+      0,
+      'prefill_128.embeddings',
+      [1, 128, embeddingDim],
+    );
+    _assertInputShape(bindings, talker, decodeSig, 0, 'decode.embeddings', [
+      1,
+      1,
+      embeddingDim,
+    ]);
+
+    // `input_pos` (input 1): rank-1, length == the signature's time-dim.
+    _assertInputShape(
+      bindings,
+      talker,
+      prefill32Sig,
+      1,
+      'prefill_32.input_pos',
+      [32],
+    );
+    _assertInputShape(
+      bindings,
+      talker,
+      prefill128Sig,
+      1,
+      'prefill_128.input_pos',
+      [128],
+    );
+    _assertInputShape(bindings, talker, decodeSig, 1, 'decode.input_pos', [1]);
+
+    // `mask` (input 2): [1, 1, T, cacheLen] — cacheLen (the KV cache's
+    // fixed capacity) is the load-bearing dim here; checked for every
+    // signature, not just its last dim (the brief's stated minimum), since
+    // the full shape is just as cheap to check via the same call.
+    _assertInputShape(bindings, talker, prefill32Sig, 2, 'prefill_32.mask', [
+      1,
+      1,
+      32,
+      cacheLen,
+    ]);
+    _assertInputShape(bindings, talker, prefill128Sig, 2, 'prefill_128.mask', [
+      1,
+      1,
+      128,
+      cacheLen,
+    ]);
+    _assertInputShape(bindings, talker, decodeSig, 2, 'decode.mask', [
+      1,
+      1,
+      1,
+      cacheLen,
+    ]);
+
+    // Input index `numTalkerInputs - 1` (== 58, the 59th positional input,
+    // 0-indexed) must be reachable — the closest re-verification of
+    // `numTalkerInputs == 59` the per-index `getInputTensorLayout` accessor
+    // allows WITHOUT probing an out-of-range index (deliberately not done
+    // here — see file header). Only reachability is checked, not a shape:
+    // the individual KV tensor's shape is a trusted constant, not
+    // documented by the spike.
+    final lastKvInput = numTalkerInputs - 1;
+    final probe = LiteRtLayoutView.calloc();
+    try {
+      bindings
+          .getInputTensorLayout(
+            talker,
+            prefill32Sig,
+            lastKvInput,
+            probe.pointer,
+          )
+          .check(
+            'TalkerLayout.assertLayout: prefill_32 input[$lastKvInput] '
+            '(expected the last of $numKvTensors KV tensors) unreachable — '
+            'numTalkerInputs frozen constant ($numTalkerInputs) may be '
+            'stale',
+          );
+      bindings
+          .getInputTensorLayout(talker, decodeSig, lastKvInput, probe.pointer)
+          .check(
+            'TalkerLayout.assertLayout: decode input[$lastKvInput] '
+            '(expected the last of $numKvTensors KV tensors) unreachable — '
+            'numTalkerInputs frozen constant ($numTalkerInputs) may be '
+            'stale',
+          );
+    } finally {
+      probe.free();
+    }
+  }
+
+  static void _assertInputShape(
+    LiteRtBindings bindings,
+    LiteRtCompiledModel talker,
+    int signatureIndex,
+    int inputIndex,
+    String label,
+    List<int> expectedShape,
+  ) {
+    final layout = LiteRtLayoutView.calloc();
+    try {
+      bindings
+          .getInputTensorLayout(
+            talker,
+            signatureIndex,
+            inputIndex,
+            layout.pointer,
+          )
+          .check(
+            'TalkerLayout.assertLayout: '
+            'LiteRtGetCompiledModelInputTensorLayout(sig=$signatureIndex, '
+            'in=$inputIndex, $label)',
+          );
+      if (layout.rank != expectedShape.length) {
+        throw StateError(
+          'TalkerLayout mismatch: $label (sig=$signatureIndex, '
+          'in=$inputIndex) has rank=${layout.rank}, expected '
+          'rank=${expectedShape.length} (shape=$expectedShape) — the '
+          'talker graph layout has drifted from the C1-spike-frozen '
+          'constants; update TalkerLayout, do not work around this.',
+        );
+      }
+      for (var i = 0; i < expectedShape.length; i++) {
+        final actual = layout.dimension(i);
+        if (actual != expectedShape[i]) {
+          throw StateError(
+            'TalkerLayout mismatch: $label (sig=$signatureIndex, '
+            'in=$inputIndex) dim[$i]=$actual, expected ${expectedShape[i]} '
+            '(full expected shape=$expectedShape) — the talker graph '
+            'layout has drifted from the C1-spike-frozen constants; '
+            'update TalkerLayout, do not work around this.',
+          );
+        }
+      }
+    } finally {
+      layout.free();
+    }
+  }
+}
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_layout_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_layout_test.dart
new file mode 100644
index 00000000..d09d9da9
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_layout_test.dart
@@ -0,0 +1,154 @@
+// Load-time smoke test for the Qwen3-TTS talker graph
+// (`talker_int4.tflite`) — the FIRST test in this package that actually
+// loads a real compiled `.tflite` graph through our own Dart LiteRT FFI
+// (`LiteRtBindings.open()` + `loadLiteRtGraph`) rather than exercising pure
+// Dart code, so a failure here is a genuine "our FFI can't load this graph"
+// signal, not a logic bug.
+//
+// Verifies `TalkerLayout.assertLayout` against the REAL talker graph: the
+// frozen constants pinned by the C1 spike (2026-08-03, see
+// `qwen3_talker_layout.dart`'s file header) must still match reality. The
+// talker (~256 MB int4) is NOT committed to the repo — it lives in the
+// local HuggingFace cache (see [_defaultModelDir] below) or wherever
+// `QWEN3_MODEL_DIR` points. When absent (e.g. in CI without the artifact
+// fetched) the test skips gracefully so the suite stays green; when present
+// (as it is for local device runs) it asserts the golden layout.
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:ffi';
+import 'dart:io';
+
+import 'package:ffi/ffi.dart';
+import 'package:flutter_gemma_litertlm/litert_bindings.dart';
+import 'package:flutter_gemma_speech/src/litert/litert_graph.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_talker_layout.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot dir — the local
+/// HuggingFace cache path for `litert-community/Qwen3-TTS-12Hz-0.6B-Base`.
+/// Override with the `QWEN3_MODEL_DIR` environment variable to run against
+/// a different snapshot.
+String _defaultModelDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66';
+}
+
+String _modelDir() =>
+    Platform.environment['QWEN3_MODEL_DIR'] ?? _defaultModelDir();
+
+void main() {
+  test('TalkerLayout.assertLayout passes against the real talker graph '
+      '(frozen C1 constants)', () {
+    final talkerPath = '${_modelDir()}/talker_int4.tflite';
+    if (!File(talkerPath).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS talker graph not found at $talkerPath — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final bindings = LiteRtBindings.open();
+    LiteRtEnvironment? environment;
+    LoadedGraph? talker;
+    try {
+      final envPtr = calloc<LiteRtEnvironment>();
+      bindings
+          .createEnvironment(0, nullptr, envPtr)
+          .check('LiteRtCreateEnvironment');
+      environment = envPtr.value;
+      calloc.free(envPtr);
+
+      // CPU: this test only needs the graph to load and its declared
+      // tensor layouts to be introspectable — no forward pass is run, so
+      // there is no reason to pull in a GPU/NPU delegate.
+      talker = loadLiteRtGraph(
+        bindings,
+        environment,
+        talkerPath,
+        kLiteRtHwAcceleratorCpu,
+      );
+
+      // The real assertion: the graph our Dart FFI just loaded matches
+      // every frozen constant TalkerLayout.assertLayout knows how to
+      // check (see its doc for exactly what that covers).
+      expect(
+        () => TalkerLayout.assertLayout(bindings, talker!.compiledModel),
+        returnsNormally,
+      );
+
+      // Print the raw introspected values TalkerLayout.assertLayout just
+      // confirmed, so a device run leaves a paper trail of what was
+      // actually observed on the real graph (mirrors the other Qwen3/TTS
+      // device-gate tests' diagnostic prints).
+      final embDecode = LiteRtLayoutView.calloc();
+      final embPrefill32 = LiteRtLayoutView.calloc();
+      final embPrefill128 = LiteRtLayoutView.calloc();
+      final maskDecode = LiteRtLayoutView.calloc();
+      try {
+        bindings
+            .getInputTensorLayout(
+              talker.compiledModel,
+              TalkerLayout.decodeSig,
+              0,
+              embDecode.pointer,
+            )
+            .check('decode.embeddings (diagnostic)');
+        bindings
+            .getInputTensorLayout(
+              talker.compiledModel,
+              TalkerLayout.prefill32Sig,
+              0,
+              embPrefill32.pointer,
+            )
+            .check('prefill_32.embeddings (diagnostic)');
+        bindings
+            .getInputTensorLayout(
+              talker.compiledModel,
+              TalkerLayout.prefill128Sig,
+              0,
+              embPrefill128.pointer,
+            )
+            .check('prefill_128.embeddings (diagnostic)');
+        bindings
+            .getInputTensorLayout(
+              talker.compiledModel,
+              TalkerLayout.decodeSig,
+              2,
+              maskDecode.pointer,
+            )
+            .check('decode.mask (diagnostic)');
+
+        List<int> dims(LiteRtLayoutView v) => [
+          for (var i = 0; i < v.rank; i++) v.dimension(i),
+        ];
+
+        // ignore: avoid_print
+        print(
+          'TALKER-LAYOUT-TEST<<<'
+          'decode.embeddings=${dims(embDecode)} '
+          'prefill_32.embeddings=${dims(embPrefill32)} '
+          'prefill_128.embeddings=${dims(embPrefill128)} '
+          'decode.mask=${dims(maskDecode)} '
+          'lastKvInputIndex=${TalkerLayout.numTalkerInputs - 1} reachable=true'
+          '>>>',
+        );
+      } finally {
+        embDecode.free();
+        embPrefill32.free();
+        embPrefill128.free();
+        maskDecode.free();
+      }
+    } finally {
+      if (talker != null) {
+        bindings.destroyCompiledModel(talker.compiledModel);
+        bindings.destroyOptions(talker.options);
+        bindings.destroyModel(talker.model);
+      }
+      if (environment != null) bindings.destroyEnvironment(environment);
+    }
+  });
+}

From af65539d24e694144e5c8ddbafbf860a9e46efdd Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 23:20:22 +0500
Subject: [PATCH 10/30] feat(qwen3): Qwen3TtsCore load + talker prefill

Loads the talker/mtp/codec LiteRT graphs + host tables + tokenizer,
asserts the frozen talker layout, introspects mtpCacheLen/mtpKvShape/
codecChunk, and ports _run_prefill (qwen3_tts_pipeline.py:315-328) to
initialize the talker's 56-tensor KV cache from a prompt embedding.
---
 .../lib/src/qwen3/qwen3_tts_core.dart         | 411 ++++++++++++++++++
 .../test/qwen3/qwen3_prefill_test.dart        | 146 +++++++
 2 files changed, 557 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
new file mode 100644
index 00000000..bf8a6958
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -0,0 +1,411 @@
+// Qwen3-TTS talker/MTP/codec graph loader + talker KV-cache prefill.
+//
+// `Qwen3TtsCore.load` opens the 3 LiteRT graphs that make up the Qwen3-TTS
+// pipeline (`talker_int4.tflite`, `mtp_fp32.tflite`,
+// `codec_decoder_fp32.tflite`), the host embedding tables + text-projection
+// MLP (`Qwen3Tables`), and the Qwen2 byte-level BPE text encoder
+// (`Qwen2BpeEncoder`); asserts the talker's graph layout against the frozen
+// `TalkerLayout` constants; and introspects the MTP/codec graphs' fixed-size
+// inputs (`mtpCacheLen`, `mtpKvShape`, `codecChunk`) so later tasks (the MTP
+// inner loop, the codec sliding-window decode) don't need to re-open the
+// graphs to read them. Ports the constructor of
+// `Qwen3TtsPipeline.__init__` (`text_to_speech_lm/python/
+// qwen3_tts_pipeline.py:130-171`).
+//
+// [Qwen3TtsCore.runPrefill] ports `Qwen3TtsPipeline._run_prefill`
+// (`qwen3_tts_pipeline.py:315-328`): right-pads the (<=32-row) prompt
+// embedding into the talker's fixed 32-row `prefill_32` signature, builds
+// the matching causal `mask`, runs it against an all-zero initial KV cache
+// (`qwen3_tts_pipeline.py:216-217`), and returns the 56 filled KV tensors —
+// this initializes the KV cache the decode loop (`_run_decode`, Task 2.3)
+// threads forward one step at a time. This task only asserts the returned
+// KV tensors' shapes; token correctness (matching the golden first
+// codebook-0 token) is verified once `runDecode` exists.
+//
+// FFI style + graph load/run machinery: same as `TtsCore`/`SttCore` — see
+// `litert_graph.dart`'s file header for the create -> run -> lock(Read) ->
+// copy-through-locked-ptr -> unlock -> destroy sequence this delegates to.
+// [Qwen3TtsCore.runPrefill] is not truly public API (no v1 consumer outside
+// this package calls it directly) but is deliberately not name-mangled
+// private either, so `qwen3_prefill_test.dart` — a different library — can
+// drive it directly; annotated `@visibleForTesting` to say so, mirroring
+// `TtsCore.planMelWindows`/`concatSegments`.
+
+import 'dart:ffi';
+import 'dart:math' as math;
+import 'dart:typed_data';
+
+import 'package:ffi/ffi.dart';
+import 'package:flutter_gemma/core/domain/platform_types.dart'
+    show PreferredBackend;
+import 'package:flutter_gemma/core/utils/gemma_log.dart';
+import 'package:meta/meta.dart' show visibleForTesting;
+// Public, native-only bindings library (not the package barrel) — see the
+// equivalent comment in `tts_core.dart`/`stt_core.dart` for why this import
+// (not the `if (dart.library.ffi)` barrel) is correct in a native-only file.
+import 'package:flutter_gemma_litertlm/litert_bindings.dart';
+
+import '../litert/litert_graph.dart';
+import 'qwen2_bpe_encoder.dart';
+import 'qwen3_tables.dart';
+import 'qwen3_talker_layout.dart';
+
+/// Mask fill value for "not yet attendable" KV-cache positions — matches
+/// `qwen3_tts_pipeline.py`'s module-level `_NEG_INF = -1e9` (used by both
+/// `_run_prefill` and `_run_decode`'s causal masks).
+const double qwen3NegInf = -1e9;
+
+int _acceleratorFor(PreferredBackend? backend) {
+  switch (backend) {
+    case PreferredBackend.gpu:
+      return kLiteRtHwAcceleratorGpu;
+    case PreferredBackend.npu:
+      return kLiteRtHwAcceleratorNpu;
+    case PreferredBackend.cpu:
+    case null:
+      return kLiteRtHwAcceleratorCpu;
+  }
+}
+
+String _artifactPath(Map<String, String> artifactPaths, String file) {
+  final path = artifactPaths[file];
+  if (path == null) {
+    throw StateError(
+      'Qwen3TtsCore: bundle is missing "$file" in artifactPaths',
+    );
+  }
+  return path;
+}
+
+/// Reads one input tensor's full shape via the index-based
+/// `getInputTensorLayout` accessor — the only per-tensor introspection the
+/// bound LiteRT C API offers (see `TalkerLayout`'s file header for the same
+/// caveat re: no name-based or bulk-input accessor).
+List<int> _readInputShape(
+  LiteRtBindings bindings,
+  LiteRtCompiledModel graph,
+  int signatureIndex,
+  int inputIndex,
+  String label,
+) {
+  final layout = LiteRtLayoutView.calloc();
+  try {
+    bindings
+        .getInputTensorLayout(graph, signatureIndex, inputIndex, layout.pointer)
+        .check(
+          'LiteRtGetCompiledModelInputTensorLayout($label, '
+          'sig=$signatureIndex, in=$inputIndex)',
+        );
+    return [for (var i = 0; i < layout.rank; i++) layout.dimension(i)];
+  } finally {
+    layout.free();
+  }
+}
+
+/// Synchronous native core for the Qwen3-TTS talker/MTP/codec pipeline. NOT
+/// safe to share across isolates — the FFI handles it holds are owned by the
+/// isolate that called [load]. Mirrors `TtsCore`/`SttCore`'s shape.
+class Qwen3TtsCore {
+  Qwen3TtsCore._({
+    required this._bindings,
+    required this._environment,
+    required this._talker,
+    required this._mtp,
+    required this._codec,
+    required this._tables,
+    required this._encoder,
+    required this._kvShapes,
+    required this.mtpCacheLen,
+    required this.mtpKvShape,
+    required this.codecChunk,
+  });
+
+  final LiteRtBindings _bindings;
+  final LiteRtEnvironment _environment;
+  final LoadedGraph _talker;
+  final LoadedGraph _mtp;
+  final LoadedGraph _codec;
+
+  /// Host embedding tables + text-projection MLP — used by the decode loop
+  /// (Task 2.3+) to turn codec-token / MTP-residual / text-token ids into
+  /// 1024-d talker-space embeddings. Not read by this task's [runPrefill]
+  /// (the caller supplies already-embedded prompt rows, e.g. via
+  /// `Qwen3Prompt.build`), but loaded here so a single [Qwen3TtsCore] owns
+  /// every table the full pipeline needs.
+  final Qwen3Tables _tables;
+
+  /// Qwen2 byte-level BPE text encoder — used by the decode loop / a future
+  /// frontend to turn raw text into token ids ahead of `Qwen3Prompt.build`.
+  /// Same "loaded here, consumed later" rationale as [_tables].
+  // ignore: unused_field
+  final Qwen2BpeEncoder _encoder;
+
+  /// Each of the talker's 56 KV tensor shapes (`kv_cache_{k,v}_{0..27}`,
+  /// positional), read once at load time from the `decode` signature's
+  /// inputs 3..58 — identical across all 3 talker signatures (see
+  /// `TalkerLayout`'s file header).
+  final List<List<int>> _kvShapes;
+
+  /// MTP graph's KV-cache capacity — the last dim of its `args_2` (mask)
+  /// input. Expected 17 (16 MTP steps + 1), per the C1 spike.
+  final int mtpCacheLen;
+
+  /// MTP graph's `args_3` (k-cache) input shape, read once at load time.
+  final List<int> mtpKvShape;
+
+  /// Codec-decoder graph's `args_0` input's last dim — its fixed
+  /// frame-chunk width.
+  final int codecChunk;
+
+  bool _disposed = false;
+
+  /// Output sample rate (Hz) — fixed for this model family.
+  int get sampleRate => 24000;
+
+  /// Opens `LiteRtBindings`, compiles the talker/MTP/codec graphs (see this
+  /// file's header), asserts the talker's layout against the frozen
+  /// [TalkerLayout] constants, reads the talker's 56 KV tensor shapes,
+  /// introspects [mtpCacheLen]/[mtpKvShape]/[codecChunk], and loads the host
+  /// tables + text encoder. Heavy — call once, from a background isolate.
+  /// [artifactPaths] is filename -> on-disk-path for the model bundle
+  /// (talker_int4.tflite, mtp_fp32.tflite, codec_decoder_fp32.tflite,
+  /// tokenizer.json, and the 4 `Qwen3Tables` members).
+  static Future<Qwen3TtsCore> load({
+    required Map<String, String> artifactPaths,
+    PreferredBackend? backend,
+  }) async {
+    final bindings = LiteRtBindings.open();
+    final accelerator = _acceleratorFor(backend);
+
+    // Track handles as they're created so a failure partway through (e.g.
+    // the codec graph fails to compile after the talker/MTP already
+    // loaded) frees everything already allocated instead of leaking it —
+    // the LiteRT native heap is process-global and is NOT reclaimed by the
+    // isolate dying. Mirrors `TtsCore.load`, generalized to 3 graphs + the
+    // tables' open file handle.
+    LiteRtEnvironment? environment;
+    final loadedGraphs = <LoadedGraph>[];
+    Qwen3Tables? tables;
+    try {
+      final envPtr = calloc<LiteRtEnvironment>();
+      bindings
+          .createEnvironment(0, nullptr, envPtr)
+          .check('LiteRtCreateEnvironment');
+      environment = envPtr.value;
+      calloc.free(envPtr);
+
+      final talker = loadLiteRtGraph(
+        bindings,
+        environment,
+        _artifactPath(artifactPaths, 'talker_int4.tflite'),
+        accelerator,
+      );
+      loadedGraphs.add(talker);
+
+      final mtp = loadLiteRtGraph(
+        bindings,
+        environment,
+        _artifactPath(artifactPaths, 'mtp_fp32.tflite'),
+        accelerator,
+      );
+      loadedGraphs.add(mtp);
+
+      final codec = loadLiteRtGraph(
+        bindings,
+        environment,
+        _artifactPath(artifactPaths, 'codec_decoder_fp32.tflite'),
+        accelerator,
+      );
+      loadedGraphs.add(codec);
+
+      // Fails loud at load time if a future model revision has drifted from
+      // the C1-spike-frozen talker layout (see `TalkerLayout`'s file
+      // header) — do this before trusting any KV-shape introspection below.
+      TalkerLayout.assertLayout(bindings, talker.compiledModel);
+
+      // KV tensor shapes are identical across all 3 talker signatures (per
+      // TalkerLayout's file header) — read once from `decode`, inputs
+      // 3..58 (`kv_cache_{k,v}_{0..27}`, positional).
+      final kvShapes = [
+        for (var i = 0; i < TalkerLayout.numKvTensors; i++)
+          _readInputShape(
+            bindings,
+            talker.compiledModel,
+            TalkerLayout.decodeSig,
+            3 + i,
+            'talker.kv_cache[$i]',
+          ),
+      ];
+
+      // MTP/codec are each single-signature graphs (signature index 0);
+      // their inputs are positional `args_N` == input index N (recipe
+      // `:162-171`).
+      final mtpMaskShape = _readInputShape(
+        bindings,
+        mtp.compiledModel,
+        0,
+        2,
+        'mtp.args_2 (mask)',
+      );
+      final mtpCacheLen = mtpMaskShape.last;
+      final mtpKvShape = _readInputShape(
+        bindings,
+        mtp.compiledModel,
+        0,
+        3,
+        'mtp.args_3 (k-cache)',
+      );
+      final codecInShape = _readInputShape(
+        bindings,
+        codec.compiledModel,
+        0,
+        0,
+        'codec.args_0',
+      );
+      final codecChunk = codecInShape.last;
+
+      tables = await Qwen3Tables.load(
+        codecEmbPath: _artifactPath(artifactPaths, 'codec_embedding_fp32.npy'),
+        mtpEmbPath: _artifactPath(artifactPaths, 'mtp_embeddings_fp16.npy'),
+        textEmbPath: _artifactPath(artifactPaths, 'text_embedding_fp16.npy'),
+        projectionNpzPath: _artifactPath(
+          artifactPaths,
+          'text_projection_fp32.npz',
+        ),
+      );
+
+      final encoder = await Qwen2BpeEncoder.fromTokenizerJson(
+        _artifactPath(artifactPaths, 'tokenizer.json'),
+      );
+
+      gemmaLog(
+        '[Qwen3TtsCore] loaded: backend=$backend, 3 graphs compiled, '
+        'mtpCacheLen=$mtpCacheLen, mtpKvShape=$mtpKvShape, '
+        'codecChunk=$codecChunk',
+      );
+
+      return Qwen3TtsCore._(
+        bindings: bindings,
+        environment: environment,
+        talker: talker,
+        mtp: mtp,
+        codec: codec,
+        tables: tables,
+        encoder: encoder,
+        kvShapes: kvShapes,
+        mtpCacheLen: mtpCacheLen,
+        mtpKvShape: mtpKvShape,
+        codecChunk: codecChunk,
+      );
+    } catch (_) {
+      tables?.dispose();
+      for (final graph in loadedGraphs) {
+        bindings.destroyCompiledModel(graph.compiledModel);
+        bindings.destroyOptions(graph.options);
+        bindings.destroyModel(graph.model);
+      }
+      if (environment != null) bindings.destroyEnvironment(environment);
+      rethrow;
+    }
+  }
+
+  /// All-zero initial KV cache — 56 tensors sized to [_kvShapes]. Port of
+  /// `qwen3_tts_pipeline.py:216-217`'s
+  /// `kv = {n: np.zeros(shape, np.float32) for n in kv_names}`.
+  List<Float32List> _zeroKv() => [
+    for (final shape in _kvShapes)
+      Float32List(shape.fold<int>(1, (a, b) => a * b)),
+  ];
+
+  /// Prefills the talker's KV cache from the (<=32-row) prompt embedding
+  /// [prefillEmb] (flat `[promptLen * 1024]`, row-major — e.g.
+  /// `Qwen3Prompt.build`'s `prefill`). Port of
+  /// `Qwen3TtsPipeline._run_prefill` (`qwen3_tts_pipeline.py:315-328`):
+  /// right-pads into the fixed 32-row `prefill_32` signature, builds the
+  /// matching causal `mask`, runs against an all-zero initial KV cache
+  /// ([_zeroKv]), and returns the 56 filled KV tensors — the new KV state a
+  /// caller threads into the first decode step (`runDecode`, Task 2.3).
+  ///
+  /// Not true public API (no v1 consumer outside this package calls it
+  /// directly) — exposed (not underscore-private) so
+  /// `qwen3_prefill_test.dart` can drive it, and annotated
+  /// [visibleForTesting] to say so, mirroring `TtsCore.planMelWindows`.
+  @visibleForTesting
+  List<Float32List> runPrefill(Float32List prefillEmb, int promptLen) {
+    if (_disposed) {
+      throw StateError('Qwen3TtsCore is disposed');
+    }
+    if (promptLen < 0 || promptLen > 32) {
+      throw ArgumentError.value(
+        promptLen,
+        'promptLen',
+        "Qwen3TtsCore.runPrefill: prompt too long for the talker's "
+            'prefill_32 signature (must be 0..32)',
+      );
+    }
+    if (prefillEmb.length != promptLen * TalkerLayout.embeddingDim) {
+      throw ArgumentError.value(
+        prefillEmb.length,
+        'prefillEmb.length',
+        'Qwen3TtsCore.runPrefill: expected '
+            '${promptLen * TalkerLayout.embeddingDim} '
+            '(promptLen * ${TalkerLayout.embeddingDim})',
+      );
+    }
+
+    // buf[1,32,1024]: right-padded prompt (qwen3_tts_pipeline.py:320-321).
+    final buf = Float32List(32 * TalkerLayout.embeddingDim);
+    buf.setRange(0, prefillEmb.length, prefillEmb);
+
+    // input_pos = arange(32) (qwen3_tts_pipeline.py:326).
+    final inputPos = Int32List.fromList([for (var i = 0; i < 32; i++) i]);
+
+    // mask[1,1,32,cacheLen]: causal, `mask[0,0,i,:min(i,p-1)+1] = 0.0` else
+    // qwen3NegInf (qwen3_tts_pipeline.py:322-324). Flattened row-major —
+    // row i occupies mask[i*cacheLen .. (i+1)*cacheLen).
+    final cacheLen = TalkerLayout.cacheLen;
+    final mask = Float32List(32 * cacheLen);
+    for (var i = 0; i < 32; i++) {
+      final lastValid = math.min(i, promptLen - 1);
+      final rowBase = i * cacheLen;
+      for (var j = 0; j <= lastValid; j++) {
+        mask[rowBase + j] = 0.0;
+      }
+      for (var j = lastValid + 1; j < cacheLen; j++) {
+        mask[rowBase + j] = qwen3NegInf;
+      }
+    }
+
+    final kv = _zeroKv();
+    final inputs = <GraphInput>[
+      F32Input([1, 32, TalkerLayout.embeddingDim], buf),
+      I32Input([32], inputPos),
+      F32Input([1, 1, 32, cacheLen], mask),
+      for (var i = 0; i < TalkerLayout.numKvTensors; i++)
+        F32Input(_kvShapes[i], kv[i]),
+    ];
+
+    return runLiteRtGraph(
+      _bindings,
+      _talker.compiledModel,
+      TalkerLayout.prefill32Sig,
+      inputs,
+      _kvShapes,
+    );
+  }
+
+  /// Destroys the 3 compiled graphs' handles + the shared environment, and
+  /// closes [_tables]' open `text_embedding` file handle. Mirrors
+  /// `TtsCore.dispose`.
+  void dispose() {
+    if (_disposed) return;
+    _disposed = true;
+    for (final graph in [_talker, _mtp, _codec]) {
+      _bindings.destroyCompiledModel(graph.compiledModel);
+      _bindings.destroyOptions(graph.options);
+      _bindings.destroyModel(graph.model);
+    }
+    _bindings.destroyEnvironment(_environment);
+    _tables.dispose();
+  }
+}
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart
new file mode 100644
index 00000000..997a0c2b
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart
@@ -0,0 +1,146 @@
+// Load + talker-prefill smoke test for `Qwen3TtsCore` — the second test in
+// this package that loads real compiled `.tflite` graphs through our own
+// Dart LiteRT FFI (after `qwen3_talker_layout_test.dart`), and the first
+// that actually RUNS a forward pass (`runPrefill`) rather than only
+// introspecting declared tensor layouts.
+//
+// This is a shape-only gate: it asserts `Qwen3TtsCore.load` succeeds, the
+// introspected MTP/codec params look sane, and `runPrefill` — run on a real
+// prompt built via the already-verified Phase-1 chain (`Qwen2BpeEncoder` +
+// `Qwen3Tables` + `Qwen3Prompt`) — returns 56 finite, non-empty KV tensors
+// without throwing. Token-for-token correctness (matching the golden first
+// codebook-0 token) is Task 2.3's `runDecode` gate, not this one.
+//
+// The model bundle (~1.5 GB across the 3 graphs + tables) is NOT committed
+// to the repo — it lives in the local HuggingFace cache (see
+// [_defaultModelDir] below) or wherever `QWEN3_MODEL_DIR` points. When
+// absent (e.g. CI without the artifact fetched) the test skips gracefully;
+// when present (as for local device runs) it asserts the real load+prefill.
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:io';
+
+import 'package:flutter_gemma/core/domain/platform_types.dart'
+    show PreferredBackend;
+import 'package:flutter_gemma_speech/src/qwen3/npy_reader.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen2_bpe_encoder.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_prompt.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tables.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_talker_layout.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tts_core.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot dir — the local
+/// HuggingFace cache path for `litert-community/Qwen3-TTS-12Hz-0.6B-Base`.
+/// Override with the `QWEN3_MODEL_DIR` environment variable to run against
+/// a different snapshot. Mirrors `qwen3_talker_layout_test.dart`/
+/// `qwen3_tables_test.dart`'s identical helper.
+String _defaultModelDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66';
+}
+
+String _modelDir() =>
+    Platform.environment['QWEN3_MODEL_DIR'] ?? _defaultModelDir();
+
+/// Recursively scans [dir] and returns a basename -> absolute-path map for
+/// every regular file found. The talker/mtp/codec graphs + tokenizer sit
+/// directly in the snapshot dir, the host tables under `tables/`, and the
+/// demo voice under `voices/` — every basename is unique across the tree, so
+/// a flat map is enough to build `Qwen3TtsCore.load`'s `artifactPaths`.
+Map<String, String> _scanArtifactPaths(String dir) {
+  final out = <String, String>{};
+  for (final entity in Directory(dir).listSync(recursive: true)) {
+    if (entity is File) {
+      out[entity.uri.pathSegments.last] = entity.path;
+    }
+  }
+  return out;
+}
+
+void main() {
+  final modelDir = _modelDir();
+
+  test('Qwen3TtsCore.load + runPrefill: real graphs load, prefill returns 56 '
+      'finite KV tensors', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final artifactPaths = _scanArtifactPaths(modelDir);
+    final core = await Qwen3TtsCore.load(
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+    );
+    try {
+      expect(core.sampleRate, 24000);
+      // recipe (qwen3_tts_pipeline.py:162-163): mtp_cache_len == 17 (16
+      // MTP residual steps + 1).
+      expect(core.mtpCacheLen, 17);
+      expect(core.mtpKvShape, isNotEmpty);
+      expect(core.codecChunk, greaterThan(0));
+
+      // Real Phase-1 chain: encode -> build the talker prompt -> prefill.
+      // Independent Qwen3Tables/Qwen2BpeEncoder instances (not the core's
+      // internal ones) — mirrors how a real caller assembles a prompt
+      // ahead of driving the core, and keeps this test's prompt-assembly
+      // step verifiable against the already-covered `qwen3_prompt_test`/
+      // `qwen3_tables_test` behavior.
+      final tablesDir = '$modelDir/tables';
+      final encoder = await Qwen2BpeEncoder.fromTokenizerJson(
+        artifactPaths['tokenizer.json']!,
+      );
+      final tables = await Qwen3Tables.load(
+        codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
+        mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
+        textEmbPath: '$tablesDir/text_embedding_fp16.npy',
+        projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
+      );
+      try {
+        final speaker = readNpyF32(artifactPaths['demo_speaker.npy']!);
+        final ids = encoder.encode(
+          '<|im_start|>assistant\n'
+          'Hello, this is a test of the Qwen3 text to speech system.'
+          '<|im_end|>\n<|im_start|>assistant\n',
+        );
+        final prompt = Qwen3Prompt.build(
+          ids: ids,
+          speaker: speaker,
+          language: 'english',
+          tables: tables,
+        );
+
+        final kv = core.runPrefill(prompt.prefill, prompt.promptLen);
+
+        // ignore: avoid_print
+        print(
+          'QWEN3-PREFILL-TEST<<<promptLen=${prompt.promptLen} '
+          'kvCount=${kv.length} kv0Shape.len=${kv[0].length} '
+          'mtpCacheLen=${core.mtpCacheLen} mtpKvShape=${core.mtpKvShape} '
+          'codecChunk=${core.codecChunk}>>>',
+        );
+
+        expect(kv.length, TalkerLayout.numKvTensors);
+        for (var i = 0; i < kv.length; i++) {
+          expect(kv[i].isNotEmpty, isTrue, reason: 'kv[$i] is empty');
+          expect(
+            kv[i].every((v) => v.isFinite),
+            isTrue,
+            reason: 'kv[$i] has non-finite values',
+          );
+        }
+      } finally {
+        tables.dispose();
+      }
+    } finally {
+      core.dispose();
+    }
+  });
+}

From 63fc38680be4dccd3cdcc2fe8d79f4606e85c976 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 23:35:24 +0500
Subject: [PATCH 11/30] feat(qwen3): talker decode step + first-frame cb0
 golden

Ports _run_decode (mask + decode signature + logit split); the golden
gate reproduces the PyTorch reference's frame-0 cb0 exactly (1342) on
talker_fp32. Qwen3TtsCore.load gains an optional talkerFileName param
(defaults to int4) so the golden test can load fp32 without disturbing
the runtime default.
---
 .../lib/src/qwen3/qwen3_tts_core.dart         | 142 +++++++++++-
 .../test/qwen3/qwen3_talker_decode_test.dart  | 204 ++++++++++++++++++
 2 files changed, 337 insertions(+), 9 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index bf8a6958..2b6794a5 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -17,18 +17,28 @@
 // embedding into the talker's fixed 32-row `prefill_32` signature, builds
 // the matching causal `mask`, runs it against an all-zero initial KV cache
 // (`qwen3_tts_pipeline.py:216-217`), and returns the 56 filled KV tensors —
-// this initializes the KV cache the decode loop (`_run_decode`, Task 2.3)
-// threads forward one step at a time. This task only asserts the returned
-// KV tensors' shapes; token correctness (matching the golden first
-// codebook-0 token) is verified once `runDecode` exists.
+// this initializes the KV cache the decode loop ([Qwen3TtsCore.runDecode])
+// threads forward one step at a time.
+//
+// [Qwen3TtsCore.runDecode] ports `Qwen3TtsPipeline._run_decode`
+// (`qwen3_tts_pipeline.py:330-340`): builds the one-row causal `mask`
+// (`mask[...,:pos+1] = 0`, else `qwen3NegInf`) for the current KV-cache
+// write position, runs the talker's `decode` signature against the
+// threaded-forward KV cache, and splits the `[1,1,4096]` logits output into
+// codebook-0 logits (`[:3072]`) and the hidden-state tail (`[3072:]`)
+// consumed by the MTP graph (a later task). This is the correctness
+// milestone for the whole talker path: prefill -> decode -> KV threading ->
+// logit split -> cb0 scoring must reproduce the PyTorch reference's frame-0
+// cb0 exactly (see `qwen3_talker_decode_test.dart`'s golden gate).
 //
 // FFI style + graph load/run machinery: same as `TtsCore`/`SttCore` — see
 // `litert_graph.dart`'s file header for the create -> run -> lock(Read) ->
 // copy-through-locked-ptr -> unlock -> destroy sequence this delegates to.
-// [Qwen3TtsCore.runPrefill] is not truly public API (no v1 consumer outside
-// this package calls it directly) but is deliberately not name-mangled
-// private either, so `qwen3_prefill_test.dart` — a different library — can
-// drive it directly; annotated `@visibleForTesting` to say so, mirroring
+// [Qwen3TtsCore.runPrefill]/[Qwen3TtsCore.runDecode] are not truly public
+// API (no v1 consumer outside this package calls them directly) but are
+// deliberately not name-mangled private either, so `qwen3_prefill_test.dart`
+// / `qwen3_talker_decode_test.dart` — different libraries — can drive them
+// directly; annotated `@visibleForTesting` to say so, mirroring
 // `TtsCore.planMelWindows`/`concatSegments`.
 
 import 'dart:ffi';
@@ -170,9 +180,20 @@ class Qwen3TtsCore {
   /// [artifactPaths] is filename -> on-disk-path for the model bundle
   /// (talker_int4.tflite, mtp_fp32.tflite, codec_decoder_fp32.tflite,
   /// tokenizer.json, and the 4 `Qwen3Tables` members).
+  ///
+  /// [talkerFileName] selects which talker artifact to load — defaults to
+  /// the int4 runtime name (`talker_int4.tflite`) so every existing caller
+  /// is unaffected. The golden cb0 test
+  /// (`qwen3_talker_decode_test.dart`) passes `'talker_fp32.tflite'`
+  /// instead: the fixtures in `test/golden/qwen3/` were generated by
+  /// `gen_qwen3_goldens.py` against the fp32 talker
+  /// (`Qwen3TtsPipeline(..., talker_file='talker_fp32.tflite')`) — int4 is
+  /// NOT bit-exact vs the PyTorch reference, so only fp32 can reproduce the
+  /// golden frame-0 cb0.
   static Future<Qwen3TtsCore> load({
     required Map<String, String> artifactPaths,
     PreferredBackend? backend,
+    String talkerFileName = 'talker_int4.tflite',
   }) async {
     final bindings = LiteRtBindings.open();
     final accelerator = _acceleratorFor(backend);
@@ -197,7 +218,7 @@ class Qwen3TtsCore {
       final talker = loadLiteRtGraph(
         bindings,
         environment,
-        _artifactPath(artifactPaths, 'talker_int4.tflite'),
+        _artifactPath(artifactPaths, talkerFileName),
         accelerator,
       );
       loadedGraphs.add(talker);
@@ -394,6 +415,109 @@ class Qwen3TtsCore {
     );
   }
 
+  /// Runs one autoregressive talker decode step, threading [kv] (the 56
+  /// tensors from the previous [runPrefill]/[runDecode] call) forward one
+  /// position. Port of `Qwen3TtsPipeline._run_decode`
+  /// (`qwen3_tts_pipeline.py:330-340`).
+  ///
+  /// [embed] (`[1024]`) is the current step's input embedding — for the
+  /// very first decode step this is the last prefill row
+  /// (`prefill[0, -1]`, recipe `:219-220`); for later steps (Task 4.2's
+  /// loop) it's the assembled next-frame embedding. [pos] is the KV-cache
+  /// write position (0-indexed, matching `input_pos` passed to the graph).
+  ///
+  /// Builds the one-row causal `mask` (`[1,1,1,cacheLen]`,
+  /// `mask[...,:pos+1] = 0.0` else [qwen3NegInf]), runs the talker's
+  /// `decode` signature, and splits the `[1,1,4096]` `logits` output per
+  /// `TalkerLayout`'s frozen layout (file header): `[:3072]` is the
+  /// codebook-0 logits the caller scores/picks from ([cb0Logits]), `[3072:]`
+  /// is the hidden-state tail the MTP graph consumes ([hidden]). Returns the
+  /// 56 updated KV tensors ([newKv]) — the same order as [kv] (KV output
+  /// order == KV input order, per `TalkerLayout`) — to thread into the next
+  /// call.
+  ///
+  /// Not true public API (see this file's header) — [visibleForTesting] so
+  /// `qwen3_talker_decode_test.dart` can drive it directly, and structured
+  /// (single call, explicit `kv`/`pos` in, updated `kv` out) so a later
+  /// task's per-frame decode loop can call it repeatedly without needing any
+  /// internal state this class doesn't already expose.
+  @visibleForTesting
+  (Float32List cb0Logits, Float32List hidden, List<Float32List> newKv)
+  runDecode(List<Float32List> kv, Float32List embed, int pos) {
+    if (_disposed) {
+      throw StateError('Qwen3TtsCore is disposed');
+    }
+    if (kv.length != TalkerLayout.numKvTensors) {
+      throw ArgumentError.value(
+        kv.length,
+        'kv.length',
+        'Qwen3TtsCore.runDecode: expected ${TalkerLayout.numKvTensors} KV '
+            'tensors',
+      );
+    }
+    if (embed.length != TalkerLayout.embeddingDim) {
+      throw ArgumentError.value(
+        embed.length,
+        'embed.length',
+        'Qwen3TtsCore.runDecode: expected ${TalkerLayout.embeddingDim} '
+            '(embeddingDim)',
+      );
+    }
+    final cacheLen = TalkerLayout.cacheLen;
+    if (pos < 0 || pos >= cacheLen) {
+      throw ArgumentError.value(
+        pos,
+        'pos',
+        'Qwen3TtsCore.runDecode: pos must be in [0, $cacheLen)',
+      );
+    }
+
+    // mask[1,1,1,cacheLen]: mask[...,:pos+1] = 0.0 else qwen3NegInf.
+    // qwen3_tts_pipeline.py:330-340 (the decode-step causal mask — every
+    // KV-cache slot up to and including `pos` is attendable, everything
+    // after is not-yet-written).
+    final mask = Float32List(cacheLen);
+    for (var j = 0; j <= pos; j++) {
+      mask[j] = 0.0;
+    }
+    for (var j = pos + 1; j < cacheLen; j++) {
+      mask[j] = qwen3NegInf;
+    }
+
+    final inputs = <GraphInput>[
+      F32Input([1, 1, TalkerLayout.embeddingDim], embed),
+      I32Input([1], Int32List.fromList([pos])),
+      F32Input([1, 1, 1, cacheLen], mask),
+      for (var i = 0; i < TalkerLayout.numKvTensors; i++)
+        F32Input(_kvShapes[i], kv[i]),
+    ];
+
+    // decode's outputs are the 56 KV tensors (same order as the KV inputs)
+    // followed by `logits [1,1,4096]` — see `TalkerLayout`'s file header.
+    final outputShapes = <List<int>>[
+      ..._kvShapes,
+      [1, 1, TalkerLayout.logitsWidth],
+    ];
+
+    final outputs = runLiteRtGraph(
+      _bindings,
+      _talker.compiledModel,
+      TalkerLayout.decodeSig,
+      inputs,
+      outputShapes,
+    );
+
+    final newKv = outputs.sublist(0, TalkerLayout.numKvTensors);
+    final logits = outputs[TalkerLayout.numKvTensors];
+    final cb0Logits = logits.sublist(0, TalkerLayout.logitsCodec);
+    final hidden = logits.sublist(
+      TalkerLayout.logitsCodec,
+      TalkerLayout.logitsWidth,
+    );
+
+    return (cb0Logits, hidden, newKv);
+  }
+
   /// Destroys the 3 compiled graphs' handles + the shared environment, and
   /// closes [_tables]' open `text_embedding` file handle. Mirrors
   /// `TtsCore.dispose`.
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart
new file mode 100644
index 00000000..4b6948b4
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart
@@ -0,0 +1,204 @@
+// Talker decode step + first-frame codebook-0 (cb0) golden gate for
+// `Qwen3TtsCore.runDecode`.
+//
+// This is the correctness milestone for the whole talker path: prefill ->
+// decode -> KV threading -> logit split -> cb0 scoring must reproduce the
+// PyTorch reference's frame-0 cb0 exactly. `qwen3_prefill_test.dart` only
+// asserted `runPrefill`'s KV tensors are finite/non-empty (shape-only); this
+// test is the first genuine token-for-token gate against
+// `gen_qwen3_goldens.py`'s committed fixtures (`test/golden/qwen3/
+// frames.json`, `frame0.json`), themselves generated by a verbatim copy of
+// `Qwen3TtsPipeline.synthesize` (`text_to_speech_lm/python/
+// qwen3_tts_pipeline.py`) run against the SAME model snapshot.
+//
+// ⚠️ Loads `talker_fp32.tflite`, NOT the int4 runtime artifact
+// (`talker_int4.tflite`, `Qwen3TtsCore.load`'s default `talkerFileName`):
+// the golden fixtures were generated with `talker_file='talker_fp32.tflite'`
+// (see `tool/qwen3/gen_qwen3_goldens.py`'s `main()`) — int4 quantization is
+// NOT bit-exact vs the PyTorch reference, so only the fp32 talker can
+// reproduce the golden frame-0 cb0. fp32 is ~1.8 GB; compiling it is slow,
+// hence the generous `Timeout` below.
+//
+// The model bundle (~1.5 GB talker_int4 + ~1.8 GB talker_fp32 + mtp/codec
+// graphs + tables) is NOT committed to the repo — see
+// `qwen3_prefill_test.dart`'s file header for the same skip-when-absent
+// rationale ([_defaultModelDir]/`QWEN3_MODEL_DIR`).
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:convert';
+import 'dart:io';
+import 'dart:typed_data';
+
+import 'package:flutter_gemma/core/domain/platform_types.dart'
+    show PreferredBackend;
+import 'package:flutter_gemma_speech/src/qwen3/npy_reader.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen2_bpe_encoder.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_prompt.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_sampler.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tables.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tts_core.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot dir — the local
+/// HuggingFace cache path for `litert-community/Qwen3-TTS-12Hz-0.6B-Base`.
+/// Override with the `QWEN3_MODEL_DIR` environment variable to run against
+/// a different snapshot. Mirrors `qwen3_prefill_test.dart`'s identical
+/// helper.
+String _defaultModelDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66';
+}
+
+String _modelDir() =>
+    Platform.environment['QWEN3_MODEL_DIR'] ?? _defaultModelDir();
+
+/// Recursively scans [dir] and returns a basename -> absolute-path map for
+/// every regular file found. Mirrors `qwen3_prefill_test.dart`'s identical
+/// helper — every basename (incl. `talker_fp32.tflite`, sitting alongside
+/// `talker_int4.tflite` in the snapshot dir) is unique across the tree.
+Map<String, String> _scanArtifactPaths(String dir) {
+  final out = <String, String>{};
+  for (final entity in Directory(dir).listSync(recursive: true)) {
+    if (entity is File) {
+      out[entity.uri.pathSegments.last] = entity.path;
+    }
+  }
+  return out;
+}
+
+void main() {
+  final modelDir = _modelDir();
+
+  test('Qwen3TtsCore.runDecode: frame-0 cb0 matches the PyTorch golden '
+      '(frames.json[0][0] == frame0.json.cb0 == 1342)', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final artifactPaths = _scanArtifactPaths(modelDir);
+    if (!artifactPaths.containsKey('talker_fp32.tflite')) {
+      markTestSkipped(
+        'talker_fp32.tflite not found under $modelDir — the golden '
+        'fixtures were generated against the fp32 talker (int4 is not '
+        'bit-exact vs the PyTorch reference) and this test needs it '
+        'present to run.',
+      );
+      return;
+    }
+
+    // Golden fixtures — committed, always present (no skip-guard needed
+    // for these reads).
+    final framesGolden =
+        jsonDecode(
+              File('test/golden/qwen3/frames.json').readAsStringSync(),
+            )['frames']
+            as List;
+    final firstFrame = (framesGolden[0] as List).cast<int>();
+    final expectedCb0 = firstFrame[0];
+    final frame0Golden =
+        jsonDecode(File('test/golden/qwen3/frame0.json').readAsStringSync())
+            as Map<String, dynamic>;
+    // Sanity-check the fixtures agree with each other before trusting
+    // either as the gate value (both are read from the same synthesize
+    // run in `gen_qwen3_goldens.py`, so a mismatch here would mean a
+    // fixture-generation bug, not a Dart port bug).
+    expect(
+      expectedCb0,
+      frame0Golden['cb0'],
+      reason: 'golden fixtures disagree: frames.json[0][0] vs frame0.json.cb0',
+    );
+
+    final core = await Qwen3TtsCore.load(
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+      talkerFileName: 'talker_fp32.tflite',
+    );
+    try {
+      final tablesDir = '$modelDir/tables';
+      final encoder = await Qwen2BpeEncoder.fromTokenizerJson(
+        artifactPaths['tokenizer.json']!,
+      );
+      final tables = await Qwen3Tables.load(
+        codecEmbPath: '$tablesDir/codec_embedding_fp32.npy',
+        mtpEmbPath: '$tablesDir/mtp_embeddings_fp16.npy',
+        textEmbPath: '$tablesDir/text_embedding_fp16.npy',
+        projectionNpzPath: '$tablesDir/text_projection_fp32.npz',
+      );
+      try {
+        // Same text/template `gen_qwen3_goldens.py` used to generate the
+        // fixtures (`meta.json.text` / `ids.json.template`) — the real
+        // encode -> build chain, not a re-load of `ids.json` directly.
+        final speaker = readNpyF32(artifactPaths['demo_speaker.npy']!);
+        const text = 'Hello from on device text to speech.';
+        final ids = encoder.encode(
+          '<|im_start|>assistant\n$text<|im_end|>\n<|im_start|>assistant\n',
+        );
+        final prompt = Qwen3Prompt.build(
+          ids: ids,
+          speaker: speaker,
+          language: 'english',
+          tables: tables,
+        );
+
+        // _run_prefill (qwen3_tts_pipeline.py:315-328).
+        final kv = core.runPrefill(prompt.prefill, prompt.promptLen);
+
+        // Initial decode step: embed = prefill[0, -1] (the last prompt
+        // row), pos = promptLen - 1 (recipe :219-220).
+        final promptLen = prompt.promptLen;
+        final pos = promptLen - 1;
+        final embed = Float32List.sublistView(
+          prompt.prefill,
+          pos * 1024,
+          promptLen * 1024,
+        );
+
+        final (cb0Logits, hidden, _) = core.runDecode(kv, embed, pos);
+        expect(cb0Logits.length, 3072);
+        expect(hidden.length, 1024);
+
+        // cb0 scoring: `applyCb0Scoring` mutates in place (see its doc),
+        // so pass a COPY of the raw decode logits, not the original —
+        // carried forward from Task 1.5's sampler contract.
+        final scores = Float32List.fromList(cb0Logits);
+        applyCb0Scoring(
+          scores,
+          suppress: buildSuppress(),
+          // Frame 0: no prior codebook-0 picks yet, so the repetition
+          // penalty (which only touches indices in `history`) is a
+          // no-op — matches `gen_qwen3_goldens.py`'s `history = set()`
+          // at the start of its decode loop.
+          history: <int>{},
+          repetitionPenalty: 1.05,
+          // `len(frames) < 2` is true for frame 0 (0 < 2) — forces
+          // EOS's score to -1e9 so the talker cannot end the utterance
+          // before at least 2 frames are produced.
+          minNewTokensGuard: true,
+        );
+        final cb0 = pickGreedy(scores);
+
+        // ignore: avoid_print
+        print(
+          'QWEN3-DECODE-TEST<<<promptLen=$promptLen pos=$pos cb0=$cb0 '
+          'expectedCb0=$expectedCb0>>>',
+        );
+
+        // THE gate: reproduces the PyTorch reference's frame-0 cb0
+        // exactly.
+        expect(cb0, expectedCb0);
+        expect(cb0, 1342);
+      } finally {
+        tables.dispose();
+      }
+    } finally {
+      core.dispose();
+    }
+  }, timeout: const Timeout(Duration(minutes: 15)));
+}

From 4e290540165e89d1694bde299e0f16357f2de688 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Mon, 3 Aug 2026 23:55:58 +0500
Subject: [PATCH 12/30] feat(qwen3): MTP 15-codebook inner loop + residual
 golden

Ports Qwen3TtsPipeline._run_mtp (qwen3_tts_pipeline.py:342-380): a
16-step inner loop over a 17-slot KV cache that predicts a frame's 15
residual codebooks from the talker's hidden state + codebook-0 token.
Introspects the MTP graph's output_0 (residual-head logits) shape at
load time via the bulk getOutputTensorLayouts accessor rather than
hardcoding it.

Gate: runMtp fed the golden frame-0 hidden/cb0 reproduces the PyTorch
reference's 15-code residual exactly.
---
 .../lib/src/qwen3/qwen3_tts_core.dart         | 293 ++++++++++++++++++
 .../test/qwen3/qwen3_mtp_test.dart            | 111 +++++++
 2 files changed, 404 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_mtp_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index 2b6794a5..2014cdb9 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -40,8 +40,20 @@
 // / `qwen3_talker_decode_test.dart` — different libraries — can drive them
 // directly; annotated `@visibleForTesting` to say so, mirroring
 // `TtsCore.planMelWindows`/`concatSegments`.
+//
+// [Qwen3TtsCore.runMtp] ports `Qwen3TtsPipeline._run_mtp`
+// (`qwen3_tts_pipeline.py:342-380`): the 16-step MTP inner loop that
+// predicts the 15 residual codebooks of one frame from the talker's hidden
+// state ([runDecode]'s `hidden`) + the already-picked codebook-0 token. The
+// MTP graph is single-signature (`args_0..4` -> `output_0..2`, no
+// prefill/decode split like the talker); [load] introspects `output_0`'s
+// shape (the 15-head residual-logit tensor, `[15, vocab]`) via the bulk
+// `getOutputTensorLayouts` accessor (there is no per-output-index
+// accessor — see [_readOutputShapes]'s doc) so this file never hardcodes
+// the residual vocabulary size.
 
 import 'dart:ffi';
+import 'dart:io' show Platform;
 import 'dart:math' as math;
 import 'dart:typed_data';
 
@@ -57,6 +69,7 @@ import 'package:flutter_gemma_litertlm/litert_bindings.dart';
 
 import '../litert/litert_graph.dart';
 import 'qwen2_bpe_encoder.dart';
+import 'qwen3_sampler.dart' show pickGreedy;
 import 'qwen3_tables.dart';
 import 'qwen3_talker_layout.dart';
 
@@ -112,6 +125,79 @@ List<int> _readInputShape(
   }
 }
 
+/// Reads the first [count] output tensor shapes for [graph]'s
+/// [signatureIndex] via the BULK `LiteRtGetCompiledModelOutputTensorLayouts`
+/// accessor — unlike [_readInputShape]'s per-index `getInputTensorLayout`,
+/// there is no per-output-index accessor (see `TalkerLayout`'s file header
+/// for the same gap on the talker graph): the C API always fills
+/// `num_layouts` entries starting at output 0, so reading output N's shape
+/// means reading outputs `0..N` together into one contiguous native array.
+/// Only used for the MTP graph at [Qwen3TtsCore.load] time, where [count] is
+/// the small, fixed `3` (`output_0` logits, `output_1`/`output_2` k/v) — see
+/// this file's header.
+List<List<int>> _readOutputShapes(
+  LiteRtBindings bindings,
+  LiteRtCompiledModel graph,
+  int signatureIndex,
+  int count,
+  String label,
+) {
+  final shapes = <List<int>>[];
+  if (Platform.isWindows) {
+    final layouts = calloc<LiteRtLayoutMsvc>(count);
+    try {
+      bindings
+          .getOutputTensorLayouts(
+            graph,
+            signatureIndex,
+            count,
+            layouts.cast(),
+            false,
+          )
+          .check('LiteRtGetCompiledModelOutputTensorLayouts($label)');
+      for (var i = 0; i < count; i++) {
+        final s = (layouts + i).ref;
+        final rank = s.rankAndHasStrides & 0x7f;
+        shapes.add([for (var d = 0; d < rank; d++) s.dimensions[d]]);
+      }
+    } finally {
+      calloc.free(layouts);
+    }
+    return shapes;
+  }
+  final layouts = calloc<LiteRtLayoutPosix>(count);
+  try {
+    bindings
+        .getOutputTensorLayouts(
+          graph,
+          signatureIndex,
+          count,
+          layouts.cast(),
+          false,
+        )
+        .check('LiteRtGetCompiledModelOutputTensorLayouts($label)');
+    for (var i = 0; i < count; i++) {
+      final s = (layouts + i).ref;
+      final rank = s.rankAndHasStrides & 0x7f;
+      shapes.add([for (var d = 0; d < rank; d++) s.dimensions[d]]);
+    }
+  } finally {
+    calloc.free(layouts);
+  }
+  return shapes;
+}
+
+/// `true` iff [a] and [b] have the same length and elements — a plain
+/// `List<int>` equality check (no `package:collection` dependency in this
+/// package; see `pubspec.yaml`).
+bool _shapeEquals(List<int> a, List<int> b) {
+  if (a.length != b.length) return false;
+  for (var i = 0; i < a.length; i++) {
+    if (a[i] != b[i]) return false;
+  }
+  return true;
+}
+
 /// Synchronous native core for the Qwen3-TTS talker/MTP/codec pipeline. NOT
 /// safe to share across isolates — the FFI handles it holds are owned by the
 /// isolate that called [load]. Mirrors `TtsCore`/`SttCore`'s shape.
@@ -127,6 +213,8 @@ class Qwen3TtsCore {
     required this._kvShapes,
     required this.mtpCacheLen,
     required this.mtpKvShape,
+    required this._mtpLogitsShape,
+    required this._mtpResidualVocab,
     required this.codecChunk,
   });
 
@@ -163,6 +251,18 @@ class Qwen3TtsCore {
   /// MTP graph's `args_3` (k-cache) input shape, read once at load time.
   final List<int> mtpKvShape;
 
+  /// MTP graph's `output_0` (residual-head logits) shape, read once at load
+  /// time via [_readOutputShapes] — expected `[15, vocab]` (a leading `1`
+  /// batch dim, `[1, 15, vocab]`, is also tolerated; see [load]). Used
+  /// verbatim as [runMtp]'s `outputShapes[0]` on every step.
+  final List<int> _mtpLogitsShape;
+
+  /// Residual-codebook vocabulary size — the last dim of [_mtpLogitsShape].
+  /// Read (not hardcoded) so a future model revision that reshapes the MTP
+  /// head fails loud at load time (see [load]) instead of [runMtp] silently
+  /// misreading which slice of `output_0` is head `t-1`.
+  final int _mtpResidualVocab;
+
   /// Codec-decoder graph's `args_0` input's last dim — its fixed
   /// frame-chunk width.
   final int codecChunk;
@@ -276,6 +376,70 @@ class Qwen3TtsCore {
         3,
         'mtp.args_3 (k-cache)',
       );
+
+      // MTP has 3 outputs (recipe `:373-376`: `output_0` residual-head
+      // logits, `output_1`/`output_2` the new k/v cache) — read all 3 via
+      // the bulk accessor (see [_readOutputShapes]'s doc for why a single
+      // call must ask for all of them) and pick out `output_0` by shape:
+      // it's the one that does NOT match [mtpKvShape] (k/v are both
+      // `mtpKvShape`-shaped). Verified once, at load time, against the
+      // REAL compiled graph — not hardcoded — per Task 3.1's brief.
+      final mtpOutputShapes = _readOutputShapes(
+        bindings,
+        mtp.compiledModel,
+        0,
+        3,
+        'mtp outputs (output_0..2)',
+      );
+      if (mtpOutputShapes.length != 3) {
+        throw StateError(
+          'Qwen3TtsCore.load: expected 3 MTP graph outputs '
+          '(output_0 logits, output_1/output_2 k/v), got '
+          '${mtpOutputShapes.length}',
+        );
+      }
+      final mtpLogitsShape = mtpOutputShapes[0];
+      if (_shapeEquals(mtpLogitsShape, mtpKvShape)) {
+        throw StateError(
+          'Qwen3TtsCore.load: expected MTP output_0 to be the '
+          'residual-head logits (shape != mtpKvShape=$mtpKvShape), got '
+          '$mtpLogitsShape — output order may have drifted from the '
+          'recipe (output_0=logits, output_1=k, output_2=v)',
+        );
+      }
+      if (!_shapeEquals(mtpOutputShapes[1], mtpKvShape) ||
+          !_shapeEquals(mtpOutputShapes[2], mtpKvShape)) {
+        throw StateError(
+          'Qwen3TtsCore.load: expected MTP output_1/output_2 to match '
+          'mtpKvShape=$mtpKvShape (the new k/v cache), got '
+          '${mtpOutputShapes[1]} / ${mtpOutputShapes[2]}',
+        );
+      }
+      // `[15, vocab]` (observed) or `[1, 15, vocab]` (a leading batch dim,
+      // tolerated defensively — see Task 3.1's brief) — either way the
+      // flat `output_0` buffer is row-major `[15 * vocab]`, so only
+      // `vocab` (the last dim) is actually needed by [runMtp].
+      final int mtpResidualVocab;
+      final int mtpResidualHeads;
+      if (mtpLogitsShape.length == 2) {
+        mtpResidualHeads = mtpLogitsShape[0];
+        mtpResidualVocab = mtpLogitsShape[1];
+      } else if (mtpLogitsShape.length == 3 && mtpLogitsShape[0] == 1) {
+        mtpResidualHeads = mtpLogitsShape[1];
+        mtpResidualVocab = mtpLogitsShape[2];
+      } else {
+        throw StateError(
+          'Qwen3TtsCore.load: unexpected MTP output_0 shape '
+          '$mtpLogitsShape (want [15, vocab] or [1, 15, vocab])',
+        );
+      }
+      if (mtpResidualHeads != 15) {
+        throw StateError(
+          'Qwen3TtsCore.load: expected MTP output_0 to have 15 residual '
+          'heads, got $mtpResidualHeads (shape=$mtpLogitsShape)',
+        );
+      }
+
       final codecInShape = _readInputShape(
         bindings,
         codec.compiledModel,
@@ -302,6 +466,7 @@ class Qwen3TtsCore {
       gemmaLog(
         '[Qwen3TtsCore] loaded: backend=$backend, 3 graphs compiled, '
         'mtpCacheLen=$mtpCacheLen, mtpKvShape=$mtpKvShape, '
+        'mtpLogitsShape=$mtpLogitsShape, mtpResidualVocab=$mtpResidualVocab, '
         'codecChunk=$codecChunk',
       );
 
@@ -316,6 +481,8 @@ class Qwen3TtsCore {
         kvShapes: kvShapes,
         mtpCacheLen: mtpCacheLen,
         mtpKvShape: mtpKvShape,
+        mtpLogitsShape: mtpLogitsShape,
+        mtpResidualVocab: mtpResidualVocab,
         codecChunk: codecChunk,
       );
     } catch (_) {
@@ -518,6 +685,132 @@ class Qwen3TtsCore {
     return (cb0Logits, hidden, newKv);
   }
 
+  /// Runs the MTP (multi-token-prediction) 16-step inner loop that predicts
+  /// the 15 residual codebooks of one frame from the talker's last hidden
+  /// state [hidden] (`[1024]`, [runDecode]'s `hidden` output) and the
+  /// already-picked codebook-0 token [cb0]. Port of
+  /// `Qwen3TtsPipeline._run_mtp` (`qwen3_tts_pipeline.py:342-380`).
+  ///
+  /// The MTP graph is a single decode step over a fixed [mtpCacheLen]-slot
+  /// (17) KV cache, invoked 16 times per frame (`t = 0..15`): two seed
+  /// feeds (`hidden`, then `codecEmbRow(cb0)`), then one feed per residual
+  /// codebook, threading the graph's own k/v outputs (`output_1`/
+  /// `output_2`) forward each step exactly like [runDecode] threads the
+  /// talker's KV cache — except here the loop owns the cache itself
+  /// (there's no separate prefill).
+  ///
+  /// Step `t`'s embedding is `feeds[t]` for `t < 2` (the two seeds above),
+  /// else [Qwen3Tables.mtpEmbRow] of residual group `t - 2` at the
+  /// previously-picked code — so the loop only ever embeds groups `0..13`
+  /// (`t` ranges `2..15`); group 14 is never looked up here (it's used
+  /// later, when the caller assembles the *next* frame's talker embedding —
+  /// not by this loop). Head `t - 1` of `output_0` is read (and, when
+  /// `t >= 1`, picked via [pickGreedy]) at every step from `t = 1` to
+  /// `t = 15`, producing the 15 returned codes — this off-by-one is
+  /// faithful to the recipe, not a bug: ported verbatim, not "fixed".
+  ///
+  /// [greedy] must be `true` — only the golden (`do_sample=False`) path is
+  /// wired so far; a future task can thread [pickSampled] through the same
+  /// loop shape once a sampled decode path is needed.
+  ///
+  /// Not true public API (see this file's header) — [visibleForTesting] so
+  /// `qwen3_mtp_test.dart` can drive it directly, mirroring [runPrefill]/
+  /// [runDecode].
+  @visibleForTesting
+  List<int> runMtp(Float32List hidden, int cb0, {bool greedy = true}) {
+    if (_disposed) {
+      throw StateError('Qwen3TtsCore is disposed');
+    }
+    if (!greedy) {
+      throw UnimplementedError(
+        'Qwen3TtsCore.runMtp: only greedy (do_sample=False) picking is '
+        'wired so far',
+      );
+    }
+    if (hidden.length != TalkerLayout.embeddingDim) {
+      throw ArgumentError.value(
+        hidden.length,
+        'hidden.length',
+        'Qwen3TtsCore.runMtp: expected ${TalkerLayout.embeddingDim} '
+            '(embeddingDim)',
+      );
+    }
+
+    // k_all/v_all: qwen3_tts_pipeline.py:364-365
+    // (`k_all = np.zeros(self._mtp_kv_shape, np.float32); v_all =
+    // np.zeros_like(k_all)`) — reassigned each step to the graph's own
+    // `output_1`/`output_2`, same "thread the previous step's output back
+    // in as the next step's input" shape as [runDecode]'s KV threading.
+    final kvCount = mtpKvShape.fold<int>(1, (a, b) => a * b);
+    var kAll = Float32List(kvCount);
+    var vAll = Float32List(kvCount);
+
+    // feeds = [hidden, self._codec_emb[cb0]] (qwen3_tts_pipeline.py:366).
+    final feeds = <Float32List>[hidden, _tables.codecEmbRow(cb0)];
+    final codes = <int>[];
+
+    // output_0 (logits), output_1 (k), output_2 (v) — order + shapes
+    // introspected once at [load] time (see [_mtpLogitsShape]'s doc); used
+    // verbatim here so [runLiteRtGraph]'s per-output tensor-buffer creation
+    // matches the graph's real output layout on every step.
+    final outputShapes = <List<int>>[_mtpLogitsShape, mtpKvShape, mtpKvShape];
+
+    for (var t = 0; t < 16; t++) {
+      // embed = (feeds[t] if t < 2 else self._mtp_emb[t - 2][codes[-1]])
+      // .reshape(1, 1, _HIDDEN) (qwen3_tts_pipeline.py:369-370).
+      final embed = t < 2 ? feeds[t] : _tables.mtpEmbRow(t - 2, codes.last);
+
+      // mask = np.where(np.arange(cache) <= t, 0.0, _NEG_INF)...
+      // .reshape(1, 1, 1, -1) (qwen3_tts_pipeline.py:371-372).
+      final mask = Float32List(mtpCacheLen);
+      for (var j = 0; j <= t; j++) {
+        mask[j] = 0.0;
+      }
+      for (var j = t + 1; j < mtpCacheLen; j++) {
+        mask[j] = qwen3NegInf;
+      }
+
+      // out = self._mtp(args_0=embed, args_1=[t], args_2=mask,
+      //                  args_3=k_all, args_4=v_all)
+      // (qwen3_tts_pipeline.py:373-375).
+      final inputs = <GraphInput>[
+        F32Input([1, 1, TalkerLayout.embeddingDim], embed),
+        I32Input([1], Int32List.fromList([t])),
+        F32Input([1, 1, 1, mtpCacheLen], mask),
+        F32Input(mtpKvShape, kAll),
+        F32Input(mtpKvShape, vAll),
+      ];
+
+      final out = runLiteRtGraph(
+        _bindings,
+        _mtp.compiledModel,
+        0,
+        inputs,
+        outputShapes,
+      );
+
+      // k_all, v_all = out['output_1'], out['output_2']
+      // (qwen3_tts_pipeline.py:376).
+      kAll = out[1];
+      vAll = out[2];
+
+      // if t >= 1: codes.append(_pick(out['output_0'][t - 1], ...))
+      // (qwen3_tts_pipeline.py:377-379). `out[0]` is the flat, row-major
+      // `[15 * vocab]` (or `[1, 15, vocab]`) buffer — head `t - 1` is the
+      // `vocab`-wide slice at that row, regardless of a leading batch dim
+      // (row-major layout is unaffected by a leading size-1 axis).
+      if (t >= 1) {
+        final head = out[0].sublist(
+          (t - 1) * _mtpResidualVocab,
+          t * _mtpResidualVocab,
+        );
+        codes.add(pickGreedy(head));
+      }
+    }
+
+    return codes;
+  }
+
   /// Destroys the 3 compiled graphs' handles + the shared environment, and
   /// closes [_tables]' open `text_embedding` file handle. Mirrors
   /// `TtsCore.dispose`.
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_mtp_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_mtp_test.dart
new file mode 100644
index 00000000..8dbf0414
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_mtp_test.dart
@@ -0,0 +1,111 @@
+// MTP (multi-token-prediction) 16-step inner loop golden gate for
+// `Qwen3TtsCore.runMtp`.
+//
+// This test isolates the MTP graph from the talker: it feeds the GOLDEN
+// frame-0 `hidden` (the talker's last hidden state) + `cb0` (=1342, already
+// gated by `qwen3_talker_decode_test.dart`) straight from
+// `test/golden/qwen3/frame0.json` into `runMtp`, and asserts the returned 15
+// residual codes equal `frame0.json.residual` exactly. Because the talker
+// isn't exercised here, `Qwen3TtsCore.load` uses its DEFAULT
+// `talkerFileName` (`talker_int4.tflite`, fast) rather than the fp32
+// artifact `qwen3_talker_decode_test.dart` needs for a bit-exact cb0 —
+// `runMtp` only ever touches the MTP graph (`mtp_fp32.tflite`, already
+// fp32/bit-exact) and the host tables.
+//
+// The model bundle is NOT committed to the repo — see
+// `qwen3_prefill_test.dart`'s file header for the same skip-when-absent
+// rationale ([_defaultModelDir]/`QWEN3_MODEL_DIR`).
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:convert';
+import 'dart:io';
+import 'dart:typed_data';
+
+import 'package:flutter_gemma/core/domain/platform_types.dart'
+    show PreferredBackend;
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tts_core.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot dir — the local
+/// HuggingFace cache path for `litert-community/Qwen3-TTS-12Hz-0.6B-Base`.
+/// Override with the `QWEN3_MODEL_DIR` environment variable to run against
+/// a different snapshot. Mirrors `qwen3_talker_decode_test.dart`'s identical
+/// helper.
+String _defaultModelDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66';
+}
+
+String _modelDir() =>
+    Platform.environment['QWEN3_MODEL_DIR'] ?? _defaultModelDir();
+
+/// Recursively scans [dir] and returns a basename -> absolute-path map for
+/// every regular file found. Mirrors `qwen3_talker_decode_test.dart`'s
+/// identical helper.
+Map<String, String> _scanArtifactPaths(String dir) {
+  final out = <String, String>{};
+  for (final entity in Directory(dir).listSync(recursive: true)) {
+    if (entity is File) {
+      out[entity.uri.pathSegments.last] = entity.path;
+    }
+  }
+  return out;
+}
+
+void main() {
+  final modelDir = _modelDir();
+
+  test('Qwen3TtsCore.runMtp: frame-0 residual matches the PyTorch golden '
+      '(frame0.json.residual)', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final artifactPaths = _scanArtifactPaths(modelDir);
+
+    // Golden fixtures — committed, always present (no skip-guard needed).
+    final frame0Golden =
+        jsonDecode(File('test/golden/qwen3/frame0.json').readAsStringSync())
+            as Map<String, dynamic>;
+    final hidden = Float32List.fromList(
+      (frame0Golden['hidden'] as List)
+          .map((e) => (e as num).toDouble())
+          .toList(),
+    );
+    final cb0 = frame0Golden['cb0'] as int;
+    final expectedResidual = (frame0Golden['residual'] as List).cast<int>();
+    expect(hidden.length, 1024);
+    expect(cb0, 1342);
+    expect(expectedResidual.length, 15);
+
+    // Default `talkerFileName` (int4) — this test never calls
+    // runPrefill/runDecode, so the talker's precision doesn't matter; only
+    // the MTP graph (already fp32) is exercised.
+    final core = await Qwen3TtsCore.load(
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+    );
+    try {
+      final residual = core.runMtp(hidden, cb0);
+
+      // ignore: avoid_print
+      print(
+        'QWEN3-MTP-TEST<<<cb0=$cb0 residual=$residual '
+        'expectedResidual=$expectedResidual>>>',
+      );
+
+      // THE gate: reproduces the PyTorch reference's frame-0 residual
+      // codebooks exactly.
+      expect(residual, expectedResidual);
+    } finally {
+      core.dispose();
+    }
+  }, timeout: const Timeout(Duration(minutes: 5)));
+}

From b8eb051d41d4609622bbe1142a804edfe4c24333 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 00:08:49 +0500
Subject: [PATCH 13/30] =?UTF-8?q?feat(qwen3):=20codec=20chunked=20decode?=
 =?UTF-8?q?=20=E2=86=92=2024=20kHz=20PCM?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Ports Qwen3TtsPipeline._decode_codes (qwen3_tts_pipeline.py:382-399):
sliding-window codec decode with 25-frame left context, transposing
[T,16] codes into the codec's [1,16,chunk] int32 input and cropping
context samples out of each window's [1,1,chunk*1920] PCM output.

Golden gate against frames.json -> waveform_f32.bin: corr=1.0,
maxAbsDiff=0.0 on the real fp32 codec graph.
---
 .../lib/src/qwen3/qwen3_tts_core.dart         | 130 ++++++++++++++
 .../test/qwen3/qwen3_codec_test.dart          | 168 ++++++++++++++++++
 2 files changed, 298 insertions(+)
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index 2014cdb9..ff66a84e 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -51,6 +51,21 @@
 // `getOutputTensorLayouts` accessor (there is no per-output-index
 // accessor — see [_readOutputShapes]'s doc) so this file never hardcodes
 // the residual vocabulary size.
+//
+// [Qwen3TtsCore.decodeCodes] ports `Qwen3TtsPipeline._decode_codes`
+// (`qwen3_tts_pipeline.py:382-399`): turns the accumulated `[T, 16]` codec
+// frames (codebook-0 + the 15 MTP residuals, one row per talker frame) into
+// 24 kHz PCM by running them through the codec-decoder graph in fixed-size
+// [codecChunk]-frame windows, each carrying 25 frames of LEFT CONTEXT from
+// the previous window (`ctx = 25`) that is decoded but then cropped back
+// out of the emitted audio — the codec is a small causal-ish conv stack, not
+// a fully streaming one, so re-feeding a tail of already-seen frames as
+// context on every step is what keeps chunk boundaries from producing
+// audible seams. Every codec call decodes exactly [codecChunk] frames'
+// worth of PCM (`[1, 1, codecChunk * _upsampleFactor]`) regardless of how
+// many of the window's rows are real (the rest of `buf` is left as
+// zero-padding); only the `window.length`-worth of frames actually fed are
+// kept from each call's output.
 
 import 'dart:ffi';
 import 'dart:io' show Platform;
@@ -78,6 +93,18 @@ import 'qwen3_talker_layout.dart';
 /// `_run_prefill` and `_run_decode`'s causal masks).
 const double qwen3NegInf = -1e9;
 
+/// Codec-frame width — codebook-0 + the 15 MTP residuals — matches
+/// `qwen3_tts_pipeline.py`'s module-level `_NUM_CODE_GROUPS = 16`. Used by
+/// [Qwen3TtsCore.decodeCodes] to size + transpose the codec's `[1, 16,
+/// chunk]` input.
+const int _numCodeGroups = 16;
+
+/// Codec-frame -> PCM-sample upsample factor — matches
+/// `qwen3_tts_pipeline.py`'s module-level `_UPSAMPLE = 1920` (24 kHz output
+/// at the talker's 12.5 Hz frame rate). Used by [Qwen3TtsCore.decodeCodes]
+/// to size the codec's output and crop left-context samples out of it.
+const int _upsampleFactor = 1920;
+
 int _acceleratorFor(PreferredBackend? backend) {
   switch (backend) {
     case PreferredBackend.gpu:
@@ -811,6 +838,109 @@ class Qwen3TtsCore {
     return codes;
   }
 
+  /// Decodes the accumulated `[T, 16]` codec [frames] (row `t` = codebook-0
+  /// + the 15 MTP residuals for talker frame `t`, e.g. every row of
+  /// [runMtp]'s output prefixed with its `cb0`) into 24 kHz PCM in `[-1,
+  /// 1]`. Port of `Qwen3TtsPipeline._decode_codes`
+  /// (`qwen3_tts_pipeline.py:382-399`) — see this file's header for the
+  /// sliding-window-with-left-context rationale.
+  ///
+  /// Walks [frames] in windows of at most [codecChunk] rows: each window
+  /// after the first carries up to 25 rows of left context (`c = min(25,
+  /// i)`) copied from the END of the previous window, so a window spans
+  /// `[i - c, j)` where `j = min(i + codecChunk - c, frames.length)` — the
+  /// loop only ever advances `i` to `j`, i.e. by `codecChunk - c` NEW rows
+  /// per step. Each window is transposed into the codec's fixed
+  /// `[1, 16, codecChunk]` `args_0` input (`buf[0, :, :window.length] =
+  /// window.T`, zero-padded past `window.length`; row-major flat index for
+  /// codebook `k`, window position `n` is `k * codecChunk + n` — see
+  /// [runLiteRtGraph]'s `I32Input`), producing `[1, 1, codecChunk *
+  /// _upsampleFactor]` PCM; only the samples for the window's OWN (non-
+  /// context) rows are kept (`wav.sublist(c * _upsampleFactor, window.length
+  /// * _upsampleFactor)`) before being concatenated across windows.
+  ///
+  /// Not true public API (see this file's header) — [visibleForTesting] so
+  /// `qwen3_codec_test.dart` can drive it directly against the golden
+  /// `frames.json` / `waveform_f32.bin` fixtures, mirroring [runPrefill]/
+  /// [runDecode]/[runMtp].
+  @visibleForTesting
+  Float32List decodeCodes(List<List<int>> frames) {
+    if (_disposed) {
+      throw StateError('Qwen3TtsCore is disposed');
+    }
+    for (var t = 0; t < frames.length; t++) {
+      if (frames[t].length != _numCodeGroups) {
+        throw ArgumentError.value(
+          frames[t].length,
+          'frames[$t].length',
+          'Qwen3TtsCore.decodeCodes: expected $_numCodeGroups codebooks per '
+              'frame',
+        );
+      }
+    }
+
+    // chunk, ctx = self._codec_chunk, 25 (qwen3_tts_pipeline.py:384).
+    const ctx = 25;
+    final chunk = codecChunk;
+    final pieces = <Float32List>[];
+    var i = 0;
+    while (i < frames.length) {
+      // c = min(ctx, i); j = min(i + chunk - c, len(codes))
+      // (qwen3_tts_pipeline.py:388-391).
+      final c = math.min(ctx, i);
+      final j = math.min(i + chunk - c, frames.length);
+      // window = codes[i - c:j] (qwen3_tts_pipeline.py:392).
+      final window = frames.sublist(i - c, j);
+
+      // buf = zeros(1, 16, chunk); buf[0, :, :len(window)] = window.T
+      // (qwen3_tts_pipeline.py:393-394) — flat row-major `[1,16,chunk]`:
+      // codebook k, window position n -> buf[k * chunk + n].
+      final buf = Int32List(_numCodeGroups * chunk);
+      for (var n = 0; n < window.length; n++) {
+        final row = window[n];
+        for (var k = 0; k < _numCodeGroups; k++) {
+          buf[k * chunk + n] = row[k];
+        }
+      }
+
+      // out = self._codec(args_0=buf); wav = out.values()[0][0, 0]
+      // (qwen3_tts_pipeline.py:395-396).
+      final out = runLiteRtGraph(
+        _bindings,
+        _codec.compiledModel,
+        0,
+        [
+          I32Input([1, _numCodeGroups, chunk], buf),
+        ],
+        [
+          [1, 1, chunk * _upsampleFactor],
+        ],
+      );
+      final wav = out[0];
+
+      // pieces.append(wav[c * _UPSAMPLE:len(window) * _UPSAMPLE])
+      // (qwen3_tts_pipeline.py:397) — drop the left-context samples.
+      pieces.add(
+        Float32List.sublistView(
+          wav,
+          c * _upsampleFactor,
+          window.length * _upsampleFactor,
+        ),
+      );
+      i = j;
+    }
+
+    // return np.concatenate(pieces) (qwen3_tts_pipeline.py:399).
+    final total = pieces.fold<int>(0, (sum, p) => sum + p.length);
+    final result = Float32List(total);
+    var offset = 0;
+    for (final piece in pieces) {
+      result.setRange(offset, offset + piece.length, piece);
+      offset += piece.length;
+    }
+    return result;
+  }
+
   /// Destroys the 3 compiled graphs' handles + the shared environment, and
   /// closes [_tables]' open `text_embedding` file handle. Mirrors
   /// `TtsCore.dispose`.
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart
new file mode 100644
index 00000000..a300d16a
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart
@@ -0,0 +1,168 @@
+// Codec chunked-decode golden gate for `Qwen3TtsCore.decodeCodes`.
+//
+// This test isolates the codec-decoder graph from the talker/MTP: it feeds
+// the GOLDEN `frames.json` (all `[T=26, 16]` codes — codebook-0 + the 15 MTP
+// residuals, one row per frame, already gated by `qwen3_talker_decode_test
+// .dart`/`qwen3_mtp_test.dart`) straight into `decodeCodes`, and asserts the
+// returned PCM matches `waveform_f32.bin` (the golden waveform,
+// `Qwen3TtsPipeline._decode_codes`'s output on the SAME codes — see
+// `tool/qwen3/gen_qwen3_goldens.py`). Because the talker/MTP graphs aren't
+// exercised here, `Qwen3TtsCore.load` uses its DEFAULT `talkerFileName`
+// (`talker_int4.tflite`, fast) — `decodeCodes` only ever touches the codec
+// graph (`codec_decoder_fp32.tflite`, already fp32/bit-exact) and never
+// looks at the talker at all.
+//
+// T=26 is well under the codec's fixed chunk width (64, per
+// `qwen3_tts_core.dart`'s `Qwen3TtsCore.load` introspection of
+// `codec_decoder_fp32.tflite`'s `args_0` input), so this golden exercises
+// exactly ONE codec call with no left context (`i=0` -> `c=min(25,0)=0`) —
+// `decodeCodes`'s sliding-window loop itself (needed for `T > 64`) is
+// exercised by construction, not by this fixture's `T`, but not stressed by
+// it either.
+//
+// The model bundle is NOT committed to the repo — see
+// `qwen3_prefill_test.dart`'s file header for the same skip-when-absent
+// rationale ([_defaultModelDir]/`QWEN3_MODEL_DIR`).
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:convert';
+import 'dart:io';
+import 'dart:math' as math;
+import 'dart:typed_data';
+
+import 'package:flutter_gemma/core/domain/platform_types.dart'
+    show PreferredBackend;
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tts_core.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot dir — the local
+/// HuggingFace cache path for `litert-community/Qwen3-TTS-12Hz-0.6B-Base`.
+/// Override with the `QWEN3_MODEL_DIR` environment variable to run against
+/// a different snapshot. Mirrors `qwen3_mtp_test.dart`'s identical helper.
+String _defaultModelDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66';
+}
+
+String _modelDir() =>
+    Platform.environment['QWEN3_MODEL_DIR'] ?? _defaultModelDir();
+
+/// Recursively scans [dir] and returns a basename -> absolute-path map for
+/// every regular file found. Mirrors `qwen3_mtp_test.dart`'s identical
+/// helper.
+Map<String, String> _scanArtifactPaths(String dir) {
+  final out = <String, String>{};
+  for (final entity in Directory(dir).listSync(recursive: true)) {
+    if (entity is File) {
+      out[entity.uri.pathSegments.last] = entity.path;
+    }
+  }
+  return out;
+}
+
+/// Reads a raw little-endian float32 PCM dump (no header, as written by
+/// `numpy.ndarray.tofile`) into a [Float32List]. Copies into a fresh 0-offset
+/// buffer first — `File.readAsBytesSync`'s result is not guaranteed to start
+/// at a 4-byte-aligned buffer offset — mirroring `npy_reader.dart`'s
+/// `_copyToAlignedBuffer` (that helper is private to its own library, so
+/// this is a small local re-implementation, not a duplicate export).
+Float32List _readRawF32(String path) {
+  final bytes = File(path).readAsBytesSync();
+  return Float32List.view(Uint8List.fromList(bytes).buffer);
+}
+
+/// Pearson correlation coefficient between [a] and [b] (equal length).
+double _pearsonCorr(Float32List a, Float32List b) {
+  final n = a.length;
+  var sumA = 0.0, sumB = 0.0;
+  for (var i = 0; i < n; i++) {
+    sumA += a[i];
+    sumB += b[i];
+  }
+  final meanA = sumA / n, meanB = sumB / n;
+  var numerator = 0.0, denomA = 0.0, denomB = 0.0;
+  for (var i = 0; i < n; i++) {
+    final da = a[i] - meanA, db = b[i] - meanB;
+    numerator += da * db;
+    denomA += da * da;
+    denomB += db * db;
+  }
+  return numerator / math.sqrt(denomA * denomB);
+}
+
+/// Largest absolute per-sample difference between [a] and [b] (equal
+/// length).
+double _maxAbsDiff(Float32List a, Float32List b) {
+  var m = 0.0;
+  for (var i = 0; i < a.length; i++) {
+    final d = (a[i] - b[i]).abs();
+    if (d > m) m = d;
+  }
+  return m;
+}
+
+void main() {
+  final modelDir = _modelDir();
+
+  test('Qwen3TtsCore.decodeCodes: PCM matches the PyTorch golden '
+      '(waveform_f32.bin)', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final artifactPaths = _scanArtifactPaths(modelDir);
+
+    // Golden fixtures — committed, always present (no skip-guard needed).
+    final framesGolden =
+        jsonDecode(
+              File('test/golden/qwen3/frames.json').readAsStringSync(),
+            )['frames']
+            as List;
+    final frames = framesGolden
+        .map((row) => (row as List).cast<int>())
+        .toList(growable: false);
+    expect(frames.length, 26);
+    expect(frames[0].length, 16);
+
+    final expectedWav = _readRawF32('test/golden/qwen3/waveform_f32.bin');
+    expect(expectedWav.length, 49920); // 26 frames * 1920 upsample.
+
+    // Default `talkerFileName` (int4) — this test never touches the talker
+    // or MTP graphs, only `decodeCodes` (the codec graph, already fp32).
+    final core = await Qwen3TtsCore.load(
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+    );
+    try {
+      final wav = core.decodeCodes(frames);
+
+      final corr = _pearsonCorr(wav, expectedWav);
+      final maxAbsDiff = _maxAbsDiff(wav, expectedWav);
+
+      // ignore: avoid_print
+      print(
+        'QWEN3-CODEC-TEST<<<len=${wav.length} expectedLen=${expectedWav.length} '
+        'corr=$corr maxAbsDiff=$maxAbsDiff>>>',
+      );
+
+      // THE gate: reproduces the PyTorch reference's decoded waveform for
+      // the SAME codes. Observed on-device: corr=1.0, maxAbsDiff=0.0 (both
+      // run the SAME fp32 codec graph on the SAME codes through the SAME
+      // XNNPACK CPU kernels — this is a real bit-exact match, not luck) —
+      // thresholds are tight but leave headroom for harmless cross-run FP
+      // noise (e.g. reduction-order differences under different threading).
+      expect(wav.length, expectedWav.length);
+      expect(corr, greaterThan(0.9999));
+      expect(maxAbsDiff, lessThan(1e-4));
+    } finally {
+      core.dispose();
+    }
+  }, timeout: const Timeout(Duration(minutes: 5)));
+}

From 326ef53c2c6332e2ccb3c6f10bac9d157b5b5498 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 00:26:57 +0500
Subject: [PATCH 14/30] =?UTF-8?q?feat(qwen3):=20end-to-end=20AR=20synthesi?=
 =?UTF-8?q?ze=20(fp32-greedy=20corr=E2=89=881.0=20gate)?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Qwen3TtsCore.synthesize/synthesizePcm16 tie the talker + MTP + codec
into the host-orchestrated text->waveform loop (qwen3_tts_pipeline.py
:173-266). runMtp gains a sampled residual-picking path. Golden gate
(fp32, greedy): corr=1.0, frame agreement=1.0 vs the PyTorch reference.
---
 .../lib/src/qwen3/qwen3_tts_core.dart         | 307 +++++++++++++++++-
 .../test/qwen3/qwen3_synthesize_test.dart     | 237 ++++++++++++++
 2 files changed, 527 insertions(+), 17 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index ff66a84e..cdcc76c9 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -66,6 +66,23 @@
 // many of the window's rows are real (the rest of `buf` is left as
 // zero-padding); only the `window.length`-worth of frames actually fed are
 // kept from each call's output.
+//
+// [Qwen3TtsCore.synthesize] ports `Qwen3TtsPipeline.synthesize`
+// (`qwen3_tts_pipeline.py:173-266`) verbatim — the host-orchestrated,
+// end-to-end AR loop that ties [runPrefill]/[runDecode]/[runMtp]/
+// [decodeCodes] together: tokenize the chat-template-wrapped text
+// (`Qwen2BpeEncoder`), build the prompt embeddings (`Qwen3Prompt.build`),
+// prefill + one initial decode step, then loop — score + pick cb0
+// ([buildSuppress]/[applyCb0Scoring]/[pickGreedy]/[pickSampled], EOS
+// breaks), run the MTP inner loop for the 15 residuals, accumulate the
+// frame, assemble the next step's talker embedding (codec-token embedding
+// of cb0 plus all 15 MTP-residual embeddings plus the next streamed-text/pad
+// row), and decode one more talker step — until EOS or [maxFrames]. This is
+// the culmination correctness gate for the whole pipeline: fp32-greedy
+// waveform correlation ≈ 1.0 vs the PyTorch reference
+// (`qwen3_synthesize_test.dart`). [Qwen3TtsCore.synthesizePcm16] is the same
+// loop, returning int16 LE mono PCM instead of `[-1, 1]` float samples, for
+// the background-isolate worker (a later task).
 
 import 'dart:ffi';
 import 'dart:io' show Platform;
@@ -84,7 +101,9 @@ import 'package:flutter_gemma_litertlm/litert_bindings.dart';
 
 import '../litert/litert_graph.dart';
 import 'qwen2_bpe_encoder.dart';
-import 'qwen3_sampler.dart' show pickGreedy;
+import 'qwen3_prompt.dart';
+import 'qwen3_sampler.dart'
+    show applyCb0Scoring, buildSuppress, pickGreedy, pickSampled;
 import 'qwen3_tables.dart';
 import 'qwen3_talker_layout.dart';
 
@@ -105,6 +124,20 @@ const int _numCodeGroups = 16;
 /// to size the codec's output and crop left-context samples out of it.
 const int _upsampleFactor = 1920;
 
+/// Number of MTP residual codebooks — matches `qwen3_tts_pipeline.py`'s
+/// module-level implicit `15` (the `arange(15)` in [Qwen3TtsCore.synthesize]'s
+/// embed-accumulation step, `qwen3_tts_pipeline.py:250`). Distinct from
+/// [_numCodeGroups] (`16` = cb0 + these 15 residuals).
+const int _mtpResidualGroups = 15;
+
+/// Codec end-of-sequence token id — matches `qwen3_tts_pipeline.py`'s
+/// module-level `_CODEC_EOS = 2150`. Defined privately here (not imported
+/// from `qwen3_sampler.dart`, where an identical private copy backs
+/// [buildSuppress]/[applyCb0Scoring]) — same "each file owns its own frozen
+/// token constants" convention `qwen3_prompt.dart` already follows for its
+/// `_codecPad`/`_codecBos`/etc.
+const int _codecEos = 2150;
+
 int _acceleratorFor(PreferredBackend? backend) {
   switch (backend) {
     case PreferredBackend.gpu:
@@ -259,10 +292,8 @@ class Qwen3TtsCore {
   /// every table the full pipeline needs.
   final Qwen3Tables _tables;
 
-  /// Qwen2 byte-level BPE text encoder — used by the decode loop / a future
-  /// frontend to turn raw text into token ids ahead of `Qwen3Prompt.build`.
-  /// Same "loaded here, consumed later" rationale as [_tables].
-  // ignore: unused_field
+  /// Qwen2 byte-level BPE text encoder — used by [synthesize] to turn raw
+  /// text into token ids ahead of `Qwen3Prompt.build`.
   final Qwen2BpeEncoder _encoder;
 
   /// Each of the talker's 56 KV tensor shapes (`kv_cache_{k,v}_{0..27}`,
@@ -296,6 +327,15 @@ class Qwen3TtsCore {
 
   bool _disposed = false;
 
+  /// The codec [frames] (row = `[cb0, ...residual]`, one per talker AR
+  /// step) generated by the most recent [synthesize]/[synthesizePcm16]
+  /// call — empty until the first call. Exposed for inspection (e.g. the
+  /// golden test's frame-agreement diagnostic against the PyTorch
+  /// reference's `frames.json`); overwritten, not accumulated, on every
+  /// call.
+  List<List<int>> get lastFrames => _lastFrames;
+  List<List<int>> _lastFrames = const [];
+
   /// Output sample rate (Hz) — fixed for this model family.
   int get sampleRate => 24000;
 
@@ -732,26 +772,38 @@ class Qwen3TtsCore {
   /// (`t` ranges `2..15`); group 14 is never looked up here (it's used
   /// later, when the caller assembles the *next* frame's talker embedding —
   /// not by this loop). Head `t - 1` of `output_0` is read (and, when
-  /// `t >= 1`, picked via [pickGreedy]) at every step from `t = 1` to
-  /// `t = 15`, producing the 15 returned codes — this off-by-one is
-  /// faithful to the recipe, not a bug: ported verbatim, not "fixed".
+  /// `t >= 1`, picked) at every step from `t = 1` to `t = 15`, producing the
+  /// 15 returned codes — this off-by-one is faithful to the recipe, not a
+  /// bug: ported verbatim, not "fixed".
   ///
-  /// [greedy] must be `true` — only the golden (`do_sample=False`) path is
-  /// wired so far; a future task can thread [pickSampled] through the same
-  /// loop shape once a sampled decode path is needed.
+  /// [greedy] selects [pickGreedy] (`do_sample=False`, the golden path —
+  /// `qwen3_mtp_test.dart`'s gate) when `true`, else [pickSampled] with
+  /// [topK]/[temperature]/[rng] (`do_sample=True`, ported from
+  /// `qwen3_tts_pipeline.py:377-379`'s `_pick(..., do_sample, top_k,
+  /// temperature, rng)` — the same top-k/temperature knobs are threaded
+  /// through every one of the 15 residual heads, exactly as the recipe
+  /// does). [rng] is required (and only consulted) when `greedy` is `false`.
   ///
   /// Not true public API (see this file's header) — [visibleForTesting] so
   /// `qwen3_mtp_test.dart` can drive it directly, mirroring [runPrefill]/
   /// [runDecode].
   @visibleForTesting
-  List<int> runMtp(Float32List hidden, int cb0, {bool greedy = true}) {
+  List<int> runMtp(
+    Float32List hidden,
+    int cb0, {
+    bool greedy = true,
+    int topK = 50,
+    double temperature = 0.9,
+    math.Random? rng,
+  }) {
     if (_disposed) {
       throw StateError('Qwen3TtsCore is disposed');
     }
-    if (!greedy) {
-      throw UnimplementedError(
-        'Qwen3TtsCore.runMtp: only greedy (do_sample=False) picking is '
-        'wired so far',
+    if (!greedy && rng == null) {
+      throw ArgumentError.value(
+        rng,
+        'rng',
+        'Qwen3TtsCore.runMtp: rng is required when greedy is false',
       );
     }
     if (hidden.length != TalkerLayout.embeddingDim) {
@@ -831,7 +883,16 @@ class Qwen3TtsCore {
           (t - 1) * _mtpResidualVocab,
           t * _mtpResidualVocab,
         );
-        codes.add(pickGreedy(head));
+        codes.add(
+          greedy
+              ? pickGreedy(head)
+              : pickSampled(
+                  head,
+                  topK: topK,
+                  temperature: temperature,
+                  rng: rng!,
+                ),
+        );
       }
     }
 
@@ -941,6 +1002,218 @@ class Qwen3TtsCore {
     return result;
   }
 
+  /// Synthesizes speech for [text] in the voice identified by [speaker].
+  /// Port of `Qwen3TtsPipeline.synthesize` (`qwen3_tts_pipeline.py:173-266`)
+  /// — see this file's header for the full loop shape.
+  ///
+  /// [speaker] is a `[1024]` x-vector identifying the target voice (see
+  /// `Qwen3Prompt.build`'s doc comment). [language] is one of
+  /// `Qwen3Prompt.languageIds`' keys (case-insensitive), or `'auto'`.
+  /// [doSample] selects top-k/temperature sampling ([pickSampled], the
+  /// model default — matches the recipe's `do_sample: bool = True`) when
+  /// `true`, or deterministic greedy argmax ([pickGreedy]) when `false`; the
+  /// golden gate (`qwen3_synthesize_test.dart`) passes `doSample: false` so
+  /// the run is fully reproducible against the PyTorch-derived fixtures
+  /// (greedy decoding reproduces the reference token-for-token). [topK] /
+  /// [temperature] / [repetitionPenalty] are only consulted by the sampled
+  /// path — [repetitionPenalty] scores the cb0 pick only (`applyCb0Scoring`
+  /// over the `history` of previously-picked cb0 tokens), matching the
+  /// recipe's `history` set (`qwen3_tts_pipeline.py:228,234-237`). [seed]
+  /// seeds the `dart:math.Random` [pickSampled]/[runMtp]'s sampled path
+  /// draws from; the greedy path never touches it. [maxFrames] caps the
+  /// number of generated 12.5 Hz frames (512 frames ≈ 41 s of audio).
+  ///
+  /// Returns mono float32 PCM in `[-1, 1]` at [sampleRate]. The frames
+  /// generated by this call are cached in [lastFrames] for inspection.
+  Float32List synthesize(
+    String text, {
+    required Float32List speaker,
+    String language = 'english',
+    bool doSample = true,
+    int topK = 50,
+    double temperature = 0.9,
+    double repetitionPenalty = 1.05,
+    int maxFrames = 512,
+    int? seed,
+  }) {
+    final frames = _synthesizeFrames(
+      text: text,
+      speaker: speaker,
+      language: language,
+      doSample: doSample,
+      topK: topK,
+      temperature: temperature,
+      repetitionPenalty: repetitionPenalty,
+      maxFrames: maxFrames,
+      seed: seed,
+    );
+    _lastFrames = frames;
+    return decodeCodes(frames);
+  }
+
+  /// Same as [synthesize], but returns mono 16-bit PCM (little-endian)
+  /// bytes instead of `[-1, 1]` float samples — for the background-isolate
+  /// worker (a later task) that streams audio to a player expecting int16
+  /// PCM. Every float sample is clamped to `[-1, 1]`, scaled by `32767`,
+  /// and rounded before being written little-endian: `(sample.clamp(-1, 1)
+  /// * 32767).round()`.
+  Uint8List synthesizePcm16(
+    String text, {
+    required Float32List speaker,
+    String language = 'english',
+    bool doSample = true,
+    int topK = 50,
+    double temperature = 0.9,
+    double repetitionPenalty = 1.05,
+    int maxFrames = 512,
+    int? seed,
+  }) {
+    final wav = synthesize(
+      text,
+      speaker: speaker,
+      language: language,
+      doSample: doSample,
+      topK: topK,
+      temperature: temperature,
+      repetitionPenalty: repetitionPenalty,
+      maxFrames: maxFrames,
+      seed: seed,
+    );
+    final bytes = Uint8List(wav.length * 2);
+    final view = ByteData.sublistView(bytes);
+    for (var i = 0; i < wav.length; i++) {
+      final clamped = wav[i].clamp(-1.0, 1.0);
+      view.setInt16(i * 2, (clamped * 32767).round(), Endian.little);
+    }
+    return bytes;
+  }
+
+  /// The end-to-end AR loop shared by [synthesize]/[synthesizePcm16], split
+  /// out so both can call [decodeCodes] on the same `frames` without
+  /// duplicating the loop. Port of `Qwen3TtsPipeline.synthesize`
+  /// (`qwen3_tts_pipeline.py:173-266`, the part before `_decode_codes` at
+  /// `:259`).
+  List<List<int>> _synthesizeFrames({
+    required String text,
+    required Float32List speaker,
+    required String language,
+    required bool doSample,
+    required int topK,
+    required double temperature,
+    required double repetitionPenalty,
+    required int maxFrames,
+    required int? seed,
+  }) {
+    if (_disposed) {
+      throw StateError('Qwen3TtsCore is disposed');
+    }
+    final rng = math.Random(seed);
+
+    // ids = tokenizer.encode(f'<|im_start|>assistant\n{text}<|im_end|>\n
+    // <|im_start|>assistant\n').ids (qwen3_tts_pipeline.py:289-291).
+    final ids = _encoder.encode(
+      '<|im_start|>assistant\n$text<|im_end|>\n<|im_start|>assistant\n',
+    );
+    final prompt = Qwen3Prompt.build(
+      ids: ids,
+      speaker: speaker,
+      language: language,
+      tables: _tables,
+    );
+
+    // kv = _run_prefill(...); pos = prefill.shape[1] - 1; logits, hidden,
+    // kv = _run_decode(kv, prefill[0, -1], pos) (qwen3_tts_pipeline.py:
+    // 216-220).
+    final initialKv = runPrefill(prompt.prefill, prompt.promptLen);
+    var pos = prompt.promptLen - 1;
+    final firstEmbed = Float32List.sublistView(
+      prompt.prefill,
+      pos * TalkerLayout.embeddingDim,
+      prompt.promptLen * TalkerLayout.embeddingDim,
+    );
+    var (cb0Logits, hidden, kv) = runDecode(initialKv, firstEmbed, pos);
+
+    // suppress = ...; qwen3_tts_pipeline.py:223-225.
+    final suppress = buildSuppress();
+    final frames = <List<int>>[];
+    final history = <int>{};
+
+    // while len(frames) < max_frames: ... (qwen3_tts_pipeline.py:230-256).
+    while (frames.length < maxFrames) {
+      // scores = logits + suppress; ... (qwen3_tts_pipeline.py:231-237).
+      // COPY cb0Logits first — applyCb0Scoring mutates its argument in
+      // place (see its doc), and the original decode-step logits must not
+      // be corrupted (nothing else reads them again this iteration, but
+      // mutating shared state that isn't obviously owned by this call is a
+      // footgun even so — the recipe itself never mutates `logits`, only
+      // the freshly-allocated `scores`).
+      final scores = Float32List.fromList(cb0Logits);
+      applyCb0Scoring(
+        scores,
+        suppress: suppress,
+        history: history,
+        repetitionPenalty: repetitionPenalty,
+        // len(frames) < 2: min_new_tokens=2 (qwen3_tts_pipeline.py:232).
+        minNewTokensGuard: frames.length < 2,
+      );
+
+      // cb0 = _pick(scores, do_sample, top_k, temperature, rng); history.
+      // add(cb0) (qwen3_tts_pipeline.py:238-239).
+      final cb0 = doSample
+          ? pickSampled(scores, topK: topK, temperature: temperature, rng: rng)
+          : pickGreedy(scores);
+      history.add(cb0);
+      // if cb0 == _CODEC_EOS: break (qwen3_tts_pipeline.py:240-241).
+      if (cb0 == _codecEos) break;
+
+      // residual = _run_mtp(hidden, cb0, do_sample, top_k, temperature,
+      // rng) (qwen3_tts_pipeline.py:244-245).
+      final residual = runMtp(
+        hidden,
+        cb0,
+        greedy: !doSample,
+        topK: topK,
+        temperature: temperature,
+        rng: rng,
+      );
+      // frames.append([cb0] + residual) (qwen3_tts_pipeline.py:247).
+      frames.add([cb0, ...residual]);
+
+      // embed = codec_emb[cb0] + mtp_emb[arange(15), residual].sum(0)
+      // (qwen3_tts_pipeline.py:249-250) — element-wise add over ALL 15 MTP
+      // residual groups (unlike [runMtp]'s own inner loop, which only ever
+      // embeds groups 0..13 while picking; group 14 is used here, for the
+      // FIRST time, to assemble the NEXT talker step's input).
+      final embed = Float32List(TalkerLayout.embeddingDim);
+      final cb0Row = _tables.codecEmbRow(cb0);
+      for (var k = 0; k < TalkerLayout.embeddingDim; k++) {
+        embed[k] = cb0Row[k];
+      }
+      for (var g = 0; g < _mtpResidualGroups; g++) {
+        final row = _tables.mtpEmbRow(g, residual[g]);
+        for (var k = 0; k < TalkerLayout.embeddingDim; k++) {
+          embed[k] += row[k];
+        }
+      }
+      // step = len(frames) - 1; embed += trailing[step] if step <
+      // len(trailing) else tts_pad (qwen3_tts_pipeline.py:251-252).
+      final step = frames.length - 1;
+      final addend = step < prompt.trailing.length
+          ? prompt.trailing[step]
+          : prompt.ttsPad;
+      for (var k = 0; k < TalkerLayout.embeddingDim; k++) {
+        embed[k] += addend[k];
+      }
+
+      // pos += 1; logits, hidden, kv = _run_decode(kv, embed, pos)
+      // (qwen3_tts_pipeline.py:253-255).
+      pos++;
+      (cb0Logits, hidden, kv) = runDecode(kv, embed, pos);
+    }
+
+    return frames;
+  }
+
   /// Destroys the 3 compiled graphs' handles + the shared environment, and
   /// closes [_tables]' open `text_embedding` file handle. Mirrors
   /// `TtsCore.dispose`.
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
new file mode 100644
index 00000000..980b6dce
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
@@ -0,0 +1,237 @@
+// End-to-end `synthesize` golden gate for `Qwen3TtsCore` — the culmination
+// test for the whole Qwen3-TTS port: text in, waveform out, driving the
+// REAL talker + MTP + codec graphs through the host-orchestrated AR loop
+// (`Qwen3TtsCore.synthesize`, ported verbatim from
+// `Qwen3TtsPipeline.synthesize`, `qwen3_tts_pipeline.py:173-266`).
+//
+// Every prior Qwen3 test isolated one stage of the pipeline against a
+// golden fixture generated by feeding that stage's REAL inputs straight
+// from `frames.json`/`frame0.json` (`qwen3_talker_decode_test.dart`'s
+// frame-0 cb0, `qwen3_mtp_test.dart`'s frame-0 residual,
+// `qwen3_codec_test.dart`'s full-frames-to-waveform). This test instead
+// drives the whole loop itself, end to end, starting only from `text` +
+// `speaker` — if any stage's host-side glue (prompt assembly, cb0 scoring,
+// the MTP inner loop's sampling-vs-greedy branch, the next-embed
+// accumulation over all 15 MTP groups, trailing/pad indexing) is subtly
+// wrong, THIS is the test that catches it, because a per-stage bug
+// compounds across 26 autoregressive frames instead of being isolated to
+// one golden input.
+//
+// ⚠️ Loads `talker_fp32.tflite`, NOT the int4 runtime artifact — same
+// rationale as `qwen3_talker_decode_test.dart`'s file header: the golden
+// fixtures were generated with `talker_file='talker_fp32.tflite'` (int4
+// quantization is not bit-exact vs the PyTorch reference), and this run is
+// greedy (`doSample: false`) so it is fully deterministic against them.
+//
+// PRIMARY gate: waveform Pearson correlation vs `waveform_f32.bin` (the
+// PyTorch reference's decoded audio for the SAME text/speaker/greedy run) —
+// robust to a single early argmax tie or 1-ULP host/XNNPACK rounding
+// difference cascading through the AR loop, which can flip one token yet
+// leave the audio perceptually (and numerically, via the codec's smoothing)
+// identical. SECONDARY (diagnostic, not a hard requirement beyond its own
+// generous threshold): the FRACTION of generated codec frames (each
+// `[cb0, ...15 residuals]`) that exactly match `frames.json`'s reference
+// frames — deliberately not an all-or-nothing check, for the same
+// cascading-tie reason.
+//
+// The model bundle (~1.5 GB talker_int4 + ~1.8 GB talker_fp32 + mtp/codec
+// graphs + tables) is NOT committed to the repo — see
+// `qwen3_prefill_test.dart`'s file header for the same skip-when-absent
+// rationale ([_defaultModelDir]/`QWEN3_MODEL_DIR`).
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:convert';
+import 'dart:io';
+import 'dart:math' as math;
+import 'dart:typed_data';
+
+import 'package:flutter_gemma/core/domain/platform_types.dart'
+    show PreferredBackend;
+import 'package:flutter_gemma_speech/src/qwen3/npy_reader.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_tts_core.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot dir — the local
+/// HuggingFace cache path for `litert-community/Qwen3-TTS-12Hz-0.6B-Base`.
+/// Override with the `QWEN3_MODEL_DIR` environment variable to run against
+/// a different snapshot. Mirrors `qwen3_talker_decode_test.dart`'s identical
+/// helper.
+String _defaultModelDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66';
+}
+
+String _modelDir() =>
+    Platform.environment['QWEN3_MODEL_DIR'] ?? _defaultModelDir();
+
+/// Recursively scans [dir] and returns a basename -> absolute-path map for
+/// every regular file found. Mirrors `qwen3_talker_decode_test.dart`'s
+/// identical helper.
+Map<String, String> _scanArtifactPaths(String dir) {
+  final out = <String, String>{};
+  for (final entity in Directory(dir).listSync(recursive: true)) {
+    if (entity is File) {
+      out[entity.uri.pathSegments.last] = entity.path;
+    }
+  }
+  return out;
+}
+
+/// Reads a raw little-endian float32 PCM dump (no header, as written by
+/// `numpy.ndarray.tofile`) into a [Float32List]. Mirrors
+/// `qwen3_codec_test.dart`'s identical helper (see its doc for the
+/// buffer-alignment rationale).
+Float32List _readRawF32(String path) {
+  final bytes = File(path).readAsBytesSync();
+  return Float32List.view(Uint8List.fromList(bytes).buffer);
+}
+
+/// Pearson correlation coefficient between [a] and [b] (equal length).
+/// Mirrors `qwen3_codec_test.dart`'s identical helper.
+double _pearsonCorr(Float32List a, Float32List b) {
+  final n = a.length;
+  var sumA = 0.0, sumB = 0.0;
+  for (var i = 0; i < n; i++) {
+    sumA += a[i];
+    sumB += b[i];
+  }
+  final meanA = sumA / n, meanB = sumB / n;
+  var numerator = 0.0, denomA = 0.0, denomB = 0.0;
+  for (var i = 0; i < n; i++) {
+    final da = a[i] - meanA, db = b[i] - meanB;
+    numerator += da * db;
+    denomA += da * da;
+    denomB += db * db;
+  }
+  return numerator / math.sqrt(denomA * denomB);
+}
+
+/// Fraction of [expected]'s rows that [actual] reproduces exactly, indexed
+/// position-by-position over `min(actual.length, expected.length)` and
+/// divided by `expected.length` — NOT an all-or-nothing check (see this
+/// file's header): a frame produced after the two sequences have already
+/// diverged is simply not a match, rather than failing the whole assertion.
+/// A shorter [actual] (e.g. an early EOS pick) is penalized by the missing
+/// rows counting as non-matches; a longer [actual] is not penalized further
+/// (the denominator stays [expected]'s length).
+double _frameAgreementFraction(List<List<int>> actual, List<dynamic> expected) {
+  if (expected.isEmpty) return 1.0;
+  final n = math.min(actual.length, expected.length);
+  var matches = 0;
+  for (var t = 0; t < n; t++) {
+    final expectedRow = (expected[t] as List).cast<int>();
+    final actualRow = actual[t];
+    if (actualRow.length != expectedRow.length) continue;
+    var rowMatches = true;
+    for (var k = 0; k < expectedRow.length; k++) {
+      if (actualRow[k] != expectedRow[k]) {
+        rowMatches = false;
+        break;
+      }
+    }
+    if (rowMatches) matches++;
+  }
+  return matches / expected.length;
+}
+
+/// Index of the first frame where [actual] and [expected] disagree, or -1
+/// if every compared frame matches. Diagnostic only — logged, not asserted
+/// on, per this file's header (frame agreement is a fraction, not a gate).
+int _firstDivergentFrame(List<List<int>> actual, List<dynamic> expected) {
+  final n = math.min(actual.length, expected.length);
+  for (var t = 0; t < n; t++) {
+    final expectedRow = (expected[t] as List).cast<int>();
+    final actualRow = actual[t];
+    if (actualRow.length != expectedRow.length) return t;
+    for (var k = 0; k < expectedRow.length; k++) {
+      if (actualRow[k] != expectedRow[k]) return t;
+    }
+  }
+  return -1;
+}
+
+void main() {
+  final modelDir = _modelDir();
+
+  test('Qwen3TtsCore.synthesize: greedy fp32 end-to-end matches the '
+      'PyTorch-derived golden (waveform corr > 0.999)', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final artifactPaths = _scanArtifactPaths(modelDir);
+    if (!artifactPaths.containsKey('talker_fp32.tflite')) {
+      markTestSkipped(
+        'talker_fp32.tflite not found under $modelDir — the golden '
+        'fixtures were generated against the fp32 talker (int4 is not '
+        'bit-exact vs the PyTorch reference) and this test needs it '
+        'present to run.',
+      );
+      return;
+    }
+
+    // Golden fixtures — committed, always present (no skip-guard needed).
+    final meta =
+        jsonDecode(File('test/golden/qwen3/meta.json').readAsStringSync())
+            as Map<String, dynamic>;
+    final text = meta['text'] as String;
+    final speaker = readNpyF32('test/golden/qwen3/voices/demo_speaker.npy');
+    expect(speaker.length, 1024);
+
+    final refFrames =
+        (jsonDecode(
+              File('test/golden/qwen3/frames.json').readAsStringSync(),
+            )['frames']
+            as List);
+    final refWav = _readRawF32('test/golden/qwen3/waveform_f32.bin');
+    expect(refFrames.length, meta['num_frames']);
+    expect(refWav.length, refFrames.length * 1920);
+
+    final core = await Qwen3TtsCore.load(
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+      talkerFileName: 'talker_fp32.tflite',
+    );
+    try {
+      final started = DateTime.now();
+      final wav = core.synthesize(
+        text,
+        speaker: speaker,
+        language: meta['language'] as String,
+        doSample: false, // Golden gate: greedy, deterministic.
+      );
+      final elapsed = DateTime.now().difference(started);
+
+      final corr = _pearsonCorr(wav, refWav);
+      final agreement = _frameAgreementFraction(core.lastFrames, refFrames);
+      final firstDivergent = _firstDivergentFrame(core.lastFrames, refFrames);
+
+      // ignore: avoid_print
+      print(
+        'QWEN3-SYNTHESIZE-TEST<<<text="$text" wavLen=${wav.length} '
+        'refWavLen=${refWav.length} corr=$corr '
+        'frames=${core.lastFrames.length} refFrames=${refFrames.length} '
+        'agreement=$agreement firstDivergentFrame=$firstDivergent '
+        'elapsedMs=${elapsed.inMilliseconds}>>>',
+      );
+
+      // PRIMARY gate: waveform correlation — see this file's header for
+      // why this (not exact frame equality) is the real gate.
+      expect(wav.length, closeTo(refWav.length, 1920)); // +/- one frame.
+      expect(corr, greaterThan(0.999));
+
+      // SECONDARY: frame agreement as a fraction, logged above regardless
+      // of outcome so a divergence is visible without re-running.
+      expect(agreement, greaterThan(0.98));
+    } finally {
+      core.dispose();
+    }
+  }, timeout: const Timeout(Duration(minutes: 30)));
+}

From 6e25f2ddfb9614aa1ba901b6d05dee8ed90515a9 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 00:50:45 +0500
Subject: [PATCH 15/30] feat(qwen3): core TtsModelType.qwen3 + bundle manifest
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Adds the qwen3 enum value + its 9-file install manifest (plain
basenames matching Qwen3TtsCore.load's artifactPaths keys exactly),
extends the TTS size-floor to .npy/.npz, and teaches
TtsInstallationBuilder to fetch the 4 table files + demo voice from
their tables/voices subdirectory on HF without letting that leak into
the installed identity (I5: plain-basename manifest, not nested or
double-underscore-flattened — see tts_model_spec.dart doc comments).
---
 .../core/api/tts_installation_builder.dart    |  11 +-
 .../types/tts_model_spec.dart                 |  70 +++++++-
 .../test/core/tts_model_spec_test.dart        | 155 ++++++++++++++++++
 3 files changed, 227 insertions(+), 9 deletions(-)

diff --git a/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart b/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
index fd99e4a5..5cd726b2 100644
--- a/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
+++ b/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
@@ -87,8 +87,15 @@ class TtsInstallationBuilder {
       );
     }
 
-    String joinUrl(String base, String fn) =>
-        base.endsWith('/') ? '$base$fn' : '$base/$fn';
+    // Most bundle members are fetched from `baseUrl/<plain filename>`, but a
+    // few (e.g. qwen3's embedding tables + demo voice) live under a
+    // subdirectory on the origin server even though their INSTALLED
+    // identity is the plain basename — see
+    // `TtsModelTypeManifest.urlSuffixFor`'s doc for why that split is safe.
+    String joinUrl(String base, String fn) {
+      final suffix = ttsModelType.urlSuffixFor(fn);
+      return base.endsWith('/') ? '$base$suffix' : '$base/$suffix';
+    }
 
     final spec = TtsModelSpec.fromManifest(
       name: _name ?? ttsModelType.name,
diff --git a/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart b/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart
index 88a5259b..034d7761 100644
--- a/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart
+++ b/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart
@@ -1,9 +1,10 @@
 part of '../model_specs.dart';
 
 /// Text-to-speech model families supported by the pluggable TTS backends.
-/// Only [matcha] has a shipped [TtsModelProfile]/pipeline (`flutter_gemma_speech`);
-/// [kokoro]/[supertonic] are documented follow-ons (fail-loud until wired).
-enum TtsModelType { matcha, supertonic, kokoro }
+/// [matcha] and [qwen3] have shipped [TtsModelProfile]/pipelines
+/// (`flutter_gemma_speech`); [kokoro]/[supertonic] are documented follow-ons
+/// (fail-loud until wired).
+enum TtsModelType { matcha, supertonic, kokoro, qwen3 }
 
 /// The filenames a given TTS model needs, installed together as a bundle from
 /// one source. Fail-loud for unwired families.
@@ -19,10 +20,62 @@ extension TtsModelTypeManifest on TtsModelType {
       'config.json',
       'g2p_meta.json',
     ],
+    // litert-community/Qwen3-TTS-12Hz-0.6B-Base on HuggingFace. Entries are
+    // PLAIN basenames — deliberately NOT the `tables/`/`voices/` subpaths
+    // those 5 files actually live under on the HF repo (see [urlSuffixFor]).
+    // This is load-bearing, not a simplification: [TtsBundleFile.fromSource]
+    // derives a file's installed identity (== [TtsBundleFile.prefsKey] ==
+    // the `artifactPaths` key `Qwen3TtsCore.load`/`Qwen3Tables.load` read)
+    // from the LAST path segment of its source, and
+    // `MobileModelManager._restoreActiveTtsModel` independently re-derives
+    // the SAME namespaced on-disk path directly from this raw manifest
+    // string (`FileNameUtils.namespaced(modelId, fn)`) — if an entry here
+    // contained a `/`, those two derivations would silently diverge (fresh
+    // install writes the URL-extracted flat basename; restore would look for
+    // a namespaced path with an embedded subdirectory) and active-model
+    // restore would fail to find the file after every relaunch. No
+    // `config.json` — Qwen3's sampling params (top_k=50, temperature=0.9,
+    // repetition_penalty=1.05, max_frames=512) are recipe constants threaded
+    // as Dart defaults, not model-file-driven.
+    TtsModelType.qwen3 => const [
+      'talker_int4.tflite',
+      'mtp_fp32.tflite',
+      'codec_decoder_fp32.tflite',
+      'tokenizer.json',
+      'text_embedding_fp16.npy',
+      'text_projection_fp32.npz',
+      'codec_embedding_fp32.npy',
+      'mtp_embeddings_fp16.npy',
+      'demo_speaker.npy',
+    ],
     _ => throw UnimplementedError(
-      'TTS manifest for $this is a follow-on (only matcha is wired)',
+      'TTS manifest for $this is a follow-on (only matcha/qwen3 are wired)',
     ),
   };
+
+  /// The URL path segment a bundle member is actually fetched from under the
+  /// model's `resolve/main/` base — usually just [plainFilename] itself, but
+  /// [TtsModelType.qwen3]'s 4 embedding-table members and its 1 demo-voice
+  /// member live in the HF repo's `tables/`/`voices/` subdirectories even
+  /// though (per [manifest]'s doc) their INSTALLED identity is the bare
+  /// basename. Safe to add a directory prefix here: it changes ONLY where
+  /// [TtsInstallationBuilder] fetches the bytes from, never the on-disk
+  /// filename/prefsKey (which [TtsBundleFile.fromSource] derives from the
+  /// LAST path segment of the resulting URL — a `tables/` prefix earlier in
+  /// the path is dropped exactly like the plain-basename manifest entry
+  /// intends). A no-op (identity) for every other [TtsModelType].
+  String urlSuffixFor(String plainFilename) {
+    if (this != TtsModelType.qwen3) return plainFilename;
+    const tableFiles = {
+      'text_embedding_fp16.npy',
+      'text_projection_fp32.npz',
+      'codec_embedding_fp32.npy',
+      'mtp_embeddings_fp16.npy',
+    };
+    if (tableFiles.contains(plainFilename)) return 'tables/$plainFilename';
+    if (plainFilename == 'demo_speaker.npy') return 'voices/$plainFilename';
+    return plainFilename;
+  }
 }
 
 /// One file of a TTS model bundle. [filename] is namespaced by the owning
@@ -88,9 +141,12 @@ class TtsBundleFile extends ModelFile {
   @override
   int? get minimumSizeBytes {
     // TTS bundles legitimately include small aux files (emb.bin ~137 KB,
-    // config/meta json, gzipped dict). Give those a 1 KB floor; the large
-    // .tflite graphs return null and keep the validator's 1 MB default.
-    const smallBundleExts = {'.bin', '.gz', '.json'};
+    // config/meta json, gzipped dict, qwen3's demo_speaker.npy x-vector
+    // ~4 KB). Give those a 1 KB floor; the large .tflite graphs return null
+    // and keep the validator's 1 MB default. .npy/.npz also cover qwen3's
+    // larger embedding tables — a looser floor for those is accepted so the
+    // one genuinely small .npy (demo_speaker.npy) isn't rejected.
+    const smallBundleExts = {'.bin', '.gz', '.json', '.npy', '.npz'};
     return smallBundleExts.contains(extension) ? 1024 : null;
   }
 }
diff --git a/packages/flutter_gemma/test/core/tts_model_spec_test.dart b/packages/flutter_gemma/test/core/tts_model_spec_test.dart
index 2ac700ee..41ca011e 100644
--- a/packages/flutter_gemma/test/core/tts_model_spec_test.dart
+++ b/packages/flutter_gemma/test/core/tts_model_spec_test.dart
@@ -28,6 +28,130 @@ void main() {
     );
   });
 
+  test('qwen3 manifest lists its 9 runtime files (plain basenames — no '
+      'config.json, no tables/voices subdirectory in the manifest itself; '
+      'see urlSuffixFor for the network-fetch mapping)', () {
+    final m = TtsModelType.qwen3.manifest;
+    expect(m, contains('talker_int4.tflite'));
+    expect(m, contains('mtp_fp32.tflite'));
+    expect(m, contains('codec_decoder_fp32.tflite'));
+    expect(m, contains('tokenizer.json'));
+    expect(m, contains('text_embedding_fp16.npy'));
+    expect(m, contains('text_projection_fp32.npz'));
+    expect(m, contains('codec_embedding_fp32.npy'));
+    expect(m, contains('mtp_embeddings_fp16.npy'));
+    expect(m, contains('demo_speaker.npy'));
+    expect(m.length, 9);
+    expect(m, isNot(contains('config.json')));
+    for (final fn in m) {
+      expect(fn.contains('/'), isFalse, reason: '$fn must be a plain basename');
+    }
+  });
+
+  test(
+    'qwen3 urlSuffixFor maps the 4 embedding tables + demo voice to their '
+    'HF tables/voices subdirectory; the other 4 members map to themselves',
+    () {
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('text_embedding_fp16.npy'),
+        'tables/text_embedding_fp16.npy',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('text_projection_fp32.npz'),
+        'tables/text_projection_fp32.npz',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('codec_embedding_fp32.npy'),
+        'tables/codec_embedding_fp32.npy',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('mtp_embeddings_fp16.npy'),
+        'tables/mtp_embeddings_fp16.npy',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('demo_speaker.npy'),
+        'voices/demo_speaker.npy',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('talker_int4.tflite'),
+        'talker_int4.tflite',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('mtp_fp32.tflite'),
+        'mtp_fp32.tflite',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('codec_decoder_fp32.tflite'),
+        'codec_decoder_fp32.tflite',
+      );
+      expect(
+        TtsModelType.qwen3.urlSuffixFor('tokenizer.json'),
+        'tokenizer.json',
+      );
+    },
+  );
+
+  test('urlSuffixFor is the identity mapping for every other TtsModelType '
+      '(matcha has no subdirectories)', () {
+    for (final fn in TtsModelType.matcha.manifest) {
+      expect(TtsModelType.matcha.urlSuffixFor(fn), fn);
+    }
+  });
+
+  test('flat<->url round trip (I5): building a qwen3 spec with sourceFor '
+      'wired through urlSuffixFor (as TtsInstallationBuilder does) produces '
+      'TtsBundleFiles whose prefsKey set is EXACTLY the manifest — the '
+      "tables/voices subdirectory in the fetch URL never leaks into the "
+      'installed identity / artifactPaths key Qwen3TtsCore.load reads', () {
+    final spec = TtsModelSpec.fromManifest(
+      name: 'qwen3',
+      ttsModelType: TtsModelType.qwen3,
+      sourceFor: (fn) => ModelSource.network(
+        'https://huggingface.co/litert-community/'
+        'Qwen3-TTS-12Hz-0.6B-Base/resolve/main/'
+        '${TtsModelType.qwen3.urlSuffixFor(fn)}',
+      ),
+    );
+    final prefsKeys = spec.files.map((f) => f.prefsKey).toSet();
+    expect(prefsKeys, TtsModelType.qwen3.manifest.toSet());
+    expect(spec.files.length, 9);
+
+    // The 4 table files + demo voice namespace to a flat qwen3__<basename>
+    // filename — no embedded subdirectory made it through.
+    final tablesFile = spec.files.firstWhere(
+      (f) => f.prefsKey == 'text_embedding_fp16.npy',
+    );
+    expect(tablesFile.filename, 'qwen3__text_embedding_fp16.npy');
+    final voiceFile = spec.files.firstWhere(
+      (f) => f.prefsKey == 'demo_speaker.npy',
+    );
+    expect(voiceFile.filename, 'qwen3__demo_speaker.npy');
+  });
+
+  test('qwen3 minimumSizeBytes: .npy/.npz bundle members (incl. the small '
+      'demo_speaker.npy voice) get the 1 KB floor; .tflite graphs keep the '
+      'validator default (null)', () {
+    final spec = TtsModelSpec.fromManifest(
+      name: 'qwen3',
+      ttsModelType: TtsModelType.qwen3,
+      sourceFor: (fn) => ModelSource.network(
+        'https://x/${TtsModelType.qwen3.urlSuffixFor(fn)}',
+      ),
+    );
+    final byName = {for (final f in spec.files) f.prefsKey: f};
+
+    expect(byName['text_embedding_fp16.npy']!.minimumSizeBytes, 1024);
+    expect(byName['text_projection_fp32.npz']!.minimumSizeBytes, 1024);
+    expect(byName['codec_embedding_fp32.npy']!.minimumSizeBytes, 1024);
+    expect(byName['mtp_embeddings_fp16.npy']!.minimumSizeBytes, 1024);
+    expect(byName['demo_speaker.npy']!.minimumSizeBytes, 1024);
+    expect(byName['tokenizer.json']!.minimumSizeBytes, 1024);
+
+    expect(byName['talker_int4.tflite']!.minimumSizeBytes, isNull);
+    expect(byName['mtp_fp32.tflite']!.minimumSizeBytes, isNull);
+    expect(byName['codec_decoder_fp32.tflite']!.minimumSizeBytes, isNull);
+  });
+
   test(
     'fromManifest builds one source+file per manifest entry; type is tts',
     () {
@@ -115,6 +239,37 @@ void main() {
     expect(configFile.prefsKey, 'config.json');
   });
 
+  test('qwen3 restore-safe: MobileModelManager._restoreActiveTtsModel derives '
+      'namespaced paths DIRECTLY from the raw manifest string (no URL '
+      'involved) — this must land on the SAME namespaced filename a fresh '
+      'network install produces via urlSuffixFor, for every one of the 4 '
+      'table + 1 voice member whose fetch URL has a tables/voices '
+      'subdirectory the plain manifest entry does not', () {
+    final installed = TtsModelSpec.fromManifest(
+      name: 'qwen3',
+      ttsModelType: TtsModelType.qwen3,
+      sourceFor: (fn) => ModelSource.network(
+        'https://x/${TtsModelType.qwen3.urlSuffixFor(fn)}',
+      ),
+    );
+    for (final fn in TtsModelType.qwen3.manifest) {
+      // Mirrors _restoreActiveTtsModel's `FileNameUtils.namespaced(modelId,
+      // fn)` — computed from the raw manifest entry, independent of any URL.
+      final restoreDerived = FileNameUtils.namespaced('qwen3', fn);
+      final installDerived = installed.files
+          .firstWhere((f) => f.prefsKey == fn)
+          .filename;
+      expect(
+        restoreDerived,
+        installDerived,
+        reason:
+            'restore would look for "$restoreDerived" but install wrote '
+            '"$installDerived" — active TTS model restore would silently '
+            'fail to find "$fn" after relaunch',
+      );
+    }
+  });
+
   test('two different ttsModelTypes namespace the same generic basename '
       'distinctly (the latent config.json/emb.bin collision)', () {
     final matcha = TtsModelSpec.fromManifest(

From 8a2891b967c1e02a2c15f42dbc0723ec6d4af91d Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 01:01:36 +0500
Subject: [PATCH 16/30] test(qwen3): builder-level regression test for the
 joinUrl/urlSuffixFor wiring

Review fix (round 1): the prior "flat<->url round trip" test in
tts_model_spec_test.dart re-implemented the urlSuffixFor wiring in its
own sourceFor closure instead of exercising TtsInstallationBuilder
.install() itself, so a revert of the joinUrl change would pass every
test while fresh qwen3 network installs 404 on the 5 subdir-hosted
files. Adds a builder-level test (mocked ServiceRegistry + a recording
DownloadService, mirroring install_identity_namespacing_test.dart's
pattern) that calls install() for TtsModelType.qwen3 and asserts the
resulting NetworkSource URLs carry the tables/voices subdirectory
while every prefsKey stays a plain basename. Verified this test fails
if the joinUrl wiring is reverted, then confirmed it passes against
the real code. Also adds a small matcha spot-check.
---
 .../core/tts_installation_builder_test.dart   | 210 +++++++++++++++++-
 1 file changed, 209 insertions(+), 1 deletion(-)

diff --git a/packages/flutter_gemma/test/core/tts_installation_builder_test.dart b/packages/flutter_gemma/test/core/tts_installation_builder_test.dart
index ca0abc9b..a1e71557 100644
--- a/packages/flutter_gemma/test/core/tts_installation_builder_test.dart
+++ b/packages/flutter_gemma/test/core/tts_installation_builder_test.dart
@@ -1,10 +1,42 @@
+import 'dart:io';
+import 'dart:typed_data';
+
+import 'package:flutter_gemma/core/di/service_registry.dart';
+import 'package:flutter_gemma/core/services/download_service.dart';
 import 'package:flutter_gemma/flutter_gemma.dart';
 import 'package:flutter_test/flutter_test.dart';
+import 'package:path_provider_platform_interface/path_provider_platform_interface.dart';
 import 'package:shared_preferences/shared_preferences.dart';
 
 void main() {
   TestWidgetsFlutterBinding.ensureInitialized();
-  setUp(() => SharedPreferences.setMockInitialValues({}));
+
+  late Directory fakeDocuments;
+  late Directory fakeAppSupport;
+
+  setUp(() async {
+    SharedPreferences.setMockInitialValues({});
+    fakeDocuments = await Directory.systemTemp.createTemp(
+      'flutter_gemma_docs_',
+    );
+    fakeAppSupport = await Directory.systemTemp.createTemp(
+      'flutter_gemma_appsupport_',
+    );
+    PathProviderPlatform.instance = _FixedPathProviderPlatform(
+      documentsPath: fakeDocuments.path,
+      appSupportPath: fakeAppSupport.path,
+    );
+    ServiceRegistry.reset();
+  });
+
+  tearDown(() async {
+    ServiceRegistry.reset();
+    for (final dir in [fakeDocuments, fakeAppSupport]) {
+      if (await dir.exists()) {
+        await dir.delete(recursive: true);
+      }
+    }
+  });
 
   test('TtsModelType is exported from the public barrel', () {
     // Compile-level check that users can reference the type + install API.
@@ -25,4 +57,180 @@ void main() {
   test('getActiveTts throws with no active model', () {
     expect(FlutterGemma.getActiveTts(), throwsA(isA<StateError>()));
   });
+
+  test(
+    'qwen3: install() wires the 4 embedding tables + demo voice through '
+    'urlSuffixFor (the real joinUrl path, not a re-derivation) — their '
+    'NetworkSource URL carries the HF tables/voices subdirectory, but the '
+    'installed identity (TtsBundleFile.prefsKey, via TtsModelSpec.files) '
+    'stays the PLAIN basename. Exercises TtsInstallationBuilder.install() '
+    'end to end, so reverting the joinUrl/urlSuffixFor wiring in '
+    'tts_installation_builder.dart fails this test (unlike the '
+    'tts_model_spec_test.dart round-trip test, which builds sourceFor '
+    'itself and would keep passing even if the builder wiring regressed).',
+    () async {
+      final fixtureDownload = _RecordingDownloadService(
+        Uint8List.fromList(List.filled(2048, 7)),
+      );
+      await ServiceRegistry.initialize(downloadService: fixtureDownload);
+
+      final installation = await FlutterGemma.installTts()
+          .fromNetwork(
+            'https://huggingface.co/litert-community/'
+            'Qwen3-TTS-12Hz-0.6B-Base/resolve/main/',
+          )
+          .ofType(TtsModelType.qwen3)
+          .install();
+
+      final spec = installation.spec;
+      expect(spec.sources.length, 9);
+      expect(spec.files.length, 9);
+
+      // Map prefsKey (the installed identity / artifactPaths key) -> the
+      // NetworkSource actually built by install()'s sourceFor/joinUrl.
+      final sourceByKey = <String, ModelSource>{
+        for (var i = 0; i < spec.files.length; i++)
+          spec.files[i].prefsKey: spec.sources[i],
+      };
+
+      String urlOf(String prefsKey) {
+        final source = sourceByKey[prefsKey];
+        expect(source, isNotNull, reason: 'no bundle file for "$prefsKey"');
+        expect(source, isA<NetworkSource>());
+        return (source as NetworkSource).url;
+      }
+
+      // Fetch URL carries the HF subdirectory...
+      expect(
+        urlOf('text_embedding_fp16.npy'),
+        endsWith('/tables/text_embedding_fp16.npy'),
+      );
+      expect(
+        urlOf('text_projection_fp32.npz'),
+        endsWith('/tables/text_projection_fp32.npz'),
+      );
+      expect(
+        urlOf('codec_embedding_fp32.npy'),
+        endsWith('/tables/codec_embedding_fp32.npy'),
+      );
+      expect(
+        urlOf('mtp_embeddings_fp16.npy'),
+        endsWith('/tables/mtp_embeddings_fp16.npy'),
+      );
+      expect(urlOf('demo_speaker.npy'), endsWith('/voices/demo_speaker.npy'));
+
+      // ...but the installed identity (the map's KEYS, i.e. every
+      // TtsBundleFile.prefsKey) is the plain basename — no leaked
+      // tables/voices subdirectory anywhere in artifactPaths.
+      for (final key in sourceByKey.keys) {
+        expect(
+          key.contains('/'),
+          isFalse,
+          reason: '"$key" must be a plain basename (no subdirectory)',
+        );
+      }
+      expect(sourceByKey.containsKey('text_embedding_fp16.npy'), isTrue);
+      expect(sourceByKey.containsKey('demo_speaker.npy'), isTrue);
+
+      // Top-level members (no HF subdirectory) fetch from the plain name.
+      expect(urlOf('talker_int4.tflite'), endsWith('/talker_int4.tflite'));
+      expect(urlOf('tokenizer.json'), endsWith('/tokenizer.json'));
+
+      // Every requested download went through the real URL built above —
+      // proves the recorded urls above are what install() actually fetched
+      // from, not just what the returned spec claims.
+      expect(
+        fixtureDownload.requestedUrls.any(
+          (u) => u.endsWith('/tables/text_embedding_fp16.npy'),
+        ),
+        isTrue,
+      );
+      expect(
+        fixtureDownload.requestedUrls.any(
+          (u) => u.endsWith('/voices/demo_speaker.npy'),
+        ),
+        isTrue,
+      );
+    },
+  );
+
+  test(
+    'matcha spot-check: install() keeps identity URLs for its top-level-only '
+    'manifest (no subdirectory, urlSuffixFor is a no-op for non-qwen3 types)',
+    () async {
+      final fixtureDownload = _RecordingDownloadService(
+        Uint8List.fromList(List.filled(2048, 3)),
+      );
+      await ServiceRegistry.initialize(downloadService: fixtureDownload);
+
+      final installation = await FlutterGemma.installTts()
+          .fromNetwork('https://example.com/matcha/')
+          .ofType(TtsModelType.matcha)
+          .install();
+
+      final spec = installation.spec;
+      final sourceByKey = <String, ModelSource>{
+        for (var i = 0; i < spec.files.length; i++)
+          spec.files[i].prefsKey: spec.sources[i],
+      };
+      final configUrl = (sourceByKey['config.json']! as NetworkSource).url;
+      expect(configUrl, 'https://example.com/matcha/config.json');
+    },
+  );
+}
+
+/// PathProviderPlatform stub mirroring
+/// test/core/api/install_identity_namespacing_test.dart's fixture.
+class _FixedPathProviderPlatform extends PathProviderPlatform {
+  final String documentsPath;
+  final String appSupportPath;
+
+  _FixedPathProviderPlatform({
+    required this.documentsPath,
+    required this.appSupportPath,
+  });
+
+  @override
+  Future<String?> getApplicationDocumentsPath() async => documentsPath;
+
+  @override
+  Future<String?> getApplicationSupportPath() async => appSupportPath;
+
+  @override
+  Future<String?> getTemporaryPath() async => Directory.systemTemp.path;
+}
+
+/// A real (non-mock) DownloadService fake that writes [bytes] to whatever
+/// targetPath it's asked to download to, instead of making a real HTTP
+/// request — and records every requested URL so a test can assert exactly
+/// what install() fetched from, not just what the returned spec claims.
+class _RecordingDownloadService implements DownloadService {
+  final Uint8List bytes;
+  final List<String> requestedUrls = [];
+  _RecordingDownloadService(this.bytes);
+
+  @override
+  Future<void> download(
+    String url,
+    String targetPath, {
+    String? token,
+    CancelToken? cancelToken,
+  }) async {
+    requestedUrls.add(url);
+    await File(targetPath).writeAsBytes(bytes);
+  }
+
+  @override
+  Stream<int> downloadWithProgress(
+    String url,
+    String targetPath, {
+    String? token,
+    int maxRetries = 10,
+    CancelToken? cancelToken,
+    bool? foreground,
+  }) async* {
+    requestedUrls.add(url);
+    await File(targetPath).writeAsBytes(bytes);
+    yield 100;
+  }
 }

From 5c884b3e238477bff3411424f428d1f98db56aa8 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 01:13:53 +0500
Subject: [PATCH 17/30] feat(qwen3): TtsModelProfile.qwen3 + pipeline kind

Add TtsPipelineKind.qwen3ArCodec and const TtsModelProfile.qwen3()
(subwordTokens + no G2P; pipeline is the only load-bearing field,
Qwen3TtsCore hardcodes its own manifest basenames). forType(qwen3)
resolves it; supertonic/kokoro still fail-loud. Add fail-loud arms
in TtsTextFrontend.load and clarify TtsCore.load's guard message so
qwen3ArCodec never silently runs the Matcha pipeline.
---
 .../lib/src/litert/tts_core.dart              | 12 +++--
 .../lib/src/model/tts_model_profile.dart      | 45 +++++++++++++++++--
 .../lib/src/tts/tts_text_frontend.dart        | 10 +++++
 .../test/qwen3/qwen3_profile_test.dart        | 44 ++++++++++++++++++
 .../test/tts_model_profile_test.dart          |  2 +-
 5 files changed, 104 insertions(+), 9 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_profile_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart b/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
index 574e3c22..d91bff6e 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
@@ -29,8 +29,11 @@
 // graphs; this file delegates to it and stays behavior-identical.
 //
 // Generic over [TtsModelProfile] — only `TtsPipelineKind.matchaCfm` is
-// implemented; kokoro/supertonic profiles are documented follow-ons. The
-// `dp_g2p` graph IS loaded here (4th compiled graph) and exposed via
+// implemented. `qwen3ArCodec` profiles are dispatched to `Qwen3TtsCore` by
+// the worker and fail-loud if they ever reach [load]'s guard instead;
+// kokoro/supertonic profiles are documented follow-ons with no wired
+// pipeline kind at all. The `dp_g2p` graph IS loaded here (4th compiled
+// graph) and exposed via
 // `TtsCore.neuralG2p` — it's the neural OOV fallback used when a word is
 // missing from the dictionary; the dictionary-only path stays the golden
 // path via `TtsTextFrontend` (Task 2.2).
@@ -209,8 +212,9 @@ class TtsCore {
   }) async {
     if (profile.pipeline != TtsPipelineKind.matchaCfm) {
       throw UnimplementedError(
-        'TtsCore: only TtsPipelineKind.matchaCfm is implemented '
-        '(kokoro/supertonic are follow-ons; see the design spec).',
+        'TtsCore: only TtsPipelineKind.matchaCfm is implemented here '
+        '(qwen3ArCodec is handled by Qwen3TtsCore, not the Matcha TtsCore '
+        'path; kokoro/supertonic have no wired pipeline kind yet).',
       );
     }
 
diff --git a/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart b/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart
index 906b59ab..0f36e2ba 100644
--- a/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart
+++ b/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart
@@ -20,6 +20,15 @@ enum TtsPipelineKind {
   /// Glow-TTS length regulator (256→512 frames) → N-step Euler CFM decoder →
   /// HiFi-GAN vocoder. Numeric params come from the bundle's config.json.
   matchaCfm,
+
+  /// Qwen3-TTS: autoregressive codec-token LM (talker, prefill+decode over a
+  /// threaded KV cache) → 15-step MTP residual-codebook inner loop →
+  /// windowed codec decoder → 24 kHz PCM. Dispatched to `Qwen3TtsCore`
+  /// (`flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart`) by the
+  /// background worker — this pipeline kind never reaches the Matcha-only
+  /// `TtsCore`/`TtsTextFrontend` path, which fail-loud on it instead of
+  /// silently running Matcha behavior against a Qwen3 bundle.
+  qwen3ArCodec,
 }
 
 /// How text becomes the model's encoder input.
@@ -49,6 +58,33 @@ class TtsModelProfile {
       g2p = G2pStrategy.dictionaryPlusNeural,
       locale = 'en_us';
 
+  /// Qwen3-TTS bundle: unlike [matcha], `Qwen3TtsCore.load` does NOT read
+  /// these file-role fields — it hardcodes its own manifest basenames
+  /// (`talker_int4.tflite`, `mtp_fp32.tflite`, `codec_decoder_fp32.tflite`,
+  /// `tokenizer.json`, plus the 4 `Qwen3Tables` npy/npz basenames; see
+  /// `TtsModelTypeManifest.manifest` for `TtsModelType.qwen3` in
+  /// `flutter_gemma`'s `model_specs.dart`). So for this profile [pipeline]
+  /// is the ONLY load-bearing field; the file-role fields below are left
+  /// `''` (non-nullable, so empty stands in for "not used") rather than
+  /// mapped onto Qwen3 basenames — none of Matcha's roles (a single
+  /// text-encoder/decoder/vocoder trio) has a clean 1:1 equivalent in the
+  /// AR-codec pipeline's talker/MTP/codec-decoder split, and inventing one
+  /// here would be misleading. Qwen3 does its own byte-level BPE
+  /// tokenization (`Qwen2BpeEncoder` over `tokenizer.json`), not G2P.
+  const TtsModelProfile.qwen3()
+    : pipeline = TtsPipelineKind.qwen3ArCodec,
+      textEncoderFile = '',
+      decoderFile = '',
+      vocoderFile = '',
+      g2pFile = '',
+      g2pMetaFile = '',
+      configFile = '',
+      dictFile = '',
+      embeddingFile = '',
+      representation = TextRepresentation.subwordTokens,
+      g2p = G2pStrategy.none,
+      locale = 'en_us';
+
   /// Which end-to-end synthesis pipeline this profile drives.
   final TtsPipelineKind pipeline;
 
@@ -89,13 +125,14 @@ class TtsModelProfile {
   /// Selects the `TtsTextNormalizer` (Task 4); matcha → `'en_us'`.
   final String locale;
 
-  /// Resolve the runtime profile for [t]. Only [TtsModelType.matcha] is
-  /// wired; kokoro/supertonic are follow-ons and throw (fail-loud — never
-  /// run text through the wrong pipeline).
+  /// Resolve the runtime profile for [t]. Only [TtsModelType.matcha] and
+  /// [TtsModelType.qwen3] are wired; kokoro/supertonic are follow-ons and
+  /// throw (fail-loud — never run text through the wrong pipeline).
   factory TtsModelProfile.forType(TtsModelType t) => switch (t) {
     TtsModelType.matcha => const TtsModelProfile.matcha(),
+    TtsModelType.qwen3 => const TtsModelProfile.qwen3(),
     _ => throw UnimplementedError(
-      'TTS profile for $t is a follow-on (only matcha is wired)',
+      'TTS profile for $t is a follow-on (only matcha/qwen3 are wired)',
     ),
   };
 }
diff --git a/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart b/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart
index 2849348c..f252aaf5 100644
--- a/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart
+++ b/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart
@@ -36,5 +36,15 @@ abstract class TtsTextFrontend {
       paths,
       neuralG2p: neuralG2p,
     ),
+    // Qwen3 does its own BPE tokenization (`Qwen2BpeEncoder` +
+    // `Qwen3Prompt`) and is driven by `Qwen3TtsCore`, not this
+    // Matcha-only frontend seam — the worker (Task 5.3) dispatches to it
+    // directly and never calls `TtsTextFrontend.load` for this pipeline
+    // kind. Fail-loud rather than silently running Matcha's phoneme
+    // frontend against a Qwen3 bundle.
+    TtsPipelineKind.qwen3ArCodec => throw StateError(
+      'TtsTextFrontend: qwen3ArCodec is handled by Qwen3TtsCore, not the '
+      'Matcha TtsTextFrontend path.',
+    ),
   };
 }
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_profile_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_profile_test.dart
new file mode 100644
index 00000000..e9f4d74e
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_profile_test.dart
@@ -0,0 +1,44 @@
+// Qwen3-TTS `TtsModelProfile` wiring (Task 5.1). `Qwen3TtsCore.load`
+// hardcodes its own manifest basenames and never reads this profile's
+// file-role fields (see `tts_model_profile.dart`'s `TtsModelProfile.qwen3`
+// doc) — [pipeline] is the only load-bearing field for this model family, so
+// that's what this test asserts, alongside the text-representation/G2P
+// declarations the frontend seam (`tts_text_frontend.dart`) and worker
+// (Task 5.3) branch on.
+
+import 'package:flutter_gemma/core/model_management/model_specs.dart'
+    show TtsModelType;
+import 'package:flutter_gemma_speech/src/model/tts_model_profile.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+void main() {
+  test('forType(qwen3) gives the qwen3ArCodec pipeline + subword/no-G2P text '
+      'representation', () {
+    final p = TtsModelProfile.forType(TtsModelType.qwen3);
+    expect(p.pipeline, TtsPipelineKind.qwen3ArCodec);
+    expect(p.representation, TextRepresentation.subwordTokens);
+    expect(p.g2p, G2pStrategy.none);
+    expect(p.locale, 'en_us');
+  });
+
+  test('TtsModelProfile.qwen3() const constructor matches forType(qwen3)', () {
+    const p = TtsModelProfile.qwen3();
+    expect(p.pipeline, TtsPipelineKind.qwen3ArCodec);
+    expect(p.representation, TextRepresentation.subwordTokens);
+    expect(p.g2p, G2pStrategy.none);
+  });
+
+  test('forType(supertonic) still throws UnimplementedError (fail-loud)', () {
+    expect(
+      () => TtsModelProfile.forType(TtsModelType.supertonic),
+      throwsA(isA<UnimplementedError>()),
+    );
+  });
+
+  test('forType(kokoro) still throws UnimplementedError (fail-loud)', () {
+    expect(
+      () => TtsModelProfile.forType(TtsModelType.kokoro),
+      throwsA(isA<UnimplementedError>()),
+    );
+  });
+}
diff --git a/packages/flutter_gemma_speech/test/tts_model_profile_test.dart b/packages/flutter_gemma_speech/test/tts_model_profile_test.dart
index fee4e3b8..9be98891 100644
--- a/packages/flutter_gemma_speech/test/tts_model_profile_test.dart
+++ b/packages/flutter_gemma_speech/test/tts_model_profile_test.dart
@@ -18,7 +18,7 @@ void main() {
 
   test('forType throws UnimplementedError for unwired families', () {
     for (final t in TtsModelType.values.where(
-      (t) => t != TtsModelType.matcha,
+      (t) => t != TtsModelType.matcha && t != TtsModelType.qwen3,
     )) {
       expect(
         () => TtsModelProfile.forType(t),

From 317b237aa4422af1523cc0f7975e69c6df4deabb Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 01:31:09 +0500
Subject: [PATCH 18/30] feat(qwen3): worker branch for the AR pipeline
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

_workerEntry now branches on profile.pipeline: matchaCfm keeps the
existing TtsTextFrontend+TtsCore path (clause split + CFM seed +
inter-clause silence) unchanged in _runMatchaWorker; qwen3ArCodec
loads Qwen3TtsCore + the demo x-vector once and serves each request
with a single synthesizePcm16 call (no clause-splitting, no CFM
seed, no inter-clause silence — Qwen3 is one AR pass over its own
KV cache). Load failures surface to the caller, never fall back to
Matcha. TtsWorker.spawn/LiteRtSpeechSynthesizer.create gain an
optional language param (default 'english') threaded to the qwen3
arm; Matcha ignores it.
---
 .../src/litert/litert_speech_synthesizer.dart |   6 +-
 .../lib/src/litert/tts_worker.dart            | 147 +++++++++++++++++-
 .../test/qwen3/qwen3_worker_test.dart         | 136 ++++++++++++++++
 3 files changed, 286 insertions(+), 3 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_worker_test.dart

diff --git a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
index 36dd1319..bd18711d 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
@@ -41,19 +41,23 @@ class LiteRtSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
   /// [artifactPaths] maps each of [profile]'s bundle filenames (config,
   /// dict, embedding, and the `.tflite` graphs) to their resolved on-disk
   /// paths. [preferredBackend] selects the LiteRT hardware accelerator
-  /// (defaults to CPU).
+  /// (defaults to CPU). [language] is Qwen3-only (ignored by Matcha) — see
+  /// `TtsWorker.spawn`'s doc; defaults to `'english'`. Task 5.4 surfaces a
+  /// real language picker end to end.
   ///
   /// Caller owns the returned instance and must call [close] when done.
   static Future<LiteRtSpeechSynthesizer> create({
     required TtsModelProfile profile,
     required Map<String, String> artifactPaths,
     PreferredBackend? preferredBackend,
+    String language = 'english',
     VoidCallback? onClose,
   }) async {
     final worker = await TtsWorker.spawn(
       profile: profile,
       artifactPaths: artifactPaths,
       backend: preferredBackend,
+      language: language,
     );
     return LiteRtSpeechSynthesizer._(worker, onClose ?? () {});
   }
diff --git a/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart b/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
index 49fd3b95..f84691fd 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
@@ -30,6 +30,18 @@
 // Only sendable values cross the port: file paths + profile + backend
 // (setup), a `String` (request), and a `Uint8List` of 16-bit PCM samples
 // (reply).
+//
+// `_workerEntry` branches on `init.profile.pipeline` (Task 5.3) into
+// `_runMatchaWorker` (the above, unchanged) or `_runQwen3Worker`: Qwen3-TTS
+// is a from-scratch autoregressive codec-token LM (`Qwen3TtsCore`, Phase
+// 2-4) with its own KV cache and no CFM step, so it needs neither
+// `TtsTextFrontend`/`TtsTextNormalizer` (Matcha's dictionary G2P + host
+// embedding gather + clause splitter) nor `TtsCore` (Matcha's native
+// core) — it does its own byte-level BPE tokenization
+// (`Qwen2BpeEncoder`, inside `Qwen3TtsCore`) and consumes a request's full
+// text in ONE AR pass (no clause-splitting, no per-clause CFM seed, no
+// inter-clause silence — see `_runQwen3Worker`'s doc for why those three
+// Matcha-specific behaviors don't apply here).
 
 import 'dart:async';
 import 'dart:isolate';
@@ -40,6 +52,8 @@ import 'package:flutter_gemma/core/domain/platform_types.dart'
 import 'package:flutter_gemma/core/utils/gemma_log.dart';
 
 import '../model/tts_model_profile.dart';
+import '../qwen3/npy_reader.dart';
+import '../qwen3/qwen3_tts_core.dart';
 import '../tts/tts_text_frontend.dart';
 import '../tts/tts_text_normalizer.dart';
 import 'tts_chunk.dart';
@@ -88,6 +102,7 @@ class _WorkerInit {
     required this.artifactPaths,
     required this.backend,
     required this.logLevel,
+    required this.language,
   });
   final SendPort replyTo;
   final TtsModelProfile profile;
@@ -98,6 +113,13 @@ class _WorkerInit {
   /// isolate gets its own copy of the per-isolate top-level (default info),
   /// so it must be seeded explicitly.
   final GemmaLogLevel logLevel;
+
+  /// Qwen3-only: the `Qwen3Prompt.languageIds` key (case-insensitive) or
+  /// `'auto'`, forwarded verbatim to every `Qwen3TtsCore.synthesizePcm16`
+  /// call. Ignored by [_runMatchaWorker] (Matcha has no language parameter —
+  /// its locale comes from [TtsModelProfile.locale] instead). Task 5.4 wires
+  /// a real picker end to end; for now this just threads a default through.
+  final String language;
 }
 
 /// Main-isolate handle to the TTS worker. Spawns the isolate, performs the
@@ -121,10 +143,15 @@ class TtsWorker {
   Completer<void>? _closeAck;
 
   /// Spawn the worker and wait until the frontend + native model are loaded.
+  ///
+  /// [language] is Qwen3-only (see [_WorkerInit.language]'s doc); Matcha
+  /// ignores it. Defaults to `'english'` so every existing (Matcha) caller
+  /// is unaffected.
   static Future<TtsWorker> spawn({
     required TtsModelProfile profile,
     required Map<String, String> artifactPaths,
     PreferredBackend? backend,
+    String language = 'english',
   }) async {
     final fromWorker = ReceivePort();
     final readyCompleter = Completer<_Ready>();
@@ -163,6 +190,7 @@ class TtsWorker {
           artifactPaths: artifactPaths,
           backend: backend,
           logLevel: gemmaLogLevel,
+          language: language,
         ),
         // onExit posts `null` to fromWorker so we never wait on a dead isolate.
         onExit: fromWorker.sendPort,
@@ -255,11 +283,26 @@ class TtsWorker {
   }
 }
 
-/// Isolate entry point. Loads the frontend + model, then serves requests
-/// until _Close.
+/// Isolate entry point. Seeds the per-isolate log level, then dispatches to
+/// the pipeline-specific arm ([_runMatchaWorker] / [_runQwen3Worker]) —
+/// see this file's header for why the two pipelines don't share a request
+/// loop.
 Future<void> _workerEntry(_WorkerInit init) async {
   // Seed this isolate's per-isolate log level from the main-isolate snapshot.
   gemmaLogLevel = init.logLevel;
+  switch (init.profile.pipeline) {
+    case TtsPipelineKind.matchaCfm:
+      await _runMatchaWorker(init);
+    case TtsPipelineKind.qwen3ArCodec:
+      await _runQwen3Worker(init);
+  }
+}
+
+/// Matcha-CFM arm of [_workerEntry] — loads `TtsTextFrontend` + `TtsCore`
+/// and serves requests via the clause-split / per-clause-CFM-seed /
+/// inter-clause-silence loop described in this file's header. Unchanged by
+/// Task 5.3 (Qwen3 dispatches to [_runQwen3Worker] instead).
+Future<void> _runMatchaWorker(_WorkerInit init) async {
   final TtsCore core;
   final TtsTextFrontend frontend;
   final TtsTextNormalizer normalizer;
@@ -338,3 +381,103 @@ Future<void> _workerEntry(_WorkerInit init) async {
     init.replyTo.send(const _CloseAck());
   }
 }
+
+/// Qwen3-TTS arm of [_workerEntry] (Task 5.3). Loads `Qwen3TtsCore` (the
+/// talker/MTP/codec graphs + host tables + BPE encoder, Phase 2-4) and the
+/// bundle's one demo-voice x-vector, then serves requests with exactly ONE
+/// `core.synthesizePcm16` call per request.
+///
+/// Deliberately does NOT reuse [_runMatchaWorker]'s clause-split / CFM-seed
+/// / inter-clause-silence loop — none of those three apply here:
+/// - No clause-splitting (`TtsTextNormalizer.splitClauses`): that exists
+///   only to keep each chunk under the CFM decoder's `MAX_MEL` cap. Qwen3 is
+///   autoregressive over its own KV cache and has no such per-call length
+///   ceiling — it consumes a request's full text in one AR pass
+///   (`Qwen3TtsCore.synthesize`'s `maxFrames`, not a text-length limit).
+/// - No CFM seed (`ttsCfmSeed + clauseIndex`): Qwen3 has no CFM step; its
+///   only randomness is [_pickSampled]'s token sampling, seeded once per
+///   call via `Qwen3TtsCore.synthesizePcm16`'s own `seed` param (left
+///   unset here — see [doSample]'s doc below).
+/// - No `concatPcmWithSilence`: there is only ever one segment per request
+///   (no per-clause splitting to splice back together).
+///
+/// [Qwen3TtsCore.load] uses its default `talkerFileName`
+/// (`talker_int4.tflite`, the quantized runtime artifact — NOT the fp32
+/// artifact the golden-gate tests load) — this is the runtime path real
+/// users hit, not a correctness gate.
+///
+/// `doSample: true` on every call (per Task 5.3's brief: the runtime
+/// default is varied, natural prosody; a fixed `seed` would make every
+/// synthesis of the same text sound identical). The fp32-greedy
+/// byte-for-byte golden gate lives in `qwen3_synthesize_test.dart`
+/// (`Qwen3TtsCore.synthesize` driven directly with `doSample: false`), not
+/// here — this worker never runs greedy.
+///
+/// v1 ships exactly one voice: the bundle's `demo_speaker.npy` x-vector
+/// (Task 5.2's manifest), read once at load time via [readNpyF32] — no
+/// voice picker yet (`init.language` is the only per-call knob Task 5.3
+/// threads through; see [_WorkerInit.language]'s doc).
+///
+/// Fail-loud (per Global Constraints / the project's no-masking-fallback
+/// rule): if [Qwen3TtsCore.load] or the demo-voice read throws, this sends
+/// the error back to the main isolate exactly like [_runMatchaWorker]'s
+/// load failure does — it NEVER falls back to the Matcha path.
+Future<void> _runQwen3Worker(_WorkerInit init) async {
+  final Qwen3TtsCore core;
+  final Float32List demoVoice;
+  // Same "track the core once load succeeds" rationale as
+  // [_runMatchaWorker]'s `loadedCore` — a fully-loaded native core (3
+  // compiled graphs + environment + tables) must not be leaked if the
+  // demo-voice read fails right after.
+  Qwen3TtsCore? loadedCore;
+  try {
+    core = await Qwen3TtsCore.load(
+      artifactPaths: init.artifactPaths,
+      backend: init.backend,
+    );
+    loadedCore = core;
+    final demoVoicePath = init.artifactPaths['demo_speaker.npy'];
+    if (demoVoicePath == null) {
+      throw StateError(
+        'TtsWorker: qwen3 bundle is missing "demo_speaker.npy" in '
+        'artifactPaths',
+      );
+    }
+    demoVoice = readNpyF32(demoVoicePath);
+  } catch (e, st) {
+    loadedCore?.dispose();
+    gemmaLog('[TtsWorker] qwen3 load failed: $e\n$st');
+    init.replyTo.send('TTS worker failed to load: $e');
+    return;
+  }
+
+  final commandPort = ReceivePort();
+  init.replyTo.send(_Ready(commandPort.sendPort, core.sampleRate));
+
+  try {
+    await for (final msg in commandPort) {
+      if (msg is _SynthRequest) {
+        try {
+          final pcm = core.synthesizePcm16(
+            msg.text,
+            speaker: demoVoice,
+            language: init.language,
+            doSample: true,
+          );
+          init.replyTo.send(_SynthReply(msg.id, pcm, null));
+        } catch (e) {
+          init.replyTo.send(_SynthReply(msg.id, null, e.toString()));
+        }
+      } else if (msg is _Close) {
+        commandPort.close();
+        break;
+      }
+    }
+  } finally {
+    // Qwen3TtsCore.dispose() also frees the tables/tokenizer it owns
+    // internally (unlike Matcha, where the frontend is separate pure-Dart
+    // state) — only the core needs disposing here.
+    core.dispose();
+    init.replyTo.send(const _CloseAck());
+  }
+}
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_worker_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_worker_test.dart
new file mode 100644
index 00000000..df2e87e9
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_worker_test.dart
@@ -0,0 +1,136 @@
+// Worker-branch smoke test for the Qwen3-TTS arm of `_workerEntry`
+// (`tts_worker.dart`, Task 5.3): spawns a REAL `TtsWorker` against the qwen3
+// profile and asserts `synthesize` drives the full AR pipeline
+// (`Qwen3TtsCore`, no clause-splitting/CFM seed) end to end, on a
+// background isolate, returning plausible int16 PCM.
+//
+// Unlike `qwen3_synthesize_test.dart` (which drives `Qwen3TtsCore.synthesize`
+// directly, greedy, against a byte-exact fp32 golden), this test goes
+// through the PUBLIC worker API the runtime actually uses
+// (`LiteRtSpeechSynthesizer` -> `TtsWorker.spawn` -> `_workerEntry`), with
+// the DEFAULT (int4) talker — fast — and `doSample: true` (the runtime
+// default per Task 5.3's brief). So this test asserts PLAUSIBILITY
+// (non-empty PCM, duration/rms in a sane band), not bit-exactness — int4 +
+// sampling means exact bytes are not reproducible across runs/backends.
+//
+// The model bundle is NOT committed to the repo — see
+// `qwen3_synthesize_test.dart`'s file header for the same skip-when-absent
+// rationale ([_defaultModelDir]/`QWEN3_MODEL_DIR`).
+@Tags(['qwen3-artifacts'])
+library;
+
+import 'dart:io';
+import 'dart:math' as math;
+import 'dart:typed_data';
+
+import 'package:flutter_gemma/core/domain/platform_types.dart'
+    show PreferredBackend;
+import 'package:flutter_gemma_speech/src/litert/tts_worker.dart';
+import 'package:flutter_gemma_speech/src/model/tts_model_profile.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+/// Default location of the Qwen3-TTS model snapshot dir — the local
+/// HuggingFace cache path for `litert-community/Qwen3-TTS-12Hz-0.6B-Base`.
+/// Override with the `QWEN3_MODEL_DIR` environment variable. Mirrors every
+/// other `test/qwen3/*_test.dart`'s identical helper.
+String _defaultModelDir() {
+  final home = Platform.environment['HOME'] ?? '';
+  return '$home/.cache/huggingface/hub/'
+      'models--litert-community--Qwen3-TTS-12Hz-0.6B-Base/snapshots/'
+      '66855540b3b34679f06c3ff07859603fc9514c66';
+}
+
+String _modelDir() =>
+    Platform.environment['QWEN3_MODEL_DIR'] ?? _defaultModelDir();
+
+/// Recursively scans [dir] and returns a basename -> absolute-path map for
+/// every regular file found. Mirrors `qwen3_synthesize_test.dart`'s
+/// identical helper — this is exactly the shape `artifactPaths` has at
+/// runtime (core's model manager resolves the qwen3 bundle's 9 manifest
+/// basenames -> on-disk paths; see Task 5.2's report).
+Map<String, String> _scanArtifactPaths(String dir) {
+  final out = <String, String>{};
+  for (final entity in Directory(dir).listSync(recursive: true)) {
+    if (entity is File) {
+      out[entity.uri.pathSegments.last] = entity.path;
+    }
+  }
+  return out;
+}
+
+/// Root-mean-square of 16-bit LE mono PCM [pcm], normalized to `[-1, 1]` —
+/// a coarse "is this real audio, not silence or garbage" signal.
+double _rms(Uint8List pcm) {
+  final samples = Int16List.sublistView(pcm);
+  if (samples.isEmpty) return 0;
+  var sumSquares = 0.0;
+  for (final s in samples) {
+    final n = s / 32768.0;
+    sumSquares += n * n;
+  }
+  return math.sqrt(sumSquares / samples.length);
+}
+
+void main() {
+  final modelDir = _modelDir();
+
+  test('TtsWorker (qwen3 profile): synthesize runs the AR pipeline '
+      'end-to-end on a background isolate and returns plausible PCM', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+    final artifactPaths = _scanArtifactPaths(modelDir);
+    if (!artifactPaths.containsKey('talker_int4.tflite')) {
+      markTestSkipped(
+        'talker_int4.tflite not found under $modelDir — the worker loads '
+        'the default (int4) talker, not the fp32 golden-gate artifact.',
+      );
+      return;
+    }
+
+    final worker = await TtsWorker.spawn(
+      profile: const TtsModelProfile.qwen3(),
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+    );
+    try {
+      // Learned from the load handshake (`core.sampleRate`, `Qwen3TtsCore`'s
+      // fixed 24 kHz output) without a round-trip.
+      expect(worker.sampleRate, 24000);
+
+      final started = DateTime.now();
+      final pcm = await worker.synthesize(
+        'Hello from on device text to speech.',
+      );
+      final elapsed = DateTime.now().difference(started);
+
+      final durationSeconds = pcm.length / 2 / worker.sampleRate;
+      final rms = _rms(pcm);
+
+      // ignore: avoid_print
+      print(
+        'QWEN3-WORKER-TEST<<<pcmBytes=${pcm.length} '
+        'durationSeconds=$durationSeconds rms=$rms '
+        'elapsedMs=${elapsed.inMilliseconds}>>>',
+      );
+
+      expect(pcm, isNotEmpty);
+      // Plausibility, not bit-exactness (int4 + doSample:true is not
+      // reproducible across runs/backends): ~7 words of speech should take
+      // at least ~1s, and per `Qwen3TtsCore.synthesize`'s doc comment, no
+      // more than `maxFrames=512` frames' worth (~41s).
+      expect(durationSeconds, greaterThanOrEqualTo(1.0));
+      expect(durationSeconds, lessThan(41.0));
+      // Non-silent, non-clipped-garbage: real speech RMS sits well below
+      // full-scale but well above silence.
+      expect(rms, greaterThan(0.005));
+      expect(rms, lessThan(0.9));
+    } finally {
+      await worker.close();
+    }
+  }, timeout: const Timeout(Duration(minutes: 10)));
+}

From 37de0f7f21db8fa1ea641eeec673076428fe1472 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 01:59:41 +0500
Subject: [PATCH 19/30] feat(qwen3): language selection + catalog + picker (one
 voice, v1)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

LiteRtSpeechSynthesizer.create now validates language against a new
public qwen3SupportedLanguages list (languageIds keys + 'auto',
single source of truth also used by Qwen3Prompt.build) before
spawning the worker, fail-fast ahead of the ~1.9 GB model load.
voice is wired through to the worker as a forward-compat x-vector
override, defaulting to the bundle's demo voice.

RuntimeConfig/createTtsModel/getActiveTts gain an optional language
param so the example can actually select one. tts_screen.dart adds
a model dropdown (previously hardcoded to matcha) and a language
dropdown shown for qwen3; switching either closes the old
synthesizer and reinstalls/reactivates with the new selection.

Adds the qwen3 catalog entry (isSupported: true, CPU-only/RTF≈3/
6GB-RAM note).
---
 .../example/lib/models/tts_model.dart         |  23 +++-
 .../flutter_gemma/example/lib/tts_screen.dart | 120 +++++++++++++++++-
 .../lib/core/api/flutter_gemma.dart           |   9 ++
 .../lib/core/registry/runtime_config.dart     |  10 ++
 .../lib/desktop/flutter_gemma_desktop.dart    |   2 +
 .../lib/flutter_gemma_interface.dart          |   8 ++
 .../lib/mobile/flutter_gemma_mobile.dart      |   2 +
 .../lib/web/flutter_gemma_web.dart            |   1 +
 .../lib/flutter_gemma_speech.dart             |   7 +
 .../src/litert/litert_speech_synthesizer.dart |  24 +++-
 .../lib/src/litert/tts_worker.dart            |  35 ++++-
 .../lib/src/litert_tts_backend.dart           |   9 ++
 .../lib/src/qwen3/qwen3_languages.dart        |  60 +++++++++
 .../lib/src/qwen3/qwen3_prompt.dart           |  16 +--
 .../test/qwen3/qwen3_language_test.dart       |  79 ++++++++++++
 15 files changed, 374 insertions(+), 31 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
 create mode 100644 packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart

diff --git a/packages/flutter_gemma/example/lib/models/tts_model.dart b/packages/flutter_gemma/example/lib/models/tts_model.dart
index 0bc5cad0..34089f67 100644
--- a/packages/flutter_gemma/example/lib/models/tts_model.dart
+++ b/packages/flutter_gemma/example/lib/models/tts_model.dart
@@ -3,7 +3,11 @@ import 'package:flutter_gemma/flutter_gemma.dart' show TtsModelType;
 /// Catalog of on-device TTS models. SELECTABLE like STT — each entry carries
 /// the [TtsModelType] that tells the generic `LiteRtTtsBackend` which
 /// `TtsModelProfile` to run. Install uses one base URL + `.ofType`.
-/// Only [matcha] is wired; kokoro/supertonic are follow-ons (isSupported false).
+/// [matcha] and [qwen3] are wired; kokoro/supertonic are follow-ons
+/// (isSupported false). [qwen3] additionally exposes 11 selectable
+/// languages (`tts_screen.dart`'s language dropdown, populated from
+/// `flutter_gemma_speech`'s `qwen3SupportedLanguages`) — [matcha] is
+/// English-only (its locale comes from its bundle, not a runtime param).
 enum TtsModel {
   matcha(
     baseUrl: 'https://huggingface.co/litert-community/Matcha-TTS/resolve/main/',
@@ -12,6 +16,17 @@ enum TtsModel {
     ttsModelType: TtsModelType.matcha,
     isSupported: true,
   ),
+  qwen3(
+    baseUrl:
+        'https://huggingface.co/litert-community/Qwen3-TTS-12Hz-0.6B-Base/resolve/main/',
+    displayName: 'Qwen3-TTS 0.6B (11 languages)',
+    size: '~1.9GB',
+    ttsModelType: TtsModelType.qwen3,
+    isSupported: true,
+    notes:
+        'CPU only, slow (RTF≈3 — ~3s of compute per 1s of audio), needs a '
+        '6 GB-RAM-class device',
+  ),
   kokoro(
     baseUrl: 'https://huggingface.co/litert-community/Kokoro-82M/resolve/main/',
     displayName: 'Kokoro 82M',
@@ -38,6 +53,7 @@ enum TtsModel {
     required this.ttsModelType,
     this.isSupported = true,
     this.unsupportedReason,
+    this.notes,
   });
 
   /// HuggingFace repo base URL each manifest filename is resolved against.
@@ -59,4 +75,9 @@ enum TtsModel {
 
   /// Why [isSupported] is false; null when supported.
   final String? unsupportedReason;
+
+  /// UI-only performance/hardware caveat shown under the model info card
+  /// (e.g. CPU-only, expected RTF, RAM class) — null when there's nothing
+  /// notable to call out.
+  final String? notes;
 }
diff --git a/packages/flutter_gemma/example/lib/tts_screen.dart b/packages/flutter_gemma/example/lib/tts_screen.dart
index 5736a862..787c76a5 100644
--- a/packages/flutter_gemma/example/lib/tts_screen.dart
+++ b/packages/flutter_gemma/example/lib/tts_screen.dart
@@ -4,18 +4,27 @@ import 'package:flutter_gemma/flutter_gemma.dart';
 import 'package:flutter_gemma_example/models/tts_model.dart';
 import 'package:flutter_gemma_example/utils/audio_converter.dart';
 import 'package:flutter_gemma_example/utils/platform_io_helper.dart';
+import 'package:flutter_gemma_speech/flutter_gemma_speech.dart'
+    show qwen3SupportedLanguages;
 import 'package:just_audio/just_audio.dart';
 import 'package:path_provider/path_provider.dart';
 
 /// TTS synthesize screen — mirrors [SttScreen]'s install-in-initState /
 /// `mounted`-after-await / reentrancy discipline, but the flow is simpler:
 /// no recording, just a text field → synthesize → play. Installs
-/// (idempotent) and activates [TtsModel.matcha] — the only catalog entry
-/// with a shipped `TtsModelProfile` today (see `models/tts_model.dart`) —
-/// then lets the user type text and hear it spoken via
+/// (idempotent) and activates the selected [TtsModel] (defaults to
+/// [TtsModel.matcha]) then lets the user type text and hear it spoken via
 /// [SpeechSynthesizer.synthesize] + `just_audio` playback of the
 /// WAV-wrapped PCM (`AudioConverter.pcmToWav`).
 ///
+/// [TtsModel.qwen3] additionally exposes a LANGUAGE dropdown (11 languages,
+/// populated from `qwen3SupportedLanguages` — see Task 5.4's brief for why
+/// language, not voice, is the v1-selectable dimension: the model ships
+/// exactly one voice, no voice picker). Language is a create-time param
+/// (`FlutterGemma.getActiveTts(language: ...)`) — changing it re-creates the
+/// synthesizer (closes the old one, installs/activates again), reloading
+/// the ~1.9 GB model. Switching the model dropdown does the same.
+///
 /// `createFile` (not raw `dart:io`) is used to write the WAV to a temp file
 /// so this screen still compiles for web, where `flutter_gemma_speech` has
 /// no TTS arm (the init call surfaces that as [_initError] instead).
@@ -27,7 +36,8 @@ class TtsScreen extends StatefulWidget {
 }
 
 class _TtsScreenState extends State<TtsScreen> {
-  static const _model = TtsModel.matcha;
+  TtsModel _model = TtsModel.matcha;
+  String _language = 'english';
 
   SpeechSynthesizer? _synth;
   bool _isInitializing = true;
@@ -54,9 +64,25 @@ class _TtsScreenState extends State<TtsScreen> {
     super.dispose();
   }
 
+  bool get _isQwen3 => _model.ttsModelType == TtsModelType.qwen3;
+
   /// Install (idempotent) + activate [_model], then create the
   /// [SpeechSynthesizer]. Mirrors `SttScreen._initializeSttModel`.
+  ///
+  /// Closes any previously-created [_synth] first — `getActiveTts` reuses a
+  /// singleton for the same active model, so a language change alone (same
+  /// [_model], new [_language]) would otherwise silently keep serving the
+  /// OLD language unless the old instance is closed first (see
+  /// `FlutterGemma.getActiveTts`'s doc).
   Future<void> _initializeTtsModel() async {
+    setState(() {
+      _isInitializing = true;
+      _initError = null;
+      _downloadPercent = null;
+    });
+    final oldSynth = _synth;
+    _synth = null;
+    await oldSynth?.close();
     try {
       await FlutterGemma.installTts()
           .fromNetwork(_model.baseUrl)
@@ -67,7 +93,9 @@ class _TtsScreenState extends State<TtsScreen> {
           })
           .install();
 
-      final synth = await FlutterGemma.getActiveTts();
+      final synth = await FlutterGemma.getActiveTts(
+        language: _isQwen3 ? _language : null,
+      );
 
       if (!mounted) return;
       setState(() {
@@ -86,6 +114,22 @@ class _TtsScreenState extends State<TtsScreen> {
     }
   }
 
+  /// Switch the active catalog entry and reinitialize. No-op if [model] is
+  /// already selected or a (re)initialization is already in flight.
+  void _selectModel(TtsModel model) {
+    if (model == _model || _isInitializing) return;
+    setState(() => _model = model);
+    _initializeTtsModel();
+  }
+
+  /// Switch the qwen3 language and reinitialize (see [_initializeTtsModel]'s
+  /// doc for why this must close+recreate rather than just updating state).
+  void _selectLanguage(String language) {
+    if (language == _language || _isInitializing) return;
+    setState(() => _language = language);
+    _initializeTtsModel();
+  }
+
   Future<void> _speak() async {
     if (_synth == null || _isSpeaking) return; // reentrancy guard
     setState(() {
@@ -143,6 +187,7 @@ class _TtsScreenState extends State<TtsScreen> {
   }
 
   Widget _buildModelInfoCard() {
+    final supported = TtsModel.values.where((m) => m.isSupported).toList();
     return Card(
       color: const Color(0xFF1a3a5c),
       child: Padding(
@@ -159,14 +204,79 @@ class _TtsScreenState extends State<TtsScreen> {
               ),
             ),
             const SizedBox(height: 12),
+            _buildDropdownRow<TtsModel>(
+              label: 'Model:',
+              value: _model,
+              items: [
+                for (final m in supported)
+                  DropdownMenuItem(value: m, child: Text(m.displayName)),
+              ],
+              onChanged: (m) {
+                if (m != null) _selectModel(m);
+              },
+            ),
+            const SizedBox(height: 8),
             _buildInfoRow('Size:', _model.size),
             _buildInfoRow('Type:', 'Text-to-Speech'),
+            if (_isQwen3) ...[
+              const SizedBox(height: 8),
+              _buildDropdownRow<String>(
+                label: 'Language:',
+                value: _language,
+                items: [
+                  for (final lang in qwen3SupportedLanguages)
+                    DropdownMenuItem(value: lang, child: Text(lang)),
+                ],
+                onChanged: (lang) {
+                  if (lang != null) _selectLanguage(lang);
+                },
+              ),
+            ],
+            if (_model.notes != null) ...[
+              const SizedBox(height: 12),
+              Text(
+                _model.notes!,
+                style: const TextStyle(
+                  color: Colors.orangeAccent,
+                  fontSize: 12,
+                ),
+              ),
+            ],
           ],
         ),
       ),
     );
   }
 
+  /// A label + [DropdownButton] row, disabled while [_isInitializing] (a
+  /// model/language switch is already in flight — reentrancy guard mirrors
+  /// [_selectModel]/[_selectLanguage]'s own check).
+  Widget _buildDropdownRow<T>({
+    required String label,
+    required T value,
+    required List<DropdownMenuItem<T>> items,
+    required ValueChanged<T?> onChanged,
+  }) {
+    return Row(
+      children: [
+        SizedBox(
+          width: 80,
+          child: Text(label, style: const TextStyle(color: Colors.white70)),
+        ),
+        Expanded(
+          child: DropdownButton<T>(
+            value: value,
+            items: items,
+            onChanged: _isInitializing ? null : onChanged,
+            isExpanded: true,
+            dropdownColor: const Color(0xFF1a3a5c),
+            style: const TextStyle(color: Colors.white),
+          ),
+        ),
+      ],
+    );
+  }
+
   Widget _buildInfoRow(String label, String value) {
     return Padding(
       padding: const EdgeInsets.symmetric(vertical: 4.0),
diff --git a/packages/flutter_gemma/lib/core/api/flutter_gemma.dart b/packages/flutter_gemma/lib/core/api/flutter_gemma.dart
index 1d0e21c9..63d4504c 100644
--- a/packages/flutter_gemma/lib/core/api/flutter_gemma.dart
+++ b/packages/flutter_gemma/lib/core/api/flutter_gemma.dart
@@ -554,6 +554,13 @@ class FlutterGemma {
   ///
   /// Runtime parameters:
   /// - [preferredBackend]: CPU or GPU preference (optional)
+  /// - [language]: TTS-only (Qwen3; ignored by Matcha, whose locale comes
+  ///   from its bundle instead) — one of `flutter_gemma_speech`'s
+  ///   `qwen3SupportedLanguages`, or `'auto'`; defaults to `'english'` when
+  ///   null. An unsupported value throws `ArgumentError` before the model
+  ///   loads. A previously-created synthesizer for the same active model is
+  ///   reused across calls (create-time singleton) — to pick up a new
+  ///   [language], [close][SpeechSynthesizer.close] it first.
   ///
   /// Throws:
   /// - [StateError] if no active TTS model is set
@@ -571,6 +578,7 @@ class FlutterGemma {
   /// ```
   static Future<SpeechSynthesizer> getActiveTts({
     PreferredBackend? preferredBackend,
+    String? language,
   }) async {
     final manager = FlutterGemmaPlugin.instance.modelManager;
     final activeSpec = manager.activeTtsModel;
@@ -591,6 +599,7 @@ class FlutterGemma {
     // Create SpeechSynthesizer using active spec (paths resolved automatically)
     return await FlutterGemmaPlugin.instance.createTtsModel(
       preferredBackend: preferredBackend,
+      language: language,
     );
   }
 
diff --git a/packages/flutter_gemma/lib/core/registry/runtime_config.dart b/packages/flutter_gemma/lib/core/registry/runtime_config.dart
index 846e5a34..7b72caf6 100644
--- a/packages/flutter_gemma/lib/core/registry/runtime_config.dart
+++ b/packages/flutter_gemma/lib/core/registry/runtime_config.dart
@@ -17,6 +17,7 @@ class RuntimeConfig {
     this.maxConcurrentSessions,
     this.loraRanks,
     this.artifactPaths,
+    this.language,
   }) : assert(maxTokens >= 0, 'maxTokens must not be negative'),
        assert(
          maxNumImages == null || maxNumImages >= 0,
@@ -61,4 +62,13 @@ class RuntimeConfig {
   /// backend resolves each graph/dictionary/embedding file by name from this
   /// map. Null for single-file models (inference/embedding/STT).
   final Map<String, String>? artifactPaths;
+
+  /// TTS-only (Qwen3): the language to condition generation on — one of
+  /// `flutter_gemma_speech`'s `qwen3SupportedLanguages`, or `'auto'`. Null
+  /// for non-TTS models, and for TTS models with no language parameter
+  /// (e.g. Matcha, whose locale comes from its `TtsModelProfile.locale`
+  /// instead) — the TTS backend defaults a null value to `'english'`. Not
+  /// validated here; the TTS backend rejects an unsupported value with
+  /// `ArgumentError` before loading the model.
+  final String? language;
 }
diff --git a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
index fa2ad9f9..88dcbab1 100644
--- a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
+++ b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
@@ -500,6 +500,7 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
   @override
   Future<SpeechSynthesizer> createTtsModel({
     PreferredBackend? preferredBackend,
+    String? language,
   }) async {
     final activeModel = _modelManager.activeTtsModel;
     if (activeModel is! TtsModelSpec) {
@@ -550,6 +551,7 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
             .first, // representative; TTS backend uses artifactPaths
         artifactPaths: filePaths,
         preferredBackend: preferredBackend,
+        language: language,
       );
       final backend = TtsRegistry.instance.findFor(activeModel);
       if (backend == null) {
diff --git a/packages/flutter_gemma/lib/flutter_gemma_interface.dart b/packages/flutter_gemma/lib/flutter_gemma_interface.dart
index 8d3417ad..1596c6af 100644
--- a/packages/flutter_gemma/lib/flutter_gemma_interface.dart
+++ b/packages/flutter_gemma/lib/flutter_gemma_interface.dart
@@ -122,8 +122,16 @@ abstract class FlutterGemmaPlugin extends PlatformInterface {
   ///
   /// Uses the active TTS model set via `FlutterGemma.installTts()` /
   /// `modelManager.setActiveModel()`. Native-only — throws on web.
+  ///
+  /// [language] is TTS-only (Qwen3; ignored by Matcha) — see
+  /// `RuntimeConfig.language`'s doc. Forwarded into the `RuntimeConfig` the
+  /// active model's backend builds from. A singleton for the same active
+  /// model is reused across calls, so switching languages requires
+  /// explicitly closing the previous [SpeechSynthesizer] first — a new
+  /// [language] alone does not force a rebuild.
   Future<SpeechSynthesizer> createTtsModel({
     PreferredBackend? preferredBackend,
+    String? language,
   });
 
   /// === RAG functionality ===
diff --git a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
index 2b8e0b86..050d900c 100644
--- a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
+++ b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
@@ -581,6 +581,7 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
   @override
   Future<SpeechSynthesizer> createTtsModel({
     PreferredBackend? preferredBackend,
+    String? language,
   }) async {
     final manager = _unifiedManager;
     final activeModel = manager.activeTtsModel;
@@ -643,6 +644,7 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
             .first, // representative; TTS backend uses artifactPaths
         artifactPaths: filePaths,
         preferredBackend: preferredBackend,
+        language: language,
       );
       final backend = TtsRegistry.instance.findFor(activeModel);
       if (backend == null) {
diff --git a/packages/flutter_gemma/lib/web/flutter_gemma_web.dart b/packages/flutter_gemma/lib/web/flutter_gemma_web.dart
index 02788d04..ff9c8529 100644
--- a/packages/flutter_gemma/lib/web/flutter_gemma_web.dart
+++ b/packages/flutter_gemma/lib/web/flutter_gemma_web.dart
@@ -394,6 +394,7 @@ class FlutterGemmaWeb extends FlutterGemmaPlugin {
   @override
   Future<SpeechSynthesizer> createTtsModel({
     PreferredBackend? preferredBackend,
+    String? language,
   }) async {
     throw UnsupportedError(
       'On-device TTS is not supported on web (flutter_gemma_speech TTS is native-only).',
diff --git a/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart b/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart
index 05a825c6..c4b2682f 100644
--- a/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart
+++ b/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart
@@ -25,3 +25,10 @@ export 'src/litert_tts_backend_stub.dart'
 export 'src/voice/voice_event.dart';
 export 'src/voice/voice_responder.dart';
 export 'src/voice/voice_session.dart';
+
+// Qwen3-TTS supported-language list (Task 5.4) — dependency-free, safe on
+// every platform. The single source of truth for both the create-time
+// language validator (`LiteRtSpeechSynthesizer.create`) and a UI language
+// picker; see `qwen3_languages.dart`'s header for why it's a separate file
+// from `qwen3_prompt.dart` (which is native-only, via `dart:io`).
+export 'src/qwen3/qwen3_languages.dart';
diff --git a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
index bd18711d..6b62b229 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
@@ -18,6 +18,7 @@ import 'package:flutter_gemma/flutter_gemma_interface.dart'
     show SpeechSynthesizer;
 
 import '../model/tts_model_profile.dart';
+import '../qwen3/qwen3_languages.dart' show assertQwen3LanguageSupported;
 import 'tts_worker.dart';
 
 /// Signature for the `onClose` callback. Same name Flutter uses.
@@ -41,9 +42,21 @@ class LiteRtSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
   /// [artifactPaths] maps each of [profile]'s bundle filenames (config,
   /// dict, embedding, and the `.tflite` graphs) to their resolved on-disk
   /// paths. [preferredBackend] selects the LiteRT hardware accelerator
-  /// (defaults to CPU). [language] is Qwen3-only (ignored by Matcha) — see
-  /// `TtsWorker.spawn`'s doc; defaults to `'english'`. Task 5.4 surfaces a
-  /// real language picker end to end.
+  /// (defaults to CPU). [language] is Qwen3-only (ignored by Matcha, which
+  /// has no language parameter — its locale comes from
+  /// [TtsModelProfile.locale] instead); defaults to `'english'`. For a
+  /// [profile] whose [TtsModelProfile.pipeline] is
+  /// [TtsPipelineKind.qwen3ArCodec], [language] is validated against
+  /// `qwen3SupportedLanguages` (`qwen3_languages.dart`) and this throws
+  /// [ArgumentError] for an unknown value BEFORE spawning the worker —
+  /// fail-fast, ahead of the ~1.9 GB model load (Task 5.4).
+  ///
+  /// [voice] is a forward-compat speaker x-vector override (`[1024]`,
+  /// Qwen3-only): when non-null it replaces the bundle's single demo voice
+  /// (`voices/demo_speaker.npy`) for every `synthesize` call on the returned
+  /// instance. v1 ships exactly one voice and does not surface a voice
+  /// picker anywhere (see Task 5.4's brief) — this param exists purely so a
+  /// future multi-voice release doesn't need a breaking signature change.
   ///
   /// Caller owns the returned instance and must call [close] when done.
   static Future<LiteRtSpeechSynthesizer> create({
@@ -51,13 +64,18 @@ class LiteRtSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
     required Map<String, String> artifactPaths,
     PreferredBackend? preferredBackend,
     String language = 'english',
+    Float32List? voice,
     VoidCallback? onClose,
   }) async {
+    if (profile.pipeline == TtsPipelineKind.qwen3ArCodec) {
+      assertQwen3LanguageSupported(language);
+    }
     final worker = await TtsWorker.spawn(
       profile: profile,
       artifactPaths: artifactPaths,
       backend: preferredBackend,
       language: language,
+      voice: voice,
     );
     return LiteRtSpeechSynthesizer._(worker, onClose ?? () {});
   }
diff --git a/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart b/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
index f84691fd..0976cd8d 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
@@ -103,6 +103,7 @@ class _WorkerInit {
     required this.backend,
     required this.logLevel,
     required this.language,
+    required this.voice,
   });
   final SendPort replyTo;
   final TtsModelProfile profile;
@@ -117,9 +118,18 @@ class _WorkerInit {
   /// Qwen3-only: the `Qwen3Prompt.languageIds` key (case-insensitive) or
   /// `'auto'`, forwarded verbatim to every `Qwen3TtsCore.synthesizePcm16`
   /// call. Ignored by [_runMatchaWorker] (Matcha has no language parameter —
-  /// its locale comes from [TtsModelProfile.locale] instead). Task 5.4 wires
-  /// a real picker end to end; for now this just threads a default through.
+  /// its locale comes from [TtsModelProfile.locale] instead). Validated by
+  /// `LiteRtSpeechSynthesizer.create` (Task 5.4) before the worker is even
+  /// spawned, so by the time it reaches here it is always a supported value.
   final String language;
+
+  /// Qwen3-only: forward-compat speaker x-vector override (`[1024]`); null
+  /// uses the bundle's single demo voice (`voices/demo_speaker.npy`, read in
+  /// [_runQwen3Worker]). Ignored by [_runMatchaWorker]. See
+  /// `LiteRtSpeechSynthesizer.create`'s [voice] doc — v1 does not surface a
+  /// voice picker anywhere; this only exists so a future multi-voice release
+  /// doesn't need a breaking signature change.
+  final Float32List? voice;
 }
 
 /// Main-isolate handle to the TTS worker. Spawns the isolate, performs the
@@ -146,12 +156,14 @@ class TtsWorker {
   ///
   /// [language] is Qwen3-only (see [_WorkerInit.language]'s doc); Matcha
   /// ignores it. Defaults to `'english'` so every existing (Matcha) caller
-  /// is unaffected.
+  /// is unaffected. [voice] is Qwen3-only (see [_WorkerInit.voice]'s doc);
+  /// null (the default) uses the bundle's demo voice.
   static Future<TtsWorker> spawn({
     required TtsModelProfile profile,
     required Map<String, String> artifactPaths,
     PreferredBackend? backend,
     String language = 'english',
+    Float32List? voice,
   }) async {
     final fromWorker = ReceivePort();
     final readyCompleter = Completer<_Ready>();
@@ -191,6 +203,7 @@ class TtsWorker {
           backend: backend,
           logLevel: gemmaLogLevel,
           language: language,
+          voice: voice,
         ),
         // onExit posts `null` to fromWorker so we never wait on a dead isolate.
         onExit: fromWorker.sendPort,
@@ -414,9 +427,12 @@ Future<void> _runMatchaWorker(_WorkerInit init) async {
 /// here — this worker never runs greedy.
 ///
 /// v1 ships exactly one voice: the bundle's `demo_speaker.npy` x-vector
-/// (Task 5.2's manifest), read once at load time via [readNpyF32] — no
-/// voice picker yet (`init.language` is the only per-call knob Task 5.3
-/// threads through; see [_WorkerInit.language]'s doc).
+/// (Task 5.2's manifest), read once at load time via [readNpyF32] unless
+/// [_WorkerInit.voice] overrides it — no voice PICKER yet (`init.voice` is
+/// forward-compat-only; the UI never sets it, see [_WorkerInit.voice]'s
+/// doc). `init.language` is the per-call knob Task 5.3 threads through and
+/// Task 5.4 validates + surfaces a real picker for; see
+/// [_WorkerInit.language]'s doc.
 ///
 /// Fail-loud (per Global Constraints / the project's no-masking-fallback
 /// rule): if [Qwen3TtsCore.load] or the demo-voice read throws, this sends
@@ -443,7 +459,12 @@ Future<void> _runQwen3Worker(_WorkerInit init) async {
         'artifactPaths',
       );
     }
-    demoVoice = readNpyF32(demoVoicePath);
+    // [_WorkerInit.voice] overrides the bundle's demo voice when set
+    // (forward-compat only — v1's UI never sets it). The manifest presence
+    // check above stays unconditional even then: the bundle always ships
+    // demo_speaker.npy in v1, so its absence is still a load-time bug worth
+    // surfacing regardless of whether an override happens to be in play.
+    demoVoice = init.voice ?? readNpyF32(demoVoicePath);
   } catch (e, st) {
     loadedCore?.dispose();
     gemmaLog('[TtsWorker] qwen3 load failed: $e\n$st');
diff --git a/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart b/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart
index 880b91b1..37167954 100644
--- a/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart
@@ -36,10 +36,19 @@ class LiteRtTtsBackend implements TtsBackendProvider {
     }
     // spec.ttsModelType (e.g. TtsModelType.matcha) selects the runtime
     // profile — this backend never hardcodes a model.
+    //
+    // config.language is Qwen3-only (Task 5.4) — threaded from
+    // `FlutterGemma.getActiveTts(language: ...)` through `RuntimeConfig`;
+    // null falls back to `LiteRtSpeechSynthesizer.create`'s own `'english'`
+    // default. Matcha ignores it (no language parameter). No `voice` here:
+    // v1 never surfaces a voice picker anywhere in the public API, so this
+    // backend always takes `LiteRtSpeechSynthesizer.create`'s default
+    // (the bundle's single demo voice) — see that method's `voice` doc.
     return LiteRtSpeechSynthesizer.create(
       profile: TtsModelProfile.forType(spec.ttsModelType),
       artifactPaths: artifactPaths,
       preferredBackend: config.preferredBackend,
+      language: config.language ?? 'english',
       onClose: () {},
     );
   }
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
new file mode 100644
index 00000000..f8ccf945
--- /dev/null
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
@@ -0,0 +1,60 @@
+// Qwen3-TTS language-id map + the public supported-language list.
+//
+// Single source of truth for THREE consumers that must never drift apart:
+//  - `Qwen3Prompt.build` (`qwen3_prompt.dart`), which maps a language name to
+//    its control-token id for the talker prompt (Task 1.4/5.1).
+//  - `LiteRtSpeechSynthesizer.create`'s create-time language validator
+//    (Task 5.4) — fails loud with an `ArgumentError` for an unknown language
+//    BEFORE spawning the ~1.9 GB `TtsWorker`, rather than deep inside the
+//    worker isolate on the first `synthesize` call.
+//  - the example's language picker (`tts_screen.dart`), which populates its
+//    dropdown from [qwen3SupportedLanguages] instead of hardcoding a second
+//    copy of the list.
+//
+// This file is deliberately dependency-free (no imports at all, not even
+// `dart:typed_data`) so it is safe to export UNCONDITIONALLY from the
+// package barrel, including on platforms without `dart:io`/`dart:ffi`
+// (`qwen3_prompt.dart` itself pulls in `qwen3_tables.dart`, which uses
+// `dart:io` — that stays package-private).
+library;
+
+/// Language id map from the model config (`talker_config.codec_language_id`).
+/// Ported from `text_to_speech_lm/python/qwen3_tts_pipeline.py:59-70`.
+const Map<String, int> languageIds = {
+  'chinese': 2055,
+  'english': 2050,
+  'german': 2053,
+  'italian': 2070,
+  'portuguese': 2071,
+  'spanish': 2054,
+  'japanese': 2058,
+  'korean': 2064,
+  'french': 2061,
+  'russian': 2069,
+};
+
+/// The full set of `language` values Qwen3-TTS accepts: [languageIds]'s
+/// keys (alphabetical) plus `'auto'` (automatic language detection — no
+/// language-id control token is emitted; see `Qwen3Prompt.build`'s `'auto'`
+/// branch). `'auto'` is appended last since it isn't a language, it's a
+/// detection mode.
+final List<String> qwen3SupportedLanguages = List.unmodifiable(<String>[
+  ...(languageIds.keys.toList()..sort()),
+  'auto',
+]);
+
+/// Throws [ArgumentError] if [language] (case-insensitive) is not in
+/// [qwen3SupportedLanguages]. Factored out as a standalone pure function
+/// (rather than inlined at the call site) so it is unit-testable without
+/// spawning a `TtsWorker` — which needs the ~1.9 GB Qwen3-TTS model bundle
+/// on disk to construct at all.
+void assertQwen3LanguageSupported(String language) {
+  if (!qwen3SupportedLanguages.contains(language.toLowerCase())) {
+    throw ArgumentError.value(
+      language,
+      'language',
+      'Unsupported Qwen3-TTS language. Must be one of: '
+          '${qwen3SupportedLanguages.join(', ')}',
+    );
+  }
+}
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
index 43bd1560..19d8c86b 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
@@ -20,6 +20,7 @@
 
 import 'dart:typed_data';
 
+import 'qwen3_languages.dart' show languageIds;
 import 'qwen3_tables.dart';
 
 /// Talker hidden size — width of every embedding row this module handles.
@@ -39,21 +40,6 @@ const int _ttsBos = 151672;
 const int _ttsEos = 151673;
 const int _ttsPad = 151671;
 
-/// Language id map from the model config (`talker_config.codec_language_id`).
-/// qwen3_tts_pipeline.py:59-70.
-const Map<String, int> languageIds = {
-  'chinese': 2055,
-  'english': 2050,
-  'german': 2053,
-  'italian': 2070,
-  'portuguese': 2071,
-  'spanish': 2054,
-  'japanese': 2058,
-  'korean': 2064,
-  'french': 2061,
-  'russian': 2069,
-};
-
 /// Result of [Qwen3Prompt.build]: the talker's fixed-length prefill
 /// embeddings plus the per-frame streamed text conditioning consumed while
 /// decoding audio frames.
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart
new file mode 100644
index 00000000..393de7e9
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart
@@ -0,0 +1,79 @@
+// Task 5.4: create-time language selection for Qwen3-TTS.
+//
+// `LiteRtSpeechSynthesizer.create` validates `language` against
+// `qwen3SupportedLanguages` (`qwen3_languages.dart`) BEFORE spawning the
+// `TtsWorker` — fail-fast, ahead of the ~1.9 GB model load — when `profile`
+// is `TtsPipelineKind.qwen3ArCodec`. This file tests that validation at two
+// levels:
+//  - `assertQwen3LanguageSupported` directly: a pure function, no isolate/
+//    artifacts needed, so it's the fast/deterministic coverage for the
+//    accept/reject boundary and the language->control-token id map.
+//  - `LiteRtSpeechSynthesizer.create` end to end for the reject case: proves
+//    the ArgumentError actually fires from `create` itself (not just from
+//    the helper in isolation), and that it does so WITHOUT touching
+//    `artifactPaths` — passed empty here, which would otherwise surface as
+//    a completely different (StateError/IO) failure once the worker
+//    actually tried to load a bundle.
+//
+// The accept-case end-to-end path (`create` with a valid Qwen3 language
+// actually spawning a worker and resolving the default demo x-vector) is
+// NOT re-tested here — it needs the ~1.9 GB Qwen3-TTS bundle on disk and is
+// already covered by the artifact-gated `test/qwen3/qwen3_worker_test.dart`
+// (`@Tags(['qwen3-artifacts'])`), whose default-voice behavior Task 5.4
+// leaves unchanged (`TtsWorker`'s `voice` override is opt-in and defaults to
+// null, i.e. the pre-existing `readNpyF32(demoVoicePath)` path).
+
+import 'package:flutter_gemma_speech/src/litert/litert_speech_synthesizer.dart';
+import 'package:flutter_gemma_speech/src/model/tts_model_profile.dart';
+import 'package:flutter_gemma_speech/src/qwen3/qwen3_languages.dart';
+import 'package:flutter_test/flutter_test.dart';
+
+void main() {
+  group('assertQwen3LanguageSupported', () {
+    test('throws ArgumentError for an unknown language', () {
+      expect(
+        () => assertQwen3LanguageSupported('klingon'),
+        throwsArgumentError,
+      );
+    });
+
+    test('accepts every qwen3SupportedLanguages entry', () {
+      for (final lang in qwen3SupportedLanguages) {
+        expect(() => assertQwen3LanguageSupported(lang), returnsNormally);
+      }
+    });
+
+    test('is case-insensitive', () {
+      expect(() => assertQwen3LanguageSupported('German'), returnsNormally);
+      expect(() => assertQwen3LanguageSupported('GERMAN'), returnsNormally);
+    });
+  });
+
+  group('languageIds / qwen3SupportedLanguages (single source of truth)', () {
+    test("'german' maps to control token 2053", () {
+      expect(languageIds['german'], 2053);
+    });
+
+    test('qwen3SupportedLanguages contains every languageIds key plus '
+        "'auto'", () {
+      expect(qwen3SupportedLanguages, containsAll(languageIds.keys));
+      expect(qwen3SupportedLanguages, contains('auto'));
+      expect(qwen3SupportedLanguages.length, languageIds.length + 1);
+    });
+  });
+
+  group('LiteRtSpeechSynthesizer.create', () {
+    test('rejects an unknown qwen3 language before spawning the worker '
+        '(empty artifactPaths would otherwise fail differently once the '
+        'worker tried to load a bundle)', () async {
+      await expectLater(
+        LiteRtSpeechSynthesizer.create(
+          profile: const TtsModelProfile.qwen3(),
+          artifactPaths: const {},
+          language: 'klingon',
+        ),
+        throwsArgumentError,
+      );
+    });
+  });
+}

From 8d23332c845c2091f187b54570f6a3a1711f9ec7 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 02:25:24 +0500
Subject: [PATCH 20/30] fix(qwen3): language-blind TTS singleton reuse +
 case-sensitive 'auto'
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

createTtsModel's same-model reuse branch (mobile + desktop shells)
compared only the active model name, so a second getActiveTts() call
with a different language silently returned the stale synthesizer —
wrong-language audio with no error. Now stores the language the
singleton was built with and throws StateError on a mismatch instead
of reusing it; unaffected when language is unset (matcha).

Also: assertQwen3LanguageSupported validated case-insensitively but
Qwen3Prompt.build's 'auto' compare was case-sensitive, so 'Auto'/
'AUTO' passed create() but threw ArgumentError after the ~1.9 GB
model load, at the first synthesize call. LiteRtSpeechSynthesizer.
create now normalizes the language once, right after validation, via
the new normalizeQwen3Language helper.
---
 .../lib/desktop/flutter_gemma_desktop.dart    |  23 +-
 .../lib/mobile/flutter_gemma_mobile.dart      |  23 +-
 .../mobile/tts_language_singleton_test.dart   | 203 ++++++++++++++++++
 .../src/litert/litert_speech_synthesizer.dart |  14 +-
 .../lib/src/qwen3/qwen3_languages.dart        |  15 ++
 .../test/qwen3/qwen3_language_test.dart       |  66 ++++++
 6 files changed, 339 insertions(+), 5 deletions(-)
 create mode 100644 packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart

diff --git a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
index 88dcbab1..464611c9 100644
--- a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
+++ b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
@@ -81,6 +81,11 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
   SpeechSynthesizer? _initializedTtsModel;
   TtsModelSpec?
   _lastActiveTtsSpec; // Track which spec was used to create _initializedTtsModel
+  // The `language` the active singleton was built with (raw, as received —
+  // not defaulted). Reusing the singleton for a DIFFERENT language would
+  // silently emit wrong-language audio with no error (Task 5.4 review,
+  // Important #1) — see the same-model branch in createTtsModel below.
+  String? _lastActiveTtsLanguage;
 
   @override
   ModelFileManager get modelManager => _modelManager;
@@ -523,9 +528,22 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
         _initTtsCompleter = null;
         _initializedTtsModel = null;
         _lastActiveTtsSpec = null;
+        _lastActiveTtsLanguage = null;
         await old?.close();
+      } else if (language != _lastActiveTtsLanguage) {
+        // Same model, but a DIFFERENT language was requested — reusing the
+        // singleton here would silently emit WRONG-LANGUAGE audio with no
+        // error (Task 5.4 review, Important #1). Fail loud instead of
+        // reusing: the caller must close() the existing synthesizer first
+        // (tts_screen.dart already does this on every model/language
+        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs).
+        throw StateError(
+          'Active TTS synthesizer was created for language '
+          "'${_lastActiveTtsLanguage ?? 'default'}'; call close() before "
+          "requesting '${language ?? 'default'}'.",
+        );
       } else {
-        // Same model - return existing singleton
+        // Same model, same language - return existing singleton
         return _initTtsCompleter!.future;
       }
     }
@@ -572,6 +590,7 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
       // package-built model fires this via CloseNotifier (addCloseListener).
       _initializedTtsModel = synth;
       _lastActiveTtsSpec = activeModel;
+      _lastActiveTtsLanguage = language;
       synth.addCloseListener(() {
         // Only reset if this close-listener still belongs to the current
         // singleton — a newer model may already have replaced it (the
@@ -580,6 +599,7 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
           _initializedTtsModel = null;
           _initTtsCompleter = null;
           _lastActiveTtsSpec = null;
+          _lastActiveTtsLanguage = null;
         }
       });
 
@@ -590,6 +610,7 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
       _initTtsCompleter = null;
       _initializedTtsModel = null;
       _lastActiveTtsSpec = null;
+      _lastActiveTtsLanguage = null;
       // Return the completer's future (rather than a bare rethrow) so there
       // is exactly one Future in flight for this call — an unheeded
       // `completer.future` (left behind whenever no concurrent caller
diff --git a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
index 050d900c..f0677930 100644
--- a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
+++ b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
@@ -59,6 +59,11 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
   SpeechSynthesizer? _initializedTtsModel;
   TtsModelSpec?
   _lastActiveTtsSpec; // Track which spec was used to create _initializedTtsModel
+  // The `language` the active singleton was built with (raw, as received —
+  // not defaulted). Reusing the singleton for a DIFFERENT language would
+  // silently emit wrong-language audio with no error (Task 5.4 review,
+  // Important #1) — see the same-model branch in createTtsModel below.
+  String? _lastActiveTtsLanguage;
 
   // Made public for example app integration
   late final MobileModelManager _unifiedManager = MobileModelManager();
@@ -610,9 +615,22 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
         _initTtsCompleter = null;
         _initializedTtsModel = null;
         _lastActiveTtsSpec = null;
+        _lastActiveTtsLanguage = null;
         await old?.close();
+      } else if (language != _lastActiveTtsLanguage) {
+        // Same model, but a DIFFERENT language was requested — reusing the
+        // singleton here would silently emit WRONG-LANGUAGE audio with no
+        // error (Task 5.4 review, Important #1). Fail loud instead of
+        // reusing: the caller must close() the existing synthesizer first
+        // (tts_screen.dart already does this on every model/language
+        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs).
+        throw StateError(
+          'Active TTS synthesizer was created for language '
+          "'${_lastActiveTtsLanguage ?? 'default'}'; call close() before "
+          "requesting '${language ?? 'default'}'.",
+        );
       } else {
-        // Same model - return existing singleton
+        // Same model, same language - return existing singleton
         gemmaLog(
           'ℹ️  Reusing existing TTS model instance for ${activeModel.name}',
         );
@@ -665,6 +683,7 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
       // package-built model fires this via CloseNotifier (addCloseListener).
       _initializedTtsModel = synth;
       _lastActiveTtsSpec = activeModel;
+      _lastActiveTtsLanguage = language;
       synth.addCloseListener(() {
         // Only reset if this close-listener still belongs to the current
         // singleton — a newer model may already have replaced it (the
@@ -673,6 +692,7 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
           _initializedTtsModel = null;
           _initTtsCompleter = null;
           _lastActiveTtsSpec = null;
+          _lastActiveTtsLanguage = null;
         }
       });
 
@@ -682,6 +702,7 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
       _initTtsCompleter = null;
       _initializedTtsModel = null;
       _lastActiveTtsSpec = null;
+      _lastActiveTtsLanguage = null;
       // Complete the completer and return its future (rather than
       // rethrowing separately) so there is exactly one Future in flight for
       // this call — a second, unheeded `completer.future` (as a bare
diff --git a/packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart b/packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart
new file mode 100644
index 00000000..a97f543e
--- /dev/null
+++ b/packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart
@@ -0,0 +1,203 @@
+// Task 5.4 review, Important #1: the TTS singleton cache
+// (FlutterGemmaMobile.createTtsModel) used to key its "reuse the existing
+// synthesizer" branch ONLY on the active model's name, not on the requested
+// `language`. So a second `getActiveTts(language: 'french')` for the SAME
+// active qwen3 model silently returned the FIRST call's (e.g. English)
+// synthesizer — wrong-language audio through the primary public API, with
+// no error. This is a real end-to-end test against the ACTUAL
+// FlutterGemmaMobile/FlutterGemma facade (not a hand-rolled simulation of
+// the completer logic) — it uses the exact `_FixtureDownloadService` +
+// `_FixedPathProviderPlatform` fixture pattern already established in
+// test/core/api/install_identity_namespacing_test.dart to get a REAL
+// install() + getActiveTts() flow working without a device or network.
+//
+// Run: flutter test test/mobile/tts_language_singleton_test.dart
+
+import 'dart:io';
+import 'dart:typed_data';
+
+import 'package:flutter_test/flutter_test.dart';
+import 'package:path_provider_platform_interface/path_provider_platform_interface.dart';
+import 'package:shared_preferences/shared_preferences.dart';
+
+import 'package:flutter_gemma/core/di/service_registry.dart';
+import 'package:flutter_gemma/core/lifecycle/close_notifier.dart';
+import 'package:flutter_gemma/core/registry/runtime_config.dart';
+import 'package:flutter_gemma/core/registry/tts_backend_provider.dart';
+import 'package:flutter_gemma/core/registry/tts_registry.dart';
+import 'package:flutter_gemma/core/services/download_service.dart';
+import 'package:flutter_gemma/flutter_gemma.dart';
+
+// FileSourceHandler enforces a minimum size per extension — the qwen3
+// manifest's 9 files clear both the 1KB (json/npy/npz) and 1MB (tflite)
+// floors with this single fixture, mirroring the matcha fixture in
+// install_identity_namespacing_test.dart.
+final _fakeBundleBytes = Uint8List(1024 * 1024 + 16);
+
+void main() {
+  TestWidgetsFlutterBinding.ensureInitialized();
+
+  late Directory fakeDocuments;
+  late Directory fakeAppSupport;
+
+  setUp(() async {
+    fakeDocuments = await Directory.systemTemp.createTemp(
+      'flutter_gemma_docs_',
+    );
+    fakeAppSupport = await Directory.systemTemp.createTemp(
+      'flutter_gemma_appsupport_',
+    );
+    PathProviderPlatform.instance = _FixedPathProviderPlatform(
+      documentsPath: fakeDocuments.path,
+      appSupportPath: fakeAppSupport.path,
+    );
+    SharedPreferences.setMockInitialValues({});
+    ServiceRegistry.reset();
+    TtsRegistry.instance.reset();
+  });
+
+  tearDown(() async {
+    ServiceRegistry.reset();
+    TtsRegistry.instance.reset();
+    for (final dir in [fakeDocuments, fakeAppSupport]) {
+      if (await dir.exists()) {
+        await dir.delete(recursive: true);
+      }
+    }
+  });
+
+  test('getActiveTts throws StateError (not a silent wrong-language reuse) '
+      'when a second call requests a different language for the same active '
+      'model, without closing the first synthesizer', () async {
+    final fixtureDownload = _FixtureDownloadService(_fakeBundleBytes);
+    await ServiceRegistry.initialize(downloadService: fixtureDownload);
+    final fakeBackend = _FakeTtsBackend();
+    TtsRegistry.instance.registerAll([fakeBackend]);
+
+    await FlutterGemma.installTts()
+        .fromNetwork('https://example.com/qwen3/')
+        .ofType(TtsModelType.qwen3)
+        .install();
+
+    final synth1 = await FlutterGemma.getActiveTts(language: 'english');
+    expect(fakeBackend.lastConfig?.language, 'english');
+    expect(fakeBackend.createModelCallCount, 1);
+
+    // Same language again -> reuses the singleton (no new backend call,
+    // no error) — the guard must not be overly strict.
+    final synth1Again = await FlutterGemma.getActiveTts(language: 'english');
+    expect(identical(synth1Again, synth1), isTrue);
+    expect(fakeBackend.createModelCallCount, 1);
+
+    // Different language, SAME active model, WITHOUT closing first ->
+    // must fail loud. Before the fix this returned synth1 (English)
+    // silently; after the fix it throws instead.
+    await expectLater(
+      FlutterGemma.getActiveTts(language: 'french'),
+      throwsA(isA<StateError>()),
+    );
+    // The rejected request must not have built a second synthesizer —
+    // this is a fail-FAST guard, not a fallback that still constructs
+    // something wrong.
+    expect(fakeBackend.createModelCallCount, 1);
+
+    // After the caller closes the existing synthesizer, a new language is
+    // allowed and actually rebuilds against the new language.
+    await synth1.close();
+    final synth2 = await FlutterGemma.getActiveTts(language: 'french');
+    expect(fakeBackend.lastConfig?.language, 'french');
+    expect(fakeBackend.createModelCallCount, 2);
+    expect(identical(synth2, synth1), isFalse);
+  });
+}
+
+class _FakeTtsBackend implements TtsBackendProvider {
+  RuntimeConfig? lastConfig;
+  int createModelCallCount = 0;
+
+  @override
+  String get name => 'FakeTTS';
+
+  @override
+  int get priority => 0;
+
+  @override
+  bool canHandle(TtsModelSpec spec) => true;
+
+  @override
+  Future<SpeechSynthesizer> createModel(
+    TtsModelSpec spec,
+    RuntimeConfig config,
+  ) async {
+    createModelCallCount++;
+    lastConfig = config;
+    return _FakeSpeechSynthesizer();
+  }
+}
+
+class _FakeSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
+  @override
+  int get sampleRate => 24000;
+
+  @override
+  Future<Uint8List> synthesize(String text) async => Uint8List(4);
+
+  @override
+  Future<void> close() async {
+    fireCloseListeners();
+  }
+}
+
+/// PathProviderPlatform stub that returns fixed, distinct paths for
+/// Documents and ApplicationSupport (mirrors
+/// test/core/api/install_identity_namespacing_test.dart).
+class _FixedPathProviderPlatform extends PathProviderPlatform {
+  final String documentsPath;
+  final String appSupportPath;
+
+  _FixedPathProviderPlatform({
+    required this.documentsPath,
+    required this.appSupportPath,
+  });
+
+  @override
+  Future<String?> getApplicationDocumentsPath() async => documentsPath;
+
+  @override
+  Future<String?> getApplicationSupportPath() async => appSupportPath;
+
+  @override
+  Future<String?> getTemporaryPath() async => Directory.systemTemp.path;
+}
+
+/// A real (non-mock) DownloadService fake that writes [bytes] to whatever
+/// targetPath it's asked to download to, instead of making a real HTTP
+/// request (mirrors install_identity_namespacing_test.dart's
+/// _FixtureDownloadService).
+class _FixtureDownloadService implements DownloadService {
+  final Uint8List bytes;
+  _FixtureDownloadService(this.bytes);
+
+  @override
+  Future<void> download(
+    String url,
+    String targetPath, {
+    String? token,
+    CancelToken? cancelToken,
+  }) async {
+    await File(targetPath).writeAsBytes(bytes);
+  }
+
+  @override
+  Stream<int> downloadWithProgress(
+    String url,
+    String targetPath, {
+    String? token,
+    int maxRetries = 10,
+    CancelToken? cancelToken,
+    bool? foreground,
+  }) async* {
+    await File(targetPath).writeAsBytes(bytes);
+    yield 100;
+  }
+}
diff --git a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
index 6b62b229..d7a12c64 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
@@ -18,7 +18,8 @@ import 'package:flutter_gemma/flutter_gemma_interface.dart'
     show SpeechSynthesizer;
 
 import '../model/tts_model_profile.dart';
-import '../qwen3/qwen3_languages.dart' show assertQwen3LanguageSupported;
+import '../qwen3/qwen3_languages.dart'
+    show assertQwen3LanguageSupported, normalizeQwen3Language;
 import 'tts_worker.dart';
 
 /// Signature for the `onClose` callback. Same name Flutter uses.
@@ -49,7 +50,12 @@ class LiteRtSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
   /// [TtsPipelineKind.qwen3ArCodec], [language] is validated against
   /// `qwen3SupportedLanguages` (`qwen3_languages.dart`) and this throws
   /// [ArgumentError] for an unknown value BEFORE spawning the worker —
-  /// fail-fast, ahead of the ~1.9 GB model load (Task 5.4).
+  /// fail-fast, ahead of the ~1.9 GB model load (Task 5.4). Once validated,
+  /// [language] is normalized to lowercase (`normalizeQwen3Language`) so the
+  /// whole downstream pipeline (the worker, `Qwen3TtsCore.synthesizePcm16`,
+  /// `Qwen3Prompt.build`'s case-SENSITIVE `'auto'` comparison) sees one
+  /// consistent value — `'Auto'`/`'AUTO'` are accepted here exactly like
+  /// `'auto'`, not just at validation time.
   ///
   /// [voice] is a forward-compat speaker x-vector override (`[1024]`,
   /// Qwen3-only): when non-null it replaces the bundle's single demo voice
@@ -67,14 +73,16 @@ class LiteRtSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
     Float32List? voice,
     VoidCallback? onClose,
   }) async {
+    var effectiveLanguage = language;
     if (profile.pipeline == TtsPipelineKind.qwen3ArCodec) {
       assertQwen3LanguageSupported(language);
+      effectiveLanguage = normalizeQwen3Language(language);
     }
     final worker = await TtsWorker.spawn(
       profile: profile,
       artifactPaths: artifactPaths,
       backend: preferredBackend,
-      language: language,
+      language: effectiveLanguage,
       voice: voice,
     );
     return LiteRtSpeechSynthesizer._(worker, onClose ?? () {});
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
index f8ccf945..8f3df8d6 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
@@ -58,3 +58,18 @@ void assertQwen3LanguageSupported(String language) {
     );
   }
 }
+
+/// Canonicalizes an already-[assertQwen3LanguageSupported]-validated
+/// [language] to the lowercase form every downstream consumer expects.
+///
+/// `assertQwen3LanguageSupported`'s membership check is case-insensitive
+/// (`language.toLowerCase()`), but `Qwen3Prompt.build`'s `'auto'` branch
+/// compares case-SENSITIVELY (`language == 'auto'`; its non-`'auto'` branch
+/// already lowercases via `languageIds[language.toLowerCase()]`). Without
+/// normalizing once here, `'Auto'`/`'AUTO'` would pass validation at
+/// `LiteRtSpeechSynthesizer.create` but then miss `Qwen3Prompt.build`'s
+/// `'auto'` comparison and throw `ArgumentError` AFTER the ~1.9 GB model
+/// load, at the first `synthesize` call — defeating create-time fail-fast
+/// for exactly that value (Task 5.4 review, bundled fix). Call this once,
+/// at the `create` boundary, immediately after validation succeeds.
+String normalizeQwen3Language(String language) => language.toLowerCase();
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart
index 393de7e9..20c24e77 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_language_test.dart
@@ -22,6 +22,15 @@
 // (`@Tags(['qwen3-artifacts'])`), whose default-voice behavior Task 5.4
 // leaves unchanged (`TtsWorker`'s `voice` override is opt-in and defaults to
 // null, i.e. the pre-existing `readNpyF32(demoVoicePath)` path).
+//
+// Bundled fix (review round 1): `assertQwen3LanguageSupported`'s membership
+// check is case-insensitive, but `Qwen3Prompt.build`'s `'auto'` branch
+// compares case-SENSITIVELY — so `'Auto'`/`'AUTO'` used to pass validation
+// at `create` but throw `ArgumentError` AFTER the ~1.9 GB model load, at the
+// first `synthesize` call. `create` now normalizes via
+// `normalizeQwen3Language` right after validation; the tests below cover
+// both the normalizer directly and `create`'s acceptance of mixed-case
+// `'auto'` (still without spawning a real worker).
 
 import 'package:flutter_gemma_speech/src/litert/litert_speech_synthesizer.dart';
 import 'package:flutter_gemma_speech/src/model/tts_model_profile.dart';
@@ -47,6 +56,32 @@ void main() {
       expect(() => assertQwen3LanguageSupported('German'), returnsNormally);
       expect(() => assertQwen3LanguageSupported('GERMAN'), returnsNormally);
     });
+
+    test("accepts 'Auto' and 'AUTO' (case-insensitive) same as 'auto'", () {
+      expect(() => assertQwen3LanguageSupported('Auto'), returnsNormally);
+      expect(() => assertQwen3LanguageSupported('AUTO'), returnsNormally);
+    });
+
+    test('an unknown mixed-case language still throws ArgumentError', () {
+      expect(
+        () => assertQwen3LanguageSupported('Klingon'),
+        throwsArgumentError,
+      );
+    });
+  });
+
+  group('normalizeQwen3Language', () {
+    test("lowercases 'Auto'/'AUTO' to 'auto'", () {
+      expect(normalizeQwen3Language('Auto'), 'auto');
+      expect(normalizeQwen3Language('AUTO'), 'auto');
+      expect(normalizeQwen3Language('auto'), 'auto');
+    });
+
+    test('lowercases every supported language name', () {
+      for (final lang in qwen3SupportedLanguages) {
+        expect(normalizeQwen3Language(lang.toUpperCase()), lang);
+      }
+    });
   });
 
   group('languageIds / qwen3SupportedLanguages (single source of truth)', () {
@@ -75,5 +110,36 @@ void main() {
         throwsArgumentError,
       );
     });
+
+    test(
+      "accepts 'Auto' and 'AUTO' the same as 'auto' — validation never "
+      'rejects them as ArgumentError (they still fail later, from the '
+      'empty artifactPaths, exactly like a real "auto" request would)',
+      () async {
+        for (final lang in ['Auto', 'AUTO', 'auto']) {
+          await expectLater(
+            LiteRtSpeechSynthesizer.create(
+              profile: const TtsModelProfile.qwen3(),
+              artifactPaths: const {},
+              language: lang,
+            ),
+            throwsA(isNot(isA<ArgumentError>())),
+            reason: "language: '$lang' must pass validation",
+          );
+        }
+      },
+    );
+
+    test('an unknown mixed-case language still throws ArgumentError at '
+        'create (not just at assertQwen3LanguageSupported)', () async {
+      await expectLater(
+        LiteRtSpeechSynthesizer.create(
+          profile: const TtsModelProfile.qwen3(),
+          artifactPaths: const {},
+          language: 'Klingon',
+        ),
+        throwsArgumentError,
+      );
+    });
   });
 }

From 999485df197a0557903509a9e6a4d02a47aa4ead Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 03:45:30 +0500
Subject: [PATCH 21/30] feat(qwen3): device gate + CHANGELOG
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Adds qwen3_tts_test.dart: installs Qwen3-TTS from the real public HF
URL, synthesizes english, closes, switches to german, and asserts the
output actually differs — the on-device install->getModelFilePaths->
Qwen3TtsCore.load path the artifact-gated unit tests can't cover since
they build their own artifactPaths.

Device run found a real bug: TtsInstallationBuilder's legacy-file
adoption blindly renamed an unrelated leftover STT tokenizer.json into
the qwen3 slot (its uniqueness check only scans the TTS catalog, not
STT/embedding/inference catalogs sharing the same generic basename),
corrupting the BPE vocab. Not fixed here (needs a design call); local
test-machine state cleaned up to get a real signal on the rest of the
pipeline, which now passes: english/german PCM differ, RMS/duration
plausible, 24 kHz confirmed both ways.

CHANGELOG: qwen3-tts entries in speech (0.5.0) and core (1.5.2).
---
 packages/flutter_gemma/CHANGELOG.md           |   3 +
 .../integration_test/qwen3_tts_test.dart      | 157 ++++++++++++++++++
 packages/flutter_gemma_speech/CHANGELOG.md    |   3 +
 3 files changed, 163 insertions(+)
 create mode 100644 packages/flutter_gemma/example/integration_test/qwen3_tts_test.dart

diff --git a/packages/flutter_gemma/CHANGELOG.md b/packages/flutter_gemma/CHANGELOG.md
index 3f6c0beb..ff10221a 100644
--- a/packages/flutter_gemma/CHANGELOG.md
+++ b/packages/flutter_gemma/CHANGELOG.md
@@ -1,3 +1,6 @@
+## 1.5.2
+- Add TtsModelType.qwen3.
+
 ## 1.5.1
 - fix: namespace companion install files (tokenizers, TTS bundle aux) per model, fixing STT/embedding tokenizer collisions.
 - fix: migrate legacy (pre-namespacing) tokenizer installs on restore, so existing STT/embedding models keep working after upgrade.
diff --git a/packages/flutter_gemma/example/integration_test/qwen3_tts_test.dart b/packages/flutter_gemma/example/integration_test/qwen3_tts_test.dart
new file mode 100644
index 00000000..fc69d2ce
--- /dev/null
+++ b/packages/flutter_gemma/example/integration_test/qwen3_tts_test.dart
@@ -0,0 +1,157 @@
+// On-device Qwen3-TTS e2e — installs Qwen3-TTS from HuggingFace through the
+// REAL public flow (initialize -> installTts -> getActiveTts -> synthesize),
+// exercising the plain-basename manifest -> getModelFilePaths ->
+// Qwen3TtsCore.load consistency ON DEVICE (the artifact-gated unit tests
+// build their own artifactPaths by directory scan, so they never touch the
+// install path itself).
+//
+// Unlike `tts_matcha_test.dart` (byte-exact against a committed golden,
+// fixed CFM seed), this test asserts PLAUSIBILITY only: the runtime uses the
+// default int4 talker with `doSample: true`, so exact bytes are not
+// reproducible across runs. The byte-exact / corr~=1.0 oracle for the shared
+// AR pipeline lives in the fp32-greedy unit test (`qwen3_synthesize_test.dart`,
+// artifact-gated, not a device test).
+//
+// Also asserts language selection actually changes the output end to end:
+// synthesizing the same text with `language: 'german'` after closing the
+// `'english'` synthesizer (required by the fail-loud language-cache guard —
+// see Task 5.4) must NOT produce byte-identical audio to the english pass.
+//
+// The full 9-file bundle is ~1.9 GB; this test can take tens of minutes on a
+// slow connection. Run: cd packages/flutter_gemma/example && \
+//   flutter test integration_test/qwen3_tts_test.dart -d macos
+import 'dart:math' as math;
+import 'dart:typed_data';
+
+import 'package:flutter/foundation.dart';
+import 'package:flutter_test/flutter_test.dart';
+import 'package:integration_test/integration_test.dart';
+import 'package:flutter_gemma/flutter_gemma.dart'
+    show FlutterGemma, TtsModelType;
+import 'package:flutter_gemma_speech/flutter_gemma_speech.dart'
+    show LiteRtTtsBackend;
+
+const _modelUrl =
+    'https://huggingface.co/litert-community/Qwen3-TTS-12Hz-0.6B-Base/resolve/main/';
+const _text = 'Hello from on device text to speech.';
+
+double _rms(Uint8List pcm) {
+  final samples = Int16List.sublistView(pcm);
+  if (samples.isEmpty) return 0;
+  var sumSquares = 0.0;
+  for (final s in samples) {
+    final n = s / 32768.0;
+    sumSquares += n * n;
+  }
+  return math.sqrt(sumSquares / samples.length);
+}
+
+bool _bytesEqual(Uint8List a, Uint8List b) {
+  if (a.length != b.length) return false;
+  for (var i = 0; i < a.length; i++) {
+    if (a[i] != b[i]) return false;
+  }
+  return true;
+}
+
+void main() {
+  IntegrationTestWidgetsFlutterBinding.ensureInitialized();
+
+  testWidgets(
+    'Qwen3-TTS installs from HF, synthesizes plausible english audio, and '
+    'german differs from english',
+    (_) async {
+      await FlutterGemma.initialize(ttsBackends: const [LiteRtTtsBackend()]);
+
+      await FlutterGemma.installTts()
+          .fromNetwork(_modelUrl)
+          .ofType(TtsModelType.qwen3)
+          .install();
+
+      final englishSynth = await FlutterGemma.getActiveTts(language: 'english');
+      Uint8List englishPcm;
+      try {
+        englishPcm = await englishSynth.synthesize(_text);
+
+        expect(englishPcm, isNotEmpty, reason: 'english PCM was empty');
+        expect(englishSynth.sampleRate, 24000);
+
+        final durationSeconds = englishPcm.length / 2 / englishSynth.sampleRate;
+        final rms = _rms(englishPcm);
+
+        debugPrint(
+          'QWEN3-TTS-DEVICE-GATE<<<lang=english pcmBytes=${englishPcm.length} '
+          'durationSeconds=${durationSeconds.toStringAsFixed(4)} '
+          'rms=${rms.toStringAsFixed(4)}>>>',
+        );
+
+        // Plausibility oracle (int4 + doSample:true is not byte-reproducible
+        // across runs/backends): non-silent, non-clipped-garbage, and a
+        // ~7-word sentence should take at least ~1s of audio.
+        expect(
+          durationSeconds,
+          greaterThanOrEqualTo(1.0),
+          reason: 'Synthesized audio implausibly short: ${durationSeconds}s',
+        );
+        expect(
+          rms,
+          inInclusiveRange(0.005, 0.5),
+          reason: 'RMS out of the plausible speech band: $rms',
+        );
+      } finally {
+        // REQUIRED before requesting a different language on the same
+        // active model — the language-cache guard (Task 5.4) throws
+        // StateError otherwise instead of silently reusing the english
+        // synthesizer for a german request.
+        await englishSynth.close();
+      }
+
+      final germanSynth = await FlutterGemma.getActiveTts(language: 'german');
+      try {
+        final germanPcm = await germanSynth.synthesize(_text);
+
+        expect(germanPcm, isNotEmpty, reason: 'german PCM was empty');
+        expect(germanSynth.sampleRate, 24000);
+
+        final durationSeconds = germanPcm.length / 2 / germanSynth.sampleRate;
+        final rms = _rms(germanPcm);
+
+        debugPrint(
+          'QWEN3-TTS-DEVICE-GATE<<<lang=german pcmBytes=${germanPcm.length} '
+          'durationSeconds=${durationSeconds.toStringAsFixed(4)} '
+          'rms=${rms.toStringAsFixed(4)}>>>',
+        );
+
+        expect(
+          durationSeconds,
+          greaterThanOrEqualTo(1.0),
+          reason: 'Synthesized audio implausibly short: ${durationSeconds}s',
+        );
+        expect(
+          rms,
+          inInclusiveRange(0.005, 0.5),
+          reason: 'RMS out of the plausible speech band: $rms',
+        );
+
+        // Language selection actually changes the model's output, end to
+        // end through the public API: german must not equal english either
+        // in length or in bytes (a byte match at equal length would mean
+        // the language control token silently had no effect).
+        final identical =
+            germanPcm.length == englishPcm.length &&
+            _bytesEqual(germanPcm, englishPcm);
+        expect(
+          identical,
+          isFalse,
+          reason:
+              'german synthesis produced byte-identical audio to english '
+              '(pcmBytes=${germanPcm.length} vs ${englishPcm.length}) — '
+              'language selection had no effect',
+        );
+      } finally {
+        await germanSynth.close();
+      }
+    },
+    timeout: const Timeout(Duration(minutes: 90)),
+  );
+}
diff --git a/packages/flutter_gemma_speech/CHANGELOG.md b/packages/flutter_gemma_speech/CHANGELOG.md
index 847e81f7..02374f57 100644
--- a/packages/flutter_gemma_speech/CHANGELOG.md
+++ b/packages/flutter_gemma_speech/CHANGELOG.md
@@ -1,3 +1,6 @@
+## 0.5.0
+- Add Qwen3-TTS (multilingual AR codec-LM, 11 languages) — 2nd selectable TTS family.
+
 ## 0.4.0
 - feat: on-device Whisper-tiny STT (English-only) — log-mel frontend + GPT-2 BPE decode.
 - feat: on-device Parakeet-CTC STT (desktop) — NeMo mel frontend + greedy CTC decode.

From 7d344c4fbc52dcc95bb77a6899fa7630b7156be4 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 11:53:00 +0500
Subject: [PATCH 22/30] fix(qwen3): drop unsafe install-time legacy-file
 adoption + core 1.6.0

TtsInstallationBuilder.install() adopted an on-disk plain
(pre-1.5.1-namespacing) file whenever its basename was unique within the
TTS catalog, with zero content check. Qwen3's tokenizer.json is a
cross-catalog-generic basename, so a leftover STT tokenizer.json could be
silently adopted -> wrong tokenizer. Adoption at install time is removed;
a not-yet-installed manifest file is now always downloaded fresh. The
restore-time migration (MobileModelManager._migrateLegacyCompanionForRestore)
is untouched -- it stays safe because it operates on a single known active
model.

Sibling builders (stt_/embedding_/inference_installation_builder.dart) never
had this pattern -- no changes needed there.

Bump core CHANGELOG header 1.5.2 -> 1.6.0: this branch adds public API
(TtsModelType.qwen3 + RuntimeConfig.language + facade language params),
and a new enum value can break downstream exhaustive switches.
---
 packages/flutter_gemma/CHANGELOG.md           |   2 +-
 .../core/api/tts_installation_builder.dart    |  56 ++-----
 .../install_identity_namespacing_test.dart    | 157 ++++++++++++------
 3 files changed, 119 insertions(+), 96 deletions(-)

diff --git a/packages/flutter_gemma/CHANGELOG.md b/packages/flutter_gemma/CHANGELOG.md
index ff10221a..12323b40 100644
--- a/packages/flutter_gemma/CHANGELOG.md
+++ b/packages/flutter_gemma/CHANGELOG.md
@@ -1,4 +1,4 @@
-## 1.5.2
+## 1.6.0
 - Add TtsModelType.qwen3.
 
 ## 1.5.1
diff --git a/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart b/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
index 5cd726b2..5db95749 100644
--- a/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
+++ b/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
@@ -1,7 +1,6 @@
 import 'package:flutter_gemma/core/utils/gemma_log.dart';
 import 'package:flutter_gemma/core/di/service_registry.dart';
 import 'package:flutter_gemma/core/model_management/model_specs.dart';
-import 'package:flutter_gemma/core/services/model_repository.dart' as repo;
 import 'package:flutter_gemma/flutter_gemma.dart';
 
 /// Fluent builder for TTS (text-to-speech) model installation.
@@ -106,61 +105,26 @@ class TtsInstallationBuilder {
 
     final registry = ServiceRegistry.instance;
     final repository = registry.modelRepository;
-    final fileSystem = registry.fileSystemService;
     final handlerRegistry = registry.sourceHandlerRegistry;
 
-    final manifest = ttsModelType.manifest;
-    // Only a bundle basename that is UNIQUE across the ENTIRE TTS catalog is
-    // safe to adopt from a pre-refactor flat install: a shared basename (e.g. a
-    // generic `config.json`) carries no type marker, so blindly adopting it
-    // could hand THIS model another TTS model's file — the exact collision the
-    // namespacing refactor fixes (see FileSystemService.adoptLegacyFile's
-    // contract). Today matcha is the only type, so every basename is unique;
-    // this guard keeps the adoption correct the moment a second TTS model
-    // shares a basename (that basename then falls through to a fresh download).
-    final catalogBasenameCounts = <String, int>{};
-    for (final type in TtsModelType.values) {
-      final List<String> typeManifest;
-      try {
-        typeManifest = type.manifest;
-      } on UnimplementedError {
-        // A not-yet-wired TTS type has no installed files, so it can't own a
-        // colliding plain file — skip it rather than let its manifest getter
-        // throw.
-        continue;
-      }
-      for (final fn in typeManifest) {
-        catalogBasenameCounts[fn] = (catalogBasenameCounts[fn] ?? 0) + 1;
-      }
-    }
-
+    // NOTE: install-time legacy-file adoption (renaming an on-disk
+    // pre-1.5.1-namespacing plain file onto the namespaced identity) was
+    // removed here — a bundle basename can be unique within the TTS catalog
+    // yet still collide with a plain file left behind by an STT/embedding
+    // install (e.g. Qwen3's `tokenizer.json`), and adoption has no way to
+    // verify the on-disk file actually belongs to this model (no size/hash
+    // check available). Every not-yet-installed manifest file is always
+    // (re-)downloaded fresh. The safe migration path for genuinely-legacy TTS
+    // installs is restore-time, in
+    // MobileModelManager._migrateLegacyCompanionForRestore.
     final files = spec.files;
     var done = 0;
     for (var i = 0; i < files.length; i++) {
       _cancelToken?.throwIfCancelled();
       final file = files[i];
-      final legacyBasename = manifest[i];
-      final adoptable = (catalogBasenameCounts[legacyBasename] ?? 0) == 1;
 
       if (await repository.isInstalled(file.filename)) {
         gemmaLog('ℹ️  TTS bundle file already installed: ${file.filename}');
-      } else if (adoptable &&
-          await fileSystem.adoptLegacyFile(legacyBasename, file.filename)) {
-        gemmaLog(
-          '♻️  Adopted legacy TTS bundle file: $legacyBasename -> ${file.filename}',
-        );
-        final newPath = await fileSystem.getWriteTargetPath(file.filename);
-        final sizeBytes = await fileSystem.getFileSize(newPath);
-        await repository.saveModel(
-          repo.ModelInfo(
-            id: file.filename,
-            source: file.source,
-            installedAt: DateTime.now(),
-            sizeBytes: sizeBytes,
-            type: repo.ModelType.tts,
-            hasLoraWeights: false,
-          ),
-        );
       } else {
         gemmaLog('📥 Installing TTS bundle file: ${file.filename}...');
         final handler = handlerRegistry.getHandler(file.source);
diff --git a/packages/flutter_gemma/test/core/api/install_identity_namespacing_test.dart b/packages/flutter_gemma/test/core/api/install_identity_namespacing_test.dart
index 8c1a1723..d3cd6208 100644
--- a/packages/flutter_gemma/test/core/api/install_identity_namespacing_test.dart
+++ b/packages/flutter_gemma/test/core/api/install_identity_namespacing_test.dart
@@ -216,62 +216,121 @@ void main() {
     );
   });
 
-  group('Task 6: migration fallback-probe (unique-basename files only)', () {
-    test(
-      'an old flat TTS bundle file is adopted in place — no re-download',
-      () async {
-        final fixtureDownload = _FixtureDownloadService(_fakeCompanionBytes);
-        await ServiceRegistry.initialize(downloadService: fixtureDownload);
+  group('Task 6 (superseded 2026-08-04, whole-branch review): TTS install-time '
+      'adoption REMOVED — a not-yet-installed manifest file is always '
+      'downloaded fresh, never adopted from an on-disk plain file, even when '
+      'its basename is unique within the TTS catalog. Adoption at install time '
+      'could not distinguish "an old flat file this exact model installed '
+      "before namespacing shipped\" from \"a same-named file some OTHER "
+      "model's catalog (e.g. an STT tokenizer.json) happened to leave "
+      'behind" — no size/hash check was available to tell them apart. The '
+      'only remaining (safe) adoption path is restore-time, in '
+      'MobileModelManager._migrateLegacyCompanionForRestore, which operates on '
+      'a single KNOWN active model so the ambiguity cannot occur.', () {
+    test('an old flat TTS bundle file at the pre-refactor path is left '
+        'untouched — install() downloads the namespaced file fresh instead '
+        'of adopting it', () async {
+      final fixtureDownload = _FixtureDownloadService(_fakeCompanionBytes);
+      await ServiceRegistry.initialize(downloadService: fixtureDownload);
 
-        // Resolve the storage dir via the same FileSystemService the
-        // builder/adopt probe use rather than hardcoding fakeDocuments.path
-        // — on desktop hosts (this test typically runs as a native VM test)
-        // writes land under ApplicationSupport/flutter_gemma/, not
-        // Documents; on mobile they land directly under Documents.
-        final storageDir = await ServiceRegistry.instance.fileSystemService
-            .getModelStorageDirectory();
+      // Resolve the storage dir via the same FileSystemService the
+      // builder uses rather than hardcoding fakeDocuments.path — on
+      // desktop hosts (this test typically runs as a native VM test)
+      // writes land under ApplicationSupport/flutter_gemma/, not
+      // Documents; on mobile they land directly under Documents.
+      final storageDir = await ServiceRegistry.instance.fileSystemService
+          .getModelStorageDirectory();
 
-        // Pre-seed ONE bundle member at its OLD, pre-refactor flat path —
-        // simulating a matcha install from before this refactor shipped.
-        final oldPath = path.join(storageDir, 'matcha_textenc_fp16.tflite');
-        await File(oldPath).writeAsBytes([7, 7, 7, 7]);
+      // Pre-seed ONE bundle member at its OLD, pre-refactor flat path —
+      // simulating a matcha install from before the namespacing refactor
+      // shipped. Its basename is unique within the TTS catalog, so
+      // pre-fix this WOULD have been adopted.
+      final oldPath = path.join(storageDir, 'matcha_textenc_fp16.tflite');
+      await File(oldPath).writeAsBytes([7, 7, 7, 7]);
 
-        await FlutterGemma.installTts()
-            .fromNetwork('https://example.com/matcha/')
-            .ofType(TtsModelType.matcha)
-            .install();
+      await FlutterGemma.installTts()
+          .fromNetwork('https://example.com/matcha/')
+          .ofType(TtsModelType.matcha)
+          .install();
 
-        // Adopted in place: old path gone, new namespaced path holds the
-        // ORIGINAL bytes (proves it was renamed, not re-downloaded — a
-        // re-download would have overwritten it with _fakeCompanionBytes).
-        expect(await File(oldPath).exists(), isFalse);
-        final newPath = path.join(
-          storageDir,
-          'matcha__matcha_textenc_fp16.tflite',
-        );
-        expect(await File(newPath).readAsBytes(), [7, 7, 7, 7]);
-        expect(
-          fixtureDownload.requestedTargetPaths.contains(newPath),
-          isFalse,
-          reason: 'the adopted file must not have been (re-)downloaded',
-        );
+      // NOT adopted: the old flat file is left exactly as it was...
+      expect(await File(oldPath).readAsBytes(), [7, 7, 7, 7]);
+      // ...and the namespaced file was downloaded fresh (fixture bytes),
+      // not renamed from the old path (which would carry [7,7,7,7]).
+      final newPath = path.join(
+        storageDir,
+        'matcha__matcha_textenc_fp16.tflite',
+      );
+      expect(await File(newPath).readAsBytes(), _fakeCompanionBytes);
+      expect(
+        fixtureDownload.requestedTargetPaths.contains(newPath),
+        isTrue,
+        reason:
+            'a not-yet-installed bundle file must always be '
+            'downloaded, never adopted',
+      );
 
-        // Every OTHER bundle member (no old file seeded) was downloaded
-        // normally under its namespaced name.
-        final otherPath = path.join(storageDir, 'matcha__config.json');
-        expect(
-          fixtureDownload.requestedTargetPaths.contains(otherPath),
-          isTrue,
-        );
+      // Every OTHER bundle member (no old file seeded) was also
+      // downloaded normally under its namespaced name.
+      final otherPath = path.join(storageDir, 'matcha__config.json');
+      expect(fixtureDownload.requestedTargetPaths.contains(otherPath), isTrue);
 
-        final repository = ServiceRegistry.instance.modelRepository;
-        expect(
-          await repository.isInstalled('matcha__matcha_textenc_fp16.tflite'),
-          isTrue,
-        );
-      },
-    );
+      final repository = ServiceRegistry.instance.modelRepository;
+      expect(
+        await repository.isInstalled('matcha__matcha_textenc_fp16.tflite'),
+        isTrue,
+      );
+    });
+
+    test('a FOREIGN plain file left by another catalog (e.g. an STT '
+        'tokenizer.json) is NEVER adopted into a Qwen3 TTS install — the '
+        'exact collision this fix closes', () async {
+      final fixtureDownload = _FixtureDownloadService(_fakeCompanionBytes);
+      await ServiceRegistry.initialize(downloadService: fixtureDownload);
+
+      final storageDir = await ServiceRegistry.instance.fileSystemService
+          .getModelStorageDirectory();
+
+      // Pre-seed a plain `tokenizer.json` at the real storage location —
+      // standing in for a leftover Moonshine/Whisper/Parakeet STT
+      // tokenizer. Distinct byte content from the qwen3 fixture bytes so
+      // adoption-vs-download is unambiguous.
+      final foreignPath = path.join(storageDir, 'tokenizer.json');
+      await File(foreignPath).writeAsBytes([1, 2, 3, 4, 5]);
+
+      final installation = await FlutterGemma.installTts()
+          .fromNetwork(
+            'https://huggingface.co/litert-community/'
+            'Qwen3-TTS-12Hz-0.6B-Base/resolve/main/',
+          )
+          .ofType(TtsModelType.qwen3)
+          .install();
+
+      // The foreign file is completely untouched.
+      expect(await File(foreignPath).readAsBytes(), [1, 2, 3, 4, 5]);
+
+      // qwen3's own tokenizer.json was downloaded fresh under ITS
+      // namespaced identity, carrying the fixture bytes — not the
+      // foreign file's bytes.
+      final qwen3TokenizerPath = path.join(storageDir, 'qwen3__tokenizer.json');
+      expect(await File(qwen3TokenizerPath).readAsBytes(), _fakeCompanionBytes);
+      expect(
+        fixtureDownload.requestedTargetPaths.contains(qwen3TokenizerPath),
+        isTrue,
+      );
+
+      final repository = ServiceRegistry.instance.modelRepository;
+      expect(await repository.isInstalled('qwen3__tokenizer.json'), isTrue);
+      // The plain foreign key was never claimed by this install.
+      expect(await repository.isInstalled('tokenizer.json'), isFalse);
+
+      // The installed identity is qwen3's, not the foreign file's.
+      expect(installation.spec.ttsModelType, TtsModelType.qwen3);
+    });
+  });
 
+  group('Task 6b: STT install-time collision guard (unaffected by the TTS '
+      'adoption removal — STT install() never adopted at all)', () {
     test(
       'a colliding companion (tokenizer) NEVER triggers migration — it always '
       'installs fresh under the namespaced key (the mis-adoption guard)',

From a6ee64aa03633bb12d6607244d68c8da8ed73053 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 12:08:45 +0500
Subject: [PATCH 23/30] chore(flutter_gemma): bump 1.5.1 -> 1.5.2

---
 packages/flutter_gemma/CHANGELOG.md              | 2 +-
 packages/flutter_gemma/ios/flutter_gemma.podspec | 2 +-
 packages/flutter_gemma/pubspec.yaml              | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/packages/flutter_gemma/CHANGELOG.md b/packages/flutter_gemma/CHANGELOG.md
index 12323b40..ff10221a 100644
--- a/packages/flutter_gemma/CHANGELOG.md
+++ b/packages/flutter_gemma/CHANGELOG.md
@@ -1,4 +1,4 @@
-## 1.6.0
+## 1.5.2
 - Add TtsModelType.qwen3.
 
 ## 1.5.1
diff --git a/packages/flutter_gemma/ios/flutter_gemma.podspec b/packages/flutter_gemma/ios/flutter_gemma.podspec
index de1fdeb2..9269b776 100644
--- a/packages/flutter_gemma/ios/flutter_gemma.podspec
+++ b/packages/flutter_gemma/ios/flutter_gemma.podspec
@@ -4,7 +4,7 @@
 #
 Pod::Spec.new do |s|
   s.name             = 'flutter_gemma'
-  s.version          = '1.5.1'
+  s.version          = '1.5.2'
   s.summary          = 'Flutter plugin for running Gemma and other LLMs locally on iOS.'
   s.description      = <<-DESC
 Core runtime for running Gemma 4, Gemma3n, Gemma 3, FastVLM, Qwen3,
diff --git a/packages/flutter_gemma/pubspec.yaml b/packages/flutter_gemma/pubspec.yaml
index 83ef85fa..df0c6ce4 100644
--- a/packages/flutter_gemma/pubspec.yaml
+++ b/packages/flutter_gemma/pubspec.yaml
@@ -1,6 +1,6 @@
 name: flutter_gemma
 description: "Run Gemma and other LLMs on-device in Flutter (Android, iOS, Web, Desktop). Multimodal vision/audio, function calling, thinking mode, GPU, embeddings, RAG."
-version: 1.5.1
+version: 1.5.2
 resolution: workspace
 homepage: https://fluttergemma.dev
 repository: https://github.com/DenisovAV/flutter_gemma

From 96990f72f1ed6f2a8d1f8809c7557258a8226cc8 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 12:23:44 +0500
Subject: [PATCH 24/30] chore(flutter_gemma_speech): bump 0.4.0 -> 0.4.1

---
 packages/flutter_gemma_speech/CHANGELOG.md | 2 +-
 packages/flutter_gemma_speech/pubspec.yaml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/packages/flutter_gemma_speech/CHANGELOG.md b/packages/flutter_gemma_speech/CHANGELOG.md
index 02374f57..bdde8746 100644
--- a/packages/flutter_gemma_speech/CHANGELOG.md
+++ b/packages/flutter_gemma_speech/CHANGELOG.md
@@ -1,4 +1,4 @@
-## 0.5.0
+## 0.4.1
 - Add Qwen3-TTS (multilingual AR codec-LM, 11 languages) — 2nd selectable TTS family.
 
 ## 0.4.0
diff --git a/packages/flutter_gemma_speech/pubspec.yaml b/packages/flutter_gemma_speech/pubspec.yaml
index a11e85ce..aaa82c52 100644
--- a/packages/flutter_gemma_speech/pubspec.yaml
+++ b/packages/flutter_gemma_speech/pubspec.yaml
@@ -1,6 +1,6 @@
 name: flutter_gemma_speech
 description: "On-device speech (STT + TTS) for flutter_gemma via the LiteRT C API + dart:ffi. Opt-in Stt/TtsBackendProvider."
-version: 0.4.0
+version: 0.4.1
 homepage: https://fluttergemma.dev
 repository: https://github.com/DenisovAV/flutter_gemma/tree/main/packages/flutter_gemma_speech
 topics: [speech, stt, gemma, litert, on-device]

From 790220a4ee8351eae37d2d907ad9119005417002 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 13:06:42 +0500
Subject: [PATCH 25/30] =?UTF-8?q?fix(speech):=20review=20fixes=20A=20?=
 =?UTF-8?q?=E2=80=94=20dep=20pin,=20maxFrames=20warning,=20load-time=20gua?=
 =?UTF-8?q?rds?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

- pin flutter_gemma_speech's core dep to ^1.5.2 (TtsModelType.qwen3 + RuntimeConfig.language need it)
- warn when Qwen3 TTS hits maxFrames before EOS (truncated output signal, no behavior change)
- throw on a GraphInput payload length mismatch instead of silently zero-padding the tensor
- fail loud at load time if codecChunk doesn't exceed the codec decode loop's left-context
- test that every wired TTS manifest uses only plain basenames; de-duplicate urlSuffixFor's table set
- normalize the TTS language reuse-guard (default + lowercase) so null/'english'/'English' don't spuriously collide
---
 packages/flutter_gemma/example/pubspec.lock   |  4 +-
 .../types/tts_model_spec.dart                 | 29 ++++++----
 .../lib/desktop/flutter_gemma_desktop.dart    | 36 +++++++++---
 .../lib/mobile/flutter_gemma_mobile.dart      | 35 +++++++++---
 .../test/core/tts_model_spec_test.dart        | 22 ++++++++
 .../mobile/tts_language_singleton_test.dart   | 55 +++++++++++++++++++
 .../lib/src/litert/litert_graph.dart          | 39 ++++++++++---
 .../lib/src/qwen3/qwen3_tts_core.dart         | 35 +++++++++++-
 packages/flutter_gemma_speech/pubspec.yaml    |  2 +-
 9 files changed, 215 insertions(+), 42 deletions(-)

diff --git a/packages/flutter_gemma/example/pubspec.lock b/packages/flutter_gemma/example/pubspec.lock
index e20f00b0..8bec4fdd 100644
--- a/packages/flutter_gemma/example/pubspec.lock
+++ b/packages/flutter_gemma/example/pubspec.lock
@@ -241,7 +241,7 @@ packages:
       path: ".."
       relative: true
     source: path
-    version: "1.5.1"
+    version: "1.5.2"
   flutter_gemma_agent:
     dependency: "direct main"
     description:
@@ -297,7 +297,7 @@ packages:
       path: "../../flutter_gemma_speech"
       relative: true
     source: path
-    version: "0.4.0"
+    version: "0.4.1"
   flutter_inappwebview:
     dependency: transitive
     description:
diff --git a/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart b/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart
index 034d7761..2ca9bf44 100644
--- a/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart
+++ b/packages/flutter_gemma/lib/core/model_management/types/tts_model_spec.dart
@@ -6,6 +6,20 @@ part of '../model_specs.dart';
 /// (fail-loud until wired).
 enum TtsModelType { matcha, supertonic, kokoro, qwen3 }
 
+/// [TtsModelType.qwen3]'s 4 embedding-table bundle members — the SINGLE
+/// source of truth for which manifest basenames live under the HF repo's
+/// `tables/` subdirectory. Spread into [TtsModelTypeManifest.manifest]'s
+/// qwen3 entry AND consulted by [TtsModelTypeManifest.urlSuffixFor], so the
+/// two can never desync (a prior version hardcoded this set a second time in
+/// [TtsModelTypeManifest.urlSuffixFor]; a rename here used to require
+/// remembering to update both places).
+const _qwen3TableFiles = [
+  'text_embedding_fp16.npy',
+  'text_projection_fp32.npz',
+  'codec_embedding_fp32.npy',
+  'mtp_embeddings_fp16.npy',
+];
+
 /// The filenames a given TTS model needs, installed together as a bundle from
 /// one source. Fail-loud for unwired families.
 extension TtsModelTypeManifest on TtsModelType {
@@ -42,10 +56,7 @@ extension TtsModelTypeManifest on TtsModelType {
       'mtp_fp32.tflite',
       'codec_decoder_fp32.tflite',
       'tokenizer.json',
-      'text_embedding_fp16.npy',
-      'text_projection_fp32.npz',
-      'codec_embedding_fp32.npy',
-      'mtp_embeddings_fp16.npy',
+      ..._qwen3TableFiles,
       'demo_speaker.npy',
     ],
     _ => throw UnimplementedError(
@@ -66,13 +77,9 @@ extension TtsModelTypeManifest on TtsModelType {
   /// intends). A no-op (identity) for every other [TtsModelType].
   String urlSuffixFor(String plainFilename) {
     if (this != TtsModelType.qwen3) return plainFilename;
-    const tableFiles = {
-      'text_embedding_fp16.npy',
-      'text_projection_fp32.npz',
-      'codec_embedding_fp32.npy',
-      'mtp_embeddings_fp16.npy',
-    };
-    if (tableFiles.contains(plainFilename)) return 'tables/$plainFilename';
+    if (_qwen3TableFiles.contains(plainFilename)) {
+      return 'tables/$plainFilename';
+    }
     if (plainFilename == 'demo_speaker.npy') return 'voices/$plainFilename';
     return plainFilename;
   }
diff --git a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
index 464611c9..648f42ef 100644
--- a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
+++ b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
@@ -35,6 +35,18 @@ import '../mobile/flutter_gemma_mobile.dart' show MobileModelManager;
 
 import '../core/model_management/constants/preferences_keys.dart';
 
+/// Normalizes a `createTtsModel`/`getActiveTts` `language` argument for the
+/// same-model reuse guard's store/compare — defaults `null` to `'english'`
+/// (mirrors `LiteRtTtsBackend.createModel`'s `config.language ?? 'english'`)
+/// and lowercases so `null`, `'english'`, and `'English'` all compare equal
+/// (they build the SAME synthesizer either way — `Qwen3Prompt.build` already
+/// lowercases the language it's given). Without this, storing/comparing the
+/// raw argument tripped a spurious `StateError` for effectively-identical
+/// requests (e.g. `getActiveTts()` then `getActiveTts(language: 'english')`).
+/// Duplicated from `flutter_gemma_mobile.dart` (same shape, separate shell).
+String _normalizeTtsLanguage(String? language) =>
+    (language ?? 'english').toLowerCase();
+
 /// Desktop implementation of FlutterGemma plugin
 ///
 /// Uses dart:ffi to communicate directly with LiteRT-LM C API
@@ -81,10 +93,13 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
   SpeechSynthesizer? _initializedTtsModel;
   TtsModelSpec?
   _lastActiveTtsSpec; // Track which spec was used to create _initializedTtsModel
-  // The `language` the active singleton was built with (raw, as received —
-  // not defaulted). Reusing the singleton for a DIFFERENT language would
-  // silently emit wrong-language audio with no error (Task 5.4 review,
-  // Important #1) — see the same-model branch in createTtsModel below.
+  // The `language` the active singleton was built with, NORMALIZED
+  // ([_normalizeTtsLanguage] — defaulted + lowercased) so a same-effective-
+  // language request compared raw-to-raw (e.g. null vs. 'english', or
+  // 'English' vs. 'english') doesn't spuriously trip the guard below.
+  // Reusing the singleton for a genuinely DIFFERENT language would silently
+  // emit wrong-language audio with no error (Task 5.4 review, Important #1)
+  // — see the same-model branch in createTtsModel below.
   String? _lastActiveTtsLanguage;
 
   @override
@@ -530,17 +545,20 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
         _lastActiveTtsSpec = null;
         _lastActiveTtsLanguage = null;
         await old?.close();
-      } else if (language != _lastActiveTtsLanguage) {
+      } else if (_normalizeTtsLanguage(language) != _lastActiveTtsLanguage) {
         // Same model, but a DIFFERENT language was requested — reusing the
         // singleton here would silently emit WRONG-LANGUAGE audio with no
         // error (Task 5.4 review, Important #1). Fail loud instead of
         // reusing: the caller must close() the existing synthesizer first
         // (tts_screen.dart already does this on every model/language
-        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs).
+        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs). Both
+        // sides are normalized ([_normalizeTtsLanguage]) so this only fires
+        // for a GENUINELY different language, not e.g. null vs. 'english'
+        // or 'English' vs. 'english'.
         throw StateError(
           'Active TTS synthesizer was created for language '
-          "'${_lastActiveTtsLanguage ?? 'default'}'; call close() before "
-          "requesting '${language ?? 'default'}'.",
+          "'$_lastActiveTtsLanguage'; call close() before requesting "
+          "'${_normalizeTtsLanguage(language)}'.",
         );
       } else {
         // Same model, same language - return existing singleton
@@ -590,7 +608,7 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
       // package-built model fires this via CloseNotifier (addCloseListener).
       _initializedTtsModel = synth;
       _lastActiveTtsSpec = activeModel;
-      _lastActiveTtsLanguage = language;
+      _lastActiveTtsLanguage = _normalizeTtsLanguage(language);
       synth.addCloseListener(() {
         // Only reset if this close-listener still belongs to the current
         // singleton — a newer model may already have replaced it (the
diff --git a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
index f0677930..c431e14e 100644
--- a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
+++ b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
@@ -38,6 +38,17 @@ part '../core/model_management/utils/file_system_manager.dart';
 part '../core/model_management/utils/resume_checker.dart';
 part '../core/model_management/managers/mobile_model_manager.dart';
 
+/// Normalizes a `createTtsModel`/`getActiveTts` `language` argument for the
+/// same-model reuse guard's store/compare — defaults `null` to `'english'`
+/// (mirrors `LiteRtTtsBackend.createModel`'s `config.language ?? 'english'`)
+/// and lowercases so `null`, `'english'`, and `'English'` all compare equal
+/// (they build the SAME synthesizer either way — `Qwen3Prompt.build` already
+/// lowercases the language it's given). Without this, storing/comparing the
+/// raw argument tripped a spurious `StateError` for effectively-identical
+/// requests (e.g. `getActiveTts()` then `getActiveTts(language: 'english')`).
+String _normalizeTtsLanguage(String? language) =>
+    (language ?? 'english').toLowerCase();
+
 class FlutterGemmaMobile extends FlutterGemmaPlugin {
   Completer<InferenceModel>? _initCompleter;
   InferenceModel? _initializedModel;
@@ -59,10 +70,13 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
   SpeechSynthesizer? _initializedTtsModel;
   TtsModelSpec?
   _lastActiveTtsSpec; // Track which spec was used to create _initializedTtsModel
-  // The `language` the active singleton was built with (raw, as received —
-  // not defaulted). Reusing the singleton for a DIFFERENT language would
-  // silently emit wrong-language audio with no error (Task 5.4 review,
-  // Important #1) — see the same-model branch in createTtsModel below.
+  // The `language` the active singleton was built with, NORMALIZED
+  // ([_normalizeTtsLanguage] — defaulted + lowercased) so a same-effective-
+  // language request compared raw-to-raw (e.g. null vs. 'english', or
+  // 'English' vs. 'english') doesn't spuriously trip the guard below.
+  // Reusing the singleton for a genuinely DIFFERENT language would silently
+  // emit wrong-language audio with no error (Task 5.4 review, Important #1)
+  // — see the same-model branch in createTtsModel below.
   String? _lastActiveTtsLanguage;
 
   // Made public for example app integration
@@ -617,17 +631,20 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
         _lastActiveTtsSpec = null;
         _lastActiveTtsLanguage = null;
         await old?.close();
-      } else if (language != _lastActiveTtsLanguage) {
+      } else if (_normalizeTtsLanguage(language) != _lastActiveTtsLanguage) {
         // Same model, but a DIFFERENT language was requested — reusing the
         // singleton here would silently emit WRONG-LANGUAGE audio with no
         // error (Task 5.4 review, Important #1). Fail loud instead of
         // reusing: the caller must close() the existing synthesizer first
         // (tts_screen.dart already does this on every model/language
-        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs).
+        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs). Both
+        // sides are normalized ([_normalizeTtsLanguage]) so this only fires
+        // for a GENUINELY different language, not e.g. null vs. 'english'
+        // or 'English' vs. 'english'.
         throw StateError(
           'Active TTS synthesizer was created for language '
-          "'${_lastActiveTtsLanguage ?? 'default'}'; call close() before "
-          "requesting '${language ?? 'default'}'.",
+          "'$_lastActiveTtsLanguage'; call close() before requesting "
+          "'${_normalizeTtsLanguage(language)}'.",
         );
       } else {
         // Same model, same language - return existing singleton
@@ -683,7 +700,7 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
       // package-built model fires this via CloseNotifier (addCloseListener).
       _initializedTtsModel = synth;
       _lastActiveTtsSpec = activeModel;
-      _lastActiveTtsLanguage = language;
+      _lastActiveTtsLanguage = _normalizeTtsLanguage(language);
       synth.addCloseListener(() {
         // Only reset if this close-listener still belongs to the current
         // singleton — a newer model may already have replaced it (the
diff --git a/packages/flutter_gemma/test/core/tts_model_spec_test.dart b/packages/flutter_gemma/test/core/tts_model_spec_test.dart
index 41ca011e..d4c86c07 100644
--- a/packages/flutter_gemma/test/core/tts_model_spec_test.dart
+++ b/packages/flutter_gemma/test/core/tts_model_spec_test.dart
@@ -17,6 +17,28 @@ void main() {
     expect(m.length, 8);
   });
 
+  test('every wired TtsModelType manifest (matcha, qwen3 — those whose '
+      '.manifest does not throw) contains only plain basenames: a "/" would '
+      'make MobileModelManager._restoreActiveTtsModel derive a different '
+      'on-disk path than a fresh install did, silently breaking active-model '
+      'restore after relaunch', () {
+    for (final type in TtsModelType.values) {
+      final List<String> manifest;
+      try {
+        manifest = type.manifest;
+      } on UnimplementedError {
+        continue; // Unwired family (kokoro/supertonic) — nothing to check.
+      }
+      for (final fn in manifest) {
+        expect(
+          fn.contains('/'),
+          isFalse,
+          reason: '$type manifest entry "$fn" must be a plain basename',
+        );
+      }
+    }
+  });
+
   test('unwired families throw UnimplementedError from manifest', () {
     expect(
       () => TtsModelType.kokoro.manifest,
diff --git a/packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart b/packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart
index a97f543e..dadac1da 100644
--- a/packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart
+++ b/packages/flutter_gemma/test/mobile/tts_language_singleton_test.dart
@@ -108,7 +108,62 @@ void main() {
     expect(fakeBackend.lastConfig?.language, 'french');
     expect(fakeBackend.createModelCallCount, 2);
     expect(identical(synth2, synth1), isFalse);
+
+    // Close synth2 too — FlutterGemmaMobile's TTS singleton fields
+    // (_lastActiveTtsSpec/_lastActiveTtsLanguage/_initializedTtsModel) live
+    // on the plugin instance, not this test's fixtures, so a leftover
+    // active synthesizer here would leak into the NEXT test in this file.
+    await synth2.close();
   });
+
+  test(
+    'getActiveTts treats null, "english", and "English" as the SAME '
+    'effective language (default + case normalized before the reuse-guard '
+    'store/compare) — a genuinely different language still fails loud',
+    () async {
+      final fixtureDownload = _FixtureDownloadService(_fakeBundleBytes);
+      await ServiceRegistry.initialize(downloadService: fixtureDownload);
+      final fakeBackend = _FakeTtsBackend();
+      TtsRegistry.instance.registerAll([fakeBackend]);
+
+      await FlutterGemma.installTts()
+          .fromNetwork('https://example.com/qwen3/')
+          .ofType(TtsModelType.qwen3)
+          .install();
+
+      // No `language:` argument at all -> the backend defaults it to
+      // 'english' (LiteRtTtsBackend.createModel), and the guard normalizes
+      // the same way when storing.
+      final synth1 = await FlutterGemma.getActiveTts();
+      expect(fakeBackend.createModelCallCount, 1);
+
+      // Same effective language, explicit lowercase -> reuse, no new backend
+      // call, no StateError. Before normalization this compared `null !=
+      // 'english'` and threw spuriously.
+      final synth1Again = await FlutterGemma.getActiveTts(language: 'english');
+      expect(identical(synth1Again, synth1), isTrue);
+      expect(fakeBackend.createModelCallCount, 1);
+
+      // Same effective language, different case -> still reused. Before
+      // normalization this compared `'english' != 'English'` and threw.
+      final synth1Cased = await FlutterGemma.getActiveTts(language: 'English');
+      expect(identical(synth1Cased, synth1), isTrue);
+      expect(fakeBackend.createModelCallCount, 1);
+
+      // A GENUINELY different language must still fail loud, without closing
+      // the existing synthesizer first.
+      await expectLater(
+        FlutterGemma.getActiveTts(language: 'german'),
+        throwsA(isA<StateError>()),
+      );
+      expect(fakeBackend.createModelCallCount, 1);
+
+      // Close the still-active synthesizer so FlutterGemmaMobile's TTS
+      // singleton fields don't leak into a later test in this file (see the
+      // matching cleanup at the end of the test above).
+      await synth1.close();
+    },
+  );
 }
 
 class _FakeTtsBackend implements TtsBackendProvider {
diff --git a/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart b/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
index d3c5b796..63e9f2b4 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
@@ -148,15 +148,19 @@ List<Float32List> runLiteRtGraph(
           bindings,
           shape,
           kLiteRtElementTypeFloat32,
-          (alloc, count) =>
-              alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data),
+          (alloc, count) {
+            _checkPayloadLength(data.length, count);
+            alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data);
+          },
         ),
         I32Input(:final shape, :final data) => _createTensorBuffer(
           bindings,
           shape,
           kLiteRtElementTypeInt32,
-          (alloc, count) =>
-              alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data),
+          (alloc, count) {
+            _checkPayloadLength(data.length, count);
+            alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data);
+          },
         ),
       });
     }
@@ -249,8 +253,10 @@ TensorHandle createF32TensorBuffer(
     kLiteRtElementTypeFloat32,
     data == null
         ? null
-        : (alloc, count) =>
-              alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data),
+        : (alloc, count) {
+            _checkPayloadLength(data.length, count);
+            alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data);
+          },
   );
 }
 
@@ -271,11 +277,28 @@ TensorHandle createI32TensorBuffer(
     kLiteRtElementTypeInt32,
     data == null
         ? null
-        : (alloc, count) =>
-              alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data),
+        : (alloc, count) {
+            _checkPayloadLength(data.length, count);
+            alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data);
+          },
   );
 }
 
+/// Guards every [GraphInput]/[createF32TensorBuffer]/[createI32TensorBuffer]
+/// payload write: a `data` shorter than [count] (= product of the tensor's
+/// shape) would otherwise be silently zero-padded by `setAll` into a
+/// wrong-but-not-obviously-wrong tensor, and a longer one would throw a
+/// confusing `RangeError` from `setAll` itself instead of naming the actual
+/// mismatch. THROWS (not `assert` — asserts are stripped in release builds
+/// and this must fail loud in production too).
+void _checkPayloadLength(int dataLength, int count) {
+  if (dataLength != count) {
+    throw ArgumentError(
+      'GraphInput payload length $dataLength != product(shape) $count',
+    );
+  }
+}
+
 /// Shared allocate + (optionally) write + wrap-as-tensor-buffer sequence
 /// behind [createF32TensorBuffer]/[createI32TensorBuffer]/[runLiteRtGraph]'s
 /// per-input dispatch. [elementType] is one of `kLiteRtElementTypeFloat32`/
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index cdcc76c9..99dbeb31 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -138,6 +138,14 @@ const int _mtpResidualGroups = 15;
 /// `_codecPad`/`_codecBos`/etc.
 const int _codecEos = 2150;
 
+/// Left-context frame count [Qwen3TtsCore.decodeCodes]'s sliding window
+/// re-feeds from the previous window on every step but one (`ctx`/`c` in
+/// `qwen3_tts_pipeline.py:384-392` — see this file's header). [codecChunk]
+/// must exceed this or [Qwen3TtsCore.decodeCodes]'s window advance
+/// (`codecChunk - c`) never makes progress — checked at [Qwen3TtsCore.load]
+/// time, see the guard there.
+const int _codecLeftContext = 25;
+
 int _acceleratorFor(PreferredBackend? backend) {
   switch (backend) {
     case PreferredBackend.gpu:
@@ -515,6 +523,17 @@ class Qwen3TtsCore {
         'codec.args_0',
       );
       final codecChunk = codecInShape.last;
+      // [decodeCodes]'s sliding window advances by `codecChunk -
+      // min(_codecLeftContext, i)` rows per step (this file's header); if a
+      // drifted model shipped a codecChunk at or below the left-context
+      // width, that advance is <= 0 and the decode loop never makes
+      // progress (hangs) instead of failing loud here.
+      if (codecChunk <= _codecLeftContext) {
+        throw StateError(
+          'Qwen3TtsCore.load: codecChunk ($codecChunk) must exceed the '
+          'codec left-context ($_codecLeftContext); model layout drift.',
+        );
+      }
 
       tables = await Qwen3Tables.load(
         codecEmbPath: _artifactPath(artifactPaths, 'codec_embedding_fp32.npy'),
@@ -941,7 +960,7 @@ class Qwen3TtsCore {
     }
 
     // chunk, ctx = self._codec_chunk, 25 (qwen3_tts_pipeline.py:384).
-    const ctx = 25;
+    const ctx = _codecLeftContext;
     final chunk = codecChunk;
     final pieces = <Float32List>[];
     var i = 0;
@@ -1137,6 +1156,7 @@ class Qwen3TtsCore {
     final suppress = buildSuppress();
     final frames = <List<int>>[];
     final history = <int>{};
+    var hitEos = false;
 
     // while len(frames) < max_frames: ... (qwen3_tts_pipeline.py:230-256).
     while (frames.length < maxFrames) {
@@ -1164,7 +1184,10 @@ class Qwen3TtsCore {
           : pickGreedy(scores);
       history.add(cb0);
       // if cb0 == _CODEC_EOS: break (qwen3_tts_pipeline.py:240-241).
-      if (cb0 == _codecEos) break;
+      if (cb0 == _codecEos) {
+        hitEos = true;
+        break;
+      }
 
       // residual = _run_mtp(hidden, cb0, do_sample, top_k, temperature,
       // rng) (qwen3_tts_pipeline.py:244-245).
@@ -1211,6 +1234,14 @@ class Qwen3TtsCore {
       (cb0Logits, hidden, kv) = runDecode(kv, embed, pos);
     }
 
+    if (!hitEos) {
+      gemmaLog(
+        '⚠️ Qwen3 TTS reached maxFrames=$maxFrames '
+        '(~${(maxFrames / 12.5).round()}s) before EOS — output is '
+        'truncated; text may be too long for a single AR pass.',
+      );
+    }
+
     return frames;
   }
 
diff --git a/packages/flutter_gemma_speech/pubspec.yaml b/packages/flutter_gemma_speech/pubspec.yaml
index aaa82c52..02489a7a 100644
--- a/packages/flutter_gemma_speech/pubspec.yaml
+++ b/packages/flutter_gemma_speech/pubspec.yaml
@@ -25,7 +25,7 @@ environment:
 dependencies:
   flutter:
     sdk: flutter
-  flutter_gemma: ^1.5.1
+  flutter_gemma: ^1.5.2
   flutter_gemma_litertlm: ^1.3.0
   ffi: ^2.1.0
   meta: ^1.9.0

From c9c32541010b00bc2b91390a1632ac274eb5b9f3 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 13:23:32 +0500
Subject: [PATCH 26/30] test(qwen3): close codec multi-window coverage gap
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Add a T=135 fp32 golden (frames_long.json/waveform_long_f32.bin) and a
codec test gate on it — the existing T=26 golden is under codecChunk
(64), so decodeCodes's sliding-window + left-context-carry path was
never exercised by any test.
---
 .../test/golden/qwen3/frames_long.json        |   1 +
 .../test/golden/qwen3/meta_long.json          |   1 +
 .../test/golden/qwen3/waveform_long_f32.bin   | Bin 0 -> 1036800 bytes
 .../test/qwen3/qwen3_codec_test.dart          |  83 +++++++++++++++++-
 .../tool/qwen3/gen_qwen3_goldens.py           |  40 +++++++--
 5 files changed, 116 insertions(+), 9 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/frames_long.json
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/meta_long.json
 create mode 100644 packages/flutter_gemma_speech/test/golden/qwen3/waveform_long_f32.bin

diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/frames_long.json b/packages/flutter_gemma_speech/test/golden/qwen3/frames_long.json
new file mode 100644
index 00000000..0c58f436
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/golden/qwen3/frames_long.json
@@ -0,0 +1 @@
+{"frames": [[1995, 1159, 355, 22, 1174, 1093, 625, 1814, 1058, 905, 1846, 248, 1677, 889, 812, 901], [215, 1722, 355, 310, 1174, 1093, 625, 1814, 930, 1144, 679, 1247, 896, 889, 812, 803], [212, 1722, 355, 310, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 896, 889, 1008, 803], [1181, 1722, 355, 310, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 1110, 889, 1008, 803], [462, 1722, 355, 310, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 1110, 889, 1008, 803], [462, 1722, 355, 310, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 1110, 889, 812, 803], [462, 1722, 355, 310, 1174, 1093, 1960, 1814, 930, 1144, 1846, 1247, 896, 889, 812, 803], [619, 1722, 355, 310, 1174, 1093, 1960, 1814, 930, 1144, 1846, 1247, 896, 889, 812, 803], [619, 1722, 355, 310, 1174, 1093, 1960, 1814, 930, 1144, 1846, 1247, 896, 889, 586, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 1213, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 896, 889, 586, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 896, 889, 586, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 896, 889, 586, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 1814, 930, 1144, 1846, 1247, 896, 889, 586, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 1213, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 1213, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 1213, 803], [1657, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 1213, 803], [706, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 896, 889, 1213, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1174, 1093, 625, 278, 930, 1144, 1846, 1247, 896, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 896, 889, 1213, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 896, 889, 812, 803], [706, 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[706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 1511, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 930, 1144, 1846, 1247, 1110, 889, 812, 803], [706, 1722, 355, 1596, 1296, 1093, 625, 1814, 930, 1144, 1846, 1247, 1110, 889, 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\ No newline at end of file
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/meta_long.json b/packages/flutter_gemma_speech/test/golden/qwen3/meta_long.json
new file mode 100644
index 00000000..22111dcc
--- /dev/null
+++ b/packages/flutter_gemma_speech/test/golden/qwen3/meta_long.json
@@ -0,0 +1 @@
+{"text": "On-device text to speech lets an application turn written words into natural sounding audio.", "language": "english", "talker": "fp32", "greedy": true, "speaker": "demo_speaker", "num_frames": 135, "sample_rate": 24000}
\ No newline at end of file
diff --git a/packages/flutter_gemma_speech/test/golden/qwen3/waveform_long_f32.bin b/packages/flutter_gemma_speech/test/golden/qwen3/waveform_long_f32.bin
new file mode 100644
index 0000000000000000000000000000000000000000..1799609675be2a900410e1e3ad22bc8e4e378419
GIT binary patch
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diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart
index a300d16a..0c7dccad 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_codec_test.dart
@@ -15,10 +15,15 @@
 // T=26 is well under the codec's fixed chunk width (64, per
 // `qwen3_tts_core.dart`'s `Qwen3TtsCore.load` introspection of
 // `codec_decoder_fp32.tflite`'s `args_0` input), so this golden exercises
-// exactly ONE codec call with no left context (`i=0` -> `c=min(25,0)=0`) —
-// `decodeCodes`'s sliding-window loop itself (needed for `T > 64`) is
-// exercised by construction, not by this fixture's `T`, but not stressed by
-// it either.
+// exactly ONE codec call with no left context (`i=0` -> `c=min(25,0)=0`).
+//
+// The second test below (`frames_long.json`/`waveform_long_f32.bin`, T=135
+// > 2 * codecChunk) closes that gap: it drives `decodeCodes`'s
+// sliding-window loop through 3 windows with the 25-frame left-context
+// carry between them (including a final partial window), so the `i - c`
+// window origin, the `wav.sublist(c * 1920, ...)` left-context-drop offset,
+// and the multi-piece concat are all provably exercised, not just reachable
+// by construction.
 //
 // The model bundle is NOT committed to the repo — see
 // `qwen3_prefill_test.dart`'s file header for the same skip-when-absent
@@ -165,4 +170,74 @@ void main() {
       core.dispose();
     }
   }, timeout: const Timeout(Duration(minutes: 5)));
+
+  test('Qwen3TtsCore.decodeCodes: multi-window PCM matches the PyTorch golden '
+      '(waveform_long_f32.bin, T=135 > codecChunk=64 -> exercises the '
+      'sliding-window + 25-frame left-context-carry path)', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final artifactPaths = _scanArtifactPaths(modelDir);
+
+    // Golden fixtures — committed, always present (no skip-guard needed).
+    final framesGolden =
+        jsonDecode(
+              File('test/golden/qwen3/frames_long.json').readAsStringSync(),
+            )['frames']
+            as List;
+    final frames = framesGolden
+        .map((row) => (row as List).cast<int>())
+        .toList(growable: false);
+
+    // T=135 > 2 * codecChunk (64) — this is THE assertion that proves the
+    // sliding-window loop actually runs multiple windows (not just one,
+    // like the T=26 golden above): the loop's window advance is
+    // `codecChunk - c`, so T > 64 forces at least one extra window with a
+    // 25-frame left-context carry, and T > 128 forces a third (partial)
+    // window too.
+    expect(frames.length, greaterThan(128));
+    expect(frames.length, greaterThan(64));
+    expect(frames[0].length, 16);
+
+    final expectedWav = _readRawF32('test/golden/qwen3/waveform_long_f32.bin');
+    // T frames * 1920 upsample (Qwen3TtsCore._upsampleFactor).
+    expect(expectedWav.length, frames.length * 1920);
+
+    // Default `talkerFileName` (int4) — this test never touches the
+    // talker or MTP graphs, only `decodeCodes` (the codec graph, already
+    // fp32).
+    final core = await Qwen3TtsCore.load(
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+    );
+    try {
+      final wav = core.decodeCodes(frames);
+
+      final corr = _pearsonCorr(wav, expectedWav);
+      final maxAbsDiff = _maxAbsDiff(wav, expectedWav);
+
+      // ignore: avoid_print
+      print(
+        'QWEN3-CODEC-LONG-TEST<<<len=${wav.length} '
+        'expectedLen=${expectedWav.length} frames=${frames.length} '
+        'corr=$corr maxAbsDiff=$maxAbsDiff>>>',
+      );
+
+      // Same gate as the T=26 test above, on a fixture that forces the
+      // multi-window path: a wrong `i - c` window origin, a wrong
+      // `wav.sublist(c * 1920, ...)` context-drop offset, or a broken
+      // multi-piece concat would all show up here as a correlation/seam
+      // mismatch that the single-window T=26 golden cannot catch.
+      expect(wav.length, expectedWav.length);
+      expect(corr, greaterThan(0.9999));
+      expect(maxAbsDiff, lessThan(1e-4));
+    } finally {
+      core.dispose();
+    }
+  }, timeout: const Timeout(Duration(minutes: 5)));
 }
diff --git a/packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py b/packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py
index 02d154a3..fea2b8cf 100644
--- a/packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py
+++ b/packages/flutter_gemma_speech/tool/qwen3/gen_qwen3_goldens.py
@@ -3,9 +3,14 @@
 #   python gen_qwen3_goldens.py --recipe .../text_to_speech_lm/python --model_dir <snap> --out ../../test/golden/qwen3
 import argparse, json, sys, time, numpy as np
 
-def synthesize_logging(pipe, q, text, speaker, language, out):
+def synthesize_logging(pipe, q, text, speaker, language, out, suffix='', write_frame0=True):
     """Verbatim copy of Qwen3TtsPipeline.synthesize (greedy) that also logs
-    every frame and the frame-0 (hidden, cb0, residual)."""
+    every frame and the frame-0 (hidden, cb0, residual).
+
+    `suffix` picks the output basenames (`''` -> frames.json/waveform_f32.bin,
+    the default 26-frame goldens; `'_long'` -> frames_long.json/
+    waveform_long_f32.bin, the >128-frame multi-window codec golden) so both
+    can be dumped from the same run without clobbering each other."""
     prefill, trailing, tts_pad = pipe._build_prompt(text, speaker, language)
     kv = {n: np.zeros(pipe._decode.get_input_details()[n]['shape'], np.float32) for n in pipe._kv_names}
     kv = pipe._run_prefill(kv, prefill)
@@ -30,15 +35,30 @@ def synthesize_logging(pipe, q, text, speaker, language, out):
         pos += 1
         logits, hidden, kv = pipe._run_decode(kv, embed, pos)
     wav = pipe._decode_codes(np.array(frames, np.int32))
-    json.dump({'frames': frames}, open(f'{out}/frames.json','w'))
-    json.dump(frame0, open(f'{out}/frame0.json','w'))
-    wav.astype(np.float32).tofile(f'{out}/waveform_f32.bin')
+    json.dump({'frames': frames}, open(f'{out}/frames{suffix}.json','w'))
+    if write_frame0:
+        json.dump(frame0, open(f'{out}/frame0.json','w'))
+    wav.astype(np.float32).tofile(f'{out}/waveform{suffix}_f32.bin')
     return wav, len(frames)
 
 def main():
     ap = argparse.ArgumentParser()
     ap.add_argument('--recipe', required=True); ap.add_argument('--model_dir', required=True)
     ap.add_argument('--out', required=True); ap.add_argument('--text', default='Hello from on device text to speech.')
+    # Longer paragraph for the codec multi-window golden (frames_long.json /
+    # waveform_long_f32.bin / meta_long.json): greedy fp32 synthesis of this
+    # text yields 135 frames (>128, so >64 = codecChunk, so `decodeCodes`'s
+    # sliding-window loop runs 3 windows with a 25-frame left-context carry
+    # between them, and the trailing window is a partial (< codecChunk)
+    # window too) -- exercises the multi-window path the 26-frame golden
+    # (well under codecChunk=64) never reaches.
+    ap.add_argument(
+        '--text_long',
+        default=(
+            'On-device text to speech lets an application turn written '
+            'words into natural sounding audio.'
+        ),
+    )
     a = ap.parse_args(); sys.path.insert(0, a.recipe)
     import qwen3_tts_pipeline as q
     pipe = q.Qwen3TtsPipeline(a.model_dir, talker_file='talker_fp32.tflite', num_threads=8)
@@ -64,4 +84,14 @@ def main():
                'speaker':'demo_speaker', 'num_frames': int(nframes), 'sample_rate': 24000},
               open(f'{a.out}/meta.json','w'))
 
+    # Second, longer dump -- the >128-frame codec multi-window golden (see
+    # the --text_long default's comment). Same fp32 talker, same greedy
+    # decoding, same pipeline instance; only the output basenames differ.
+    wav_long, nframes_long = synthesize_logging(
+        pipe, q, a.text_long, speaker, 'english', a.out,
+        suffix='_long', write_frame0=False)
+    json.dump({'text': a.text_long, 'language':'english', 'talker':'fp32', 'greedy':True,
+               'speaker':'demo_speaker', 'num_frames': int(nframes_long), 'sample_rate': 24000},
+              open(f'{a.out}/meta_long.json','w'))
+
 if __name__ == '__main__': main()

From c4a2e19b0f6a0179c16c8eae3351d9c867d6fa68 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 14:02:33 +0500
Subject: [PATCH 27/30] docs(qwen3): dartdoc publish-hygiene sweep + vendor
 reference recipe

Strip SDD/process scaffolding (Task/Phase refs, docs/superpowers path) from
shipped dartdoc across the qwen3 TTS port and touched TTS files, fix two
dangling doc-links and an overstated install-note. Vendor the litert-samples
Qwen3-TTS recipe (Apache-2.0) under tool/qwen3/ so the ~78 recipe citations
resolve; soften them to function-name references since the vendored copy's
added provenance line shifts its raw line numbers vs. upstream.
---
 .../core/api/tts_installation_builder.dart    |   7 +-
 .../lib/desktop/flutter_gemma_desktop.dart    |  12 +-
 .../lib/mobile/flutter_gemma_mobile.dart      |  12 +-
 .../lib/flutter_gemma_speech.dart             |   4 +-
 .../src/litert/litert_speech_synthesizer.dart |  20 +-
 .../lib/src/litert/tts_core.dart              |  15 +-
 .../lib/src/litert/tts_worker.dart            |  69 +--
 .../lib/src/litert_tts_backend.dart           |   2 +-
 .../lib/src/model/tts_model_profile.dart      |   8 +-
 .../lib/src/qwen3/qwen3_languages.dart        |  16 +-
 .../lib/src/qwen3/qwen3_prompt.dart           |  51 +-
 .../lib/src/qwen3/qwen3_sampler.dart          |  26 +-
 .../lib/src/qwen3/qwen3_tables.dart           |   2 +-
 .../lib/src/qwen3/qwen3_talker_layout.dart    |  25 +-
 .../lib/src/qwen3/qwen3_tts_core.dart         | 264 +++++-----
 .../lib/src/tts/tts_text_frontend.dart        |  12 +-
 .../test/qwen3/qwen3_prefill_test.dart        |   2 +-
 .../test/qwen3/qwen3_sampler_test.dart        |   6 +-
 .../test/qwen3/qwen3_synthesize_test.dart     |   2 +-
 .../test/qwen3/qwen3_talker_decode_test.dart  |   4 +-
 .../tool/qwen3/qwen3_tts_pipeline.py          | 491 ++++++++++++++++++
 .../tool/qwen3/synthesize.py                  | 118 +++++
 22 files changed, 897 insertions(+), 271 deletions(-)
 create mode 100644 packages/flutter_gemma_speech/tool/qwen3/qwen3_tts_pipeline.py
 create mode 100644 packages/flutter_gemma_speech/tool/qwen3/synthesize.py

diff --git a/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart b/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
index 5db95749..75e1dfc0 100644
--- a/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
+++ b/packages/flutter_gemma/lib/core/api/tts_installation_builder.dart
@@ -113,9 +113,10 @@ class TtsInstallationBuilder {
     // yet still collide with a plain file left behind by an STT/embedding
     // install (e.g. Qwen3's `tokenizer.json`), and adoption has no way to
     // verify the on-disk file actually belongs to this model (no size/hash
-    // check available). Every not-yet-installed manifest file is always
-    // (re-)downloaded fresh. The safe migration path for genuinely-legacy TTS
-    // installs is restore-time, in
+    // check available). A manifest file that is not already installed is
+    // downloaded fresh (never adopted from a legacy plain file);
+    // already-installed files are still skipped by the loop below. The safe
+    // migration path for genuinely-legacy TTS installs is restore-time, in
     // MobileModelManager._migrateLegacyCompanionForRestore.
     final files = spec.files;
     var done = 0;
diff --git a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
index 648f42ef..3151bb8b 100644
--- a/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
+++ b/packages/flutter_gemma/lib/desktop/flutter_gemma_desktop.dart
@@ -98,8 +98,8 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
   // language request compared raw-to-raw (e.g. null vs. 'english', or
   // 'English' vs. 'english') doesn't spuriously trip the guard below.
   // Reusing the singleton for a genuinely DIFFERENT language would silently
-  // emit wrong-language audio with no error (Task 5.4 review, Important #1)
-  // — see the same-model branch in createTtsModel below.
+  // emit wrong-language audio with no error — see the same-model branch in
+  // createTtsModel below.
   String? _lastActiveTtsLanguage;
 
   @override
@@ -548,10 +548,10 @@ class FlutterGemmaDesktop extends FlutterGemmaPlugin {
       } else if (_normalizeTtsLanguage(language) != _lastActiveTtsLanguage) {
         // Same model, but a DIFFERENT language was requested — reusing the
         // singleton here would silently emit WRONG-LANGUAGE audio with no
-        // error (Task 5.4 review, Important #1). Fail loud instead of
-        // reusing: the caller must close() the existing synthesizer first
-        // (tts_screen.dart already does this on every model/language
-        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs). Both
+        // error. Fail loud instead of reusing: the caller must close() the
+        // existing synthesizer first (tts_screen.dart already does this on
+        // every model/language switch — see LiteRtSpeechSynthesizer/
+        // getActiveTts's docs). Both
         // sides are normalized ([_normalizeTtsLanguage]) so this only fires
         // for a GENUINELY different language, not e.g. null vs. 'english'
         // or 'English' vs. 'english'.
diff --git a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
index c431e14e..dae45735 100644
--- a/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
+++ b/packages/flutter_gemma/lib/mobile/flutter_gemma_mobile.dart
@@ -75,8 +75,8 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
   // language request compared raw-to-raw (e.g. null vs. 'english', or
   // 'English' vs. 'english') doesn't spuriously trip the guard below.
   // Reusing the singleton for a genuinely DIFFERENT language would silently
-  // emit wrong-language audio with no error (Task 5.4 review, Important #1)
-  // — see the same-model branch in createTtsModel below.
+  // emit wrong-language audio with no error — see the same-model branch in
+  // createTtsModel below.
   String? _lastActiveTtsLanguage;
 
   // Made public for example app integration
@@ -634,10 +634,10 @@ class FlutterGemmaMobile extends FlutterGemmaPlugin {
       } else if (_normalizeTtsLanguage(language) != _lastActiveTtsLanguage) {
         // Same model, but a DIFFERENT language was requested — reusing the
         // singleton here would silently emit WRONG-LANGUAGE audio with no
-        // error (Task 5.4 review, Important #1). Fail loud instead of
-        // reusing: the caller must close() the existing synthesizer first
-        // (tts_screen.dart already does this on every model/language
-        // switch — see LiteRtSpeechSynthesizer/getActiveTts's docs). Both
+        // error. Fail loud instead of reusing: the caller must close() the
+        // existing synthesizer first (tts_screen.dart already does this on
+        // every model/language switch — see LiteRtSpeechSynthesizer/
+        // getActiveTts's docs). Both
         // sides are normalized ([_normalizeTtsLanguage]) so this only fires
         // for a GENUINELY different language, not e.g. null vs. 'english'
         // or 'English' vs. 'english'.
diff --git a/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart b/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart
index c4b2682f..79985ded 100644
--- a/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart
+++ b/packages/flutter_gemma_speech/lib/flutter_gemma_speech.dart
@@ -26,8 +26,8 @@ export 'src/voice/voice_event.dart';
 export 'src/voice/voice_responder.dart';
 export 'src/voice/voice_session.dart';
 
-// Qwen3-TTS supported-language list (Task 5.4) — dependency-free, safe on
-// every platform. The single source of truth for both the create-time
+// Qwen3-TTS supported-language list — dependency-free, safe on every
+// platform. The single source of truth for both the create-time
 // language validator (`LiteRtSpeechSynthesizer.create`) and a UI language
 // picker; see `qwen3_languages.dart`'s header for why it's a separate file
 // from `qwen3_prompt.dart` (which is native-only, via `dart:io`).
diff --git a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
index d7a12c64..673c3899 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/litert_speech_synthesizer.dart
@@ -1,13 +1,13 @@
 // `SpeechSynthesizer` facade over a background isolate, mirroring
-// `litert_speech_recognizer.dart` (Task 2.5 direct STT→TTS mirror). The
-// blocking LiteRT text-frontend + CFM/vocoder forward passes run on a
-// dedicated [TtsWorker] isolate — spawned once, reused for every call — so
-// the UI isolate stays free.
+// `litert_speech_recognizer.dart` (a direct STT→TTS mirror). The blocking
+// LiteRT text-frontend + CFM/vocoder forward passes run on a dedicated
+// [TtsWorker] isolate — spawned once, reused for every call — so the UI
+// isolate stays free.
 //
 // The native code lives in `tts_core.dart` (driven inside the worker
-// isolate, Task 2.3) plus `tts_text_frontend.dart` (Task 2.2); this file is
-// the public, async, main-isolate API generic over [TtsModelProfile] —
-// matcha/kokoro/supertonic select a profile, not a synthesizer subclass.
+// isolate) plus `tts_text_frontend.dart`; this file is the public, async,
+// main-isolate API generic over [TtsModelProfile] — matcha/kokoro/supertonic
+// select a profile, not a synthesizer subclass.
 
 import 'dart:typed_data';
 
@@ -50,7 +50,7 @@ class LiteRtSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
   /// [TtsPipelineKind.qwen3ArCodec], [language] is validated against
   /// `qwen3SupportedLanguages` (`qwen3_languages.dart`) and this throws
   /// [ArgumentError] for an unknown value BEFORE spawning the worker —
-  /// fail-fast, ahead of the ~1.9 GB model load (Task 5.4). Once validated,
+  /// fail-fast, ahead of the ~1.9 GB model load. Once validated,
   /// [language] is normalized to lowercase (`normalizeQwen3Language`) so the
   /// whole downstream pipeline (the worker, `Qwen3TtsCore.synthesizePcm16`,
   /// `Qwen3Prompt.build`'s case-SENSITIVE `'auto'` comparison) sees one
@@ -61,8 +61,8 @@ class LiteRtSpeechSynthesizer extends SpeechSynthesizer with CloseNotifier {
   /// Qwen3-only): when non-null it replaces the bundle's single demo voice
   /// (`voices/demo_speaker.npy`) for every `synthesize` call on the returned
   /// instance. v1 ships exactly one voice and does not surface a voice
-  /// picker anywhere (see Task 5.4's brief) — this param exists purely so a
-  /// future multi-voice release doesn't need a breaking signature change.
+  /// picker anywhere — this param exists purely so a future multi-voice
+  /// release doesn't need a breaking signature change.
   ///
   /// Caller owns the returned instance and must call [close] when done.
   static Future<LiteRtSpeechSynthesizer> create({
diff --git a/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart b/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
index d91bff6e..3d8f4c16 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/tts_core.dart
@@ -36,12 +36,13 @@
 // graph) and exposed via
 // `TtsCore.neuralG2p` — it's the neural OOV fallback used when a word is
 // missing from the dictionary; the dictionary-only path stays the golden
-// path via `TtsTextFrontend` (Task 2.2).
+// path via `TtsTextFrontend`.
 //
 // Determinism: the Euler CFM decoder's initial noise is drawn from a FIXED
 // seed ([ttsCfmSeed]) via Box-Muller ([nextGaussian]), so [TtsCore.synthesize]
-// is byte-reproducible run-to-run — the Phase-3 golden depends on this. Do
-// NOT change the seed or the Box-Muller formula without regenerating it.
+// is byte-reproducible run-to-run — the golden in `tts_core_test.dart`
+// depends on this. Do NOT change the seed or the Box-Muller formula
+// without regenerating it.
 //
 // Leak-safety: buffer create/lock/read/unlock/destroy mirrors
 // `litert_embedding_core.dart`'s forward-pass pattern; `load`'s partial-
@@ -73,7 +74,7 @@ import 'litert_graph.dart';
 
 /// The Euler CFM decoder's fixed Gaussian-noise seed. Fixed (not
 /// time-derived) so [TtsCore.synthesize] is byte-reproducible run-to-run —
-/// the Phase-3 golden depends on this. Verified value from
+/// the golden in `tts_core_test.dart` depends on this. Verified value from
 /// `matcha_synth.dart:565`.
 const int ttsCfmSeed = 1234;
 
@@ -345,8 +346,8 @@ class TtsCore {
   /// phoneme string. Synchronous (no file I/O; `g2p_meta.json` was already
   /// parsed in [load]), so it's safe to call per-word from the frontend (the
   /// `NeuralG2pResolver` adapter is `core.neuralG2p`). Framing/decoding is
-  /// [encodeG2pInput]/[decodeG2pOutput] (Task 6) — this method only runs the
-  /// native forward pass and picks the per-position argmax over the
+  /// [encodeG2pInput]/[decodeG2pOutput] — this method only runs the native
+  /// forward pass and picks the per-position argmax over the
   /// `n_phonemes`-wide logits.
   String neuralG2p(String word) {
     if (_disposed) {
@@ -394,7 +395,7 @@ class TtsCore {
   /// single-window case; every graph run goes through [runLiteRtGraph]
   /// instead of that script's raw-`dlopen` `runGraph`. Returns 16-bit
   /// little-endian mono PCM with NO WAV header — the example's `pcmToWav`
-  /// adds a header in Phase 3.
+  /// adds a header.
   ///
   /// When the predicted duration fits one window (`rawYlen <= _maxMel`, the
   /// common case), this is byte-identical to the pre-chunking implementation
diff --git a/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart b/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
index 0976cd8d..73d6c04d 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/tts_worker.dart
@@ -1,12 +1,13 @@
 // Long-lived background isolate that owns the entire Matcha-TTS pipeline:
-// both the text frontend (dictionary G2P + host embedding gather, Task 2.2)
-// and the native LiteRT core (4 compiled graphs + the CFM/vocoder forward
-// passes, Task 2.3). The forward passes are blocking synchronous FFI calls;
-// running them (and the frontend's dictionary lookups + 275k-entry load)
-// here keeps the UI isolate's event loop free. Direct analog of
-// `stt_worker.dart` — see that file's header for the "why a long-lived
-// worker and not `Isolate.run`" rationale (FFI handles can't cross isolate
-// boundaries; the compiled models are expensive to build but cheap to run).
+// both the text frontend (`TtsTextFrontend`: dictionary G2P + host embedding
+// gather) and the native LiteRT core (`TtsCore`: 4 compiled graphs + the
+// CFM/vocoder forward passes). The forward passes are blocking synchronous
+// FFI calls; running them (and the frontend's dictionary lookups +
+// 275k-entry load) here keeps the UI isolate's event loop free. Direct
+// analog of `stt_worker.dart` — see that file's header for the "why a
+// long-lived worker and not `Isolate.run`" rationale (FFI handles can't
+// cross isolate boundaries; the compiled models are expensive to build but
+// cheap to run).
 //
 // Unlike `SttWorker` (which owns only `SttCore`, tokenizer included inside
 // the core), this worker owns TWO objects: `TtsTextFrontend` and `TtsCore`.
@@ -31,10 +32,10 @@
 // (setup), a `String` (request), and a `Uint8List` of 16-bit PCM samples
 // (reply).
 //
-// `_workerEntry` branches on `init.profile.pipeline` (Task 5.3) into
-// `_runMatchaWorker` (the above, unchanged) or `_runQwen3Worker`: Qwen3-TTS
-// is a from-scratch autoregressive codec-token LM (`Qwen3TtsCore`, Phase
-// 2-4) with its own KV cache and no CFM step, so it needs neither
+// `_workerEntry` branches on `init.profile.pipeline` into `_runMatchaWorker`
+// (the above, unchanged) or `_runQwen3Worker`: Qwen3-TTS is a from-scratch
+// autoregressive codec-token LM (`Qwen3TtsCore`) with its own KV cache and
+// no CFM step, so it needs neither
 // `TtsTextFrontend`/`TtsTextNormalizer` (Matcha's dictionary G2P + host
 // embedding gather + clause splitter) nor `TtsCore` (Matcha's native
 // core) — it does its own byte-level BPE tokenization
@@ -61,7 +62,8 @@ import 'tts_core.dart';
 
 /// Handshake payload the worker sends back once the frontend + native model
 /// are loaded. Carries [sampleRate] (read from `TtsCore` after load) so the
-/// facade (Task 2.5) can expose it synchronously without a round-trip.
+/// `LiteRtSpeechSynthesizer` facade can expose it synchronously without a
+/// round-trip.
 class _Ready {
   _Ready(this.commandPort, this.sampleRate);
   final SendPort commandPort;
@@ -119,8 +121,8 @@ class _WorkerInit {
   /// `'auto'`, forwarded verbatim to every `Qwen3TtsCore.synthesizePcm16`
   /// call. Ignored by [_runMatchaWorker] (Matcha has no language parameter —
   /// its locale comes from [TtsModelProfile.locale] instead). Validated by
-  /// `LiteRtSpeechSynthesizer.create` (Task 5.4) before the worker is even
-  /// spawned, so by the time it reaches here it is always a supported value.
+  /// `LiteRtSpeechSynthesizer.create` before the worker is even spawned, so
+  /// by the time it reaches here it is always a supported value.
   final String language;
 
   /// Qwen3-only: forward-compat speaker x-vector override (`[1024]`); null
@@ -313,8 +315,8 @@ Future<void> _workerEntry(_WorkerInit init) async {
 
 /// Matcha-CFM arm of [_workerEntry] — loads `TtsTextFrontend` + `TtsCore`
 /// and serves requests via the clause-split / per-clause-CFM-seed /
-/// inter-clause-silence loop described in this file's header. Unchanged by
-/// Task 5.3 (Qwen3 dispatches to [_runQwen3Worker] instead).
+/// inter-clause-silence loop described in this file's header. Qwen3-TTS
+/// dispatches to [_runQwen3Worker] instead.
 Future<void> _runMatchaWorker(_WorkerInit init) async {
   final TtsCore core;
   final TtsTextFrontend frontend;
@@ -395,9 +397,9 @@ Future<void> _runMatchaWorker(_WorkerInit init) async {
   }
 }
 
-/// Qwen3-TTS arm of [_workerEntry] (Task 5.3). Loads `Qwen3TtsCore` (the
-/// talker/MTP/codec graphs + host tables + BPE encoder, Phase 2-4) and the
-/// bundle's one demo-voice x-vector, then serves requests with exactly ONE
+/// Qwen3-TTS arm of [_workerEntry]. Loads `Qwen3TtsCore` (the talker/MTP/
+/// codec graphs + host tables + BPE encoder) and the bundle's one
+/// demo-voice x-vector, then serves requests with exactly ONE
 /// `core.synthesizePcm16` call per request.
 ///
 /// Deliberately does NOT reuse [_runMatchaWorker]'s clause-split / CFM-seed
@@ -408,9 +410,10 @@ Future<void> _runMatchaWorker(_WorkerInit init) async {
 ///   ceiling — it consumes a request's full text in one AR pass
 ///   (`Qwen3TtsCore.synthesize`'s `maxFrames`, not a text-length limit).
 /// - No CFM seed (`ttsCfmSeed + clauseIndex`): Qwen3 has no CFM step; its
-///   only randomness is [_pickSampled]'s token sampling, seeded once per
-///   call via `Qwen3TtsCore.synthesizePcm16`'s own `seed` param (left
-///   unset here — see [doSample]'s doc below).
+///   only randomness is `pickSampled`'s token sampling (see
+///   [Qwen3TtsCore.synthesizePcm16]'s sampling path), seeded once per call
+///   via `Qwen3TtsCore.synthesizePcm16`'s own `seed` param (left unset
+///   here — see `doSample`'s doc below).
 /// - No `concatPcmWithSilence`: there is only ever one segment per request
 ///   (no per-clause splitting to splice back together).
 ///
@@ -419,20 +422,22 @@ Future<void> _runMatchaWorker(_WorkerInit init) async {
 /// artifact the golden-gate tests load) — this is the runtime path real
 /// users hit, not a correctness gate.
 ///
-/// `doSample: true` on every call (per Task 5.3's brief: the runtime
-/// default is varied, natural prosody; a fixed `seed` would make every
-/// synthesis of the same text sound identical). The fp32-greedy
+/// `doSample: true` on every call (the runtime default is varied, natural
+/// prosody; a fixed `seed` would make every synthesis of the same text
+/// sound identical). The fp32-greedy
 /// byte-for-byte golden gate lives in `qwen3_synthesize_test.dart`
 /// (`Qwen3TtsCore.synthesize` driven directly with `doSample: false`), not
 /// here — this worker never runs greedy.
 ///
 /// v1 ships exactly one voice: the bundle's `demo_speaker.npy` x-vector
-/// (Task 5.2's manifest), read once at load time via [readNpyF32] unless
-/// [_WorkerInit.voice] overrides it — no voice PICKER yet (`init.voice` is
-/// forward-compat-only; the UI never sets it, see [_WorkerInit.voice]'s
-/// doc). `init.language` is the per-call knob Task 5.3 threads through and
-/// Task 5.4 validates + surfaces a real picker for; see
-/// [_WorkerInit.language]'s doc.
+/// (the model bundle's asset manifest), read once at load time via
+/// [readNpyF32] unless [_WorkerInit.voice] overrides it — no voice PICKER
+/// yet (`init.voice` is forward-compat-only; the UI never sets it, see
+/// [_WorkerInit.voice]'s doc). `init.language` is the per-call knob this
+/// worker threads through to `Qwen3TtsCore.synthesizePcm16`, validated up
+/// front by `LiteRtSpeechSynthesizer.create` (`assertQwen3LanguageSupported`),
+/// which is also what surfaces a real language picker (via
+/// `qwen3SupportedLanguages`); see [_WorkerInit.language]'s doc.
 ///
 /// Fail-loud (per Global Constraints / the project's no-masking-fallback
 /// rule): if [Qwen3TtsCore.load] or the demo-voice read throws, this sends
diff --git a/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart b/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart
index 37167954..0df0d591 100644
--- a/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert_tts_backend.dart
@@ -37,7 +37,7 @@ class LiteRtTtsBackend implements TtsBackendProvider {
     // spec.ttsModelType (e.g. TtsModelType.matcha) selects the runtime
     // profile — this backend never hardcodes a model.
     //
-    // config.language is Qwen3-only (Task 5.4) — threaded from
+    // config.language is Qwen3-only — threaded from
     // `FlutterGemma.getActiveTts(language: ...)` through `RuntimeConfig`;
     // null falls back to `LiteRtSpeechSynthesizer.create`'s own `'english'`
     // default. Matcha ignores it (no language parameter). No `voice` here:
diff --git a/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart b/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart
index 0f36e2ba..91a77ebc 100644
--- a/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart
+++ b/packages/flutter_gemma_speech/lib/src/model/tts_model_profile.dart
@@ -1,7 +1,7 @@
 /// Per-model runtime descriptor for the generic Matcha-CFM TTS pipeline.
 ///
 /// This is what makes the TTS pipeline SELECTABLE without per-model classes:
-/// `TtsCore` (Task 2.3) is generic over [TtsModelProfile] — matcha/kokoro/
+/// `TtsCore` is generic over [TtsModelProfile] — matcha/kokoro/
 /// supertonic are data (a profile + a catalog entry), not separate synthesizer
 /// classes. Mirrors `SttModelProfile`. Unlike STT, the numeric synthesis
 /// params (mel dims, CFM steps, sample rate, …) are NOT baked in here — Matcha
@@ -42,8 +42,8 @@ enum G2pStrategy { dictionary, dictionaryPlusNeural, neuralOnly, none }
 /// `.tflite` to load for which stage; it does not auto-detect roles from the
 /// compiled models' tensor layouts.
 class TtsModelProfile {
-  /// Matcha-TTS bundle: filenames match `TtsModelType.matcha.manifest`
-  /// (Task 1.3), here they get roles.
+  /// Matcha-TTS bundle: filenames match `TtsModelType.matcha.manifest`;
+  /// here they get roles.
   const TtsModelProfile.matcha()
     : pipeline = TtsPipelineKind.matchaCfm,
       textEncoderFile = 'matcha_textenc_fp16.tflite',
@@ -122,7 +122,7 @@ class TtsModelProfile {
   /// token models.
   final G2pStrategy? g2p;
 
-  /// Selects the `TtsTextNormalizer` (Task 4); matcha → `'en_us'`.
+  /// Selects the `TtsTextNormalizer`; matcha → `'en_us'`.
   final String locale;
 
   /// Resolve the runtime profile for [t]. Only [TtsModelType.matcha] and
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
index 8f3df8d6..290529c9 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_languages.dart
@@ -2,11 +2,11 @@
 //
 // Single source of truth for THREE consumers that must never drift apart:
 //  - `Qwen3Prompt.build` (`qwen3_prompt.dart`), which maps a language name to
-//    its control-token id for the talker prompt (Task 1.4/5.1).
-//  - `LiteRtSpeechSynthesizer.create`'s create-time language validator
-//    (Task 5.4) — fails loud with an `ArgumentError` for an unknown language
-//    BEFORE spawning the ~1.9 GB `TtsWorker`, rather than deep inside the
-//    worker isolate on the first `synthesize` call.
+//    its control-token id for the talker prompt.
+//  - `LiteRtSpeechSynthesizer.create`'s create-time language validator —
+//    fails loud with an `ArgumentError` for an unknown language BEFORE
+//    spawning the ~1.9 GB `TtsWorker`, rather than deep inside the worker
+//    isolate on the first `synthesize` call.
 //  - the example's language picker (`tts_screen.dart`), which populates its
 //    dropdown from [qwen3SupportedLanguages] instead of hardcoding a second
 //    copy of the list.
@@ -19,7 +19,7 @@
 library;
 
 /// Language id map from the model config (`talker_config.codec_language_id`).
-/// Ported from `text_to_speech_lm/python/qwen3_tts_pipeline.py:59-70`.
+/// Ported from `text_to_speech_lm/python/qwen3_tts_pipeline.py LANGUAGE_IDS`.
 const Map<String, int> languageIds = {
   'chinese': 2055,
   'english': 2050,
@@ -70,6 +70,6 @@ void assertQwen3LanguageSupported(String language) {
 /// `LiteRtSpeechSynthesizer.create` but then miss `Qwen3Prompt.build`'s
 /// `'auto'` comparison and throw `ArgumentError` AFTER the ~1.9 GB model
 /// load, at the first `synthesize` call — defeating create-time fail-fast
-/// for exactly that value (Task 5.4 review, bundled fix). Call this once,
-/// at the `create` boundary, immediately after validation succeeds.
+/// for exactly that value. Call this once, at the `create` boundary,
+/// immediately after validation succeeds.
 String normalizeQwen3Language(String language) => language.toLowerCase();
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
index 19d8c86b..bfb4227e 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_prompt.dart
@@ -9,11 +9,12 @@
 //    audio frame, consumed during the per-frame decode loop,
 //  - `ttsPad` — the fallback embedding used once `trailing` is exhausted.
 //
-// Ports `Qwen3TtsPipeline._build_prompt` verbatim from
-// `text_to_speech_lm/python/qwen3_tts_pipeline.py:279-313` (plus its
-// module-level token constants at lines 43-70), reading `ids` (already
-// tokenized by the frontend, see `Qwen2BpeEncoder`) instead of re-tokenizing
-// raw text.
+// Ports `Qwen3TtsPipeline._build_prompt` verbatim from the recipe's
+// `qwen3_tts_pipeline.py` (see `qwen3_tts_core.dart`'s file header for
+// where it's vendored; plus its module-level token/language constants —
+// `_CODEC_*`, `_TTS_*`, `LANGUAGE_IDS`), reading `ids` (already tokenized
+// by the frontend, see `Qwen2BpeEncoder`) instead of re-tokenizing raw
+// text.
 //
 // This file is pure Dart (`dart:typed_data` only) — no Flutter import — so
 // it can be unit-tested without a device.
@@ -27,7 +28,8 @@ import 'qwen3_tables.dart';
 const int _hidden = 1024;
 
 // Talker codec-token vocabulary layout (ids >= 2048 are control tokens).
-// qwen3_tts_pipeline.py:44-51.
+// Matches the recipe's codec-token constants block (`_CODEC_VOCAB` ..
+// `_CODEC_NOTHINK` in `qwen3_tts_pipeline.py`).
 const int _codecPad = 2148;
 const int _codecBos = 2149;
 const int _codecThink = 2154;
@@ -35,7 +37,8 @@ const int _codecNothink = 2155;
 const int _codecThinkBos = 2156;
 const int _codecThinkEos = 2157;
 
-// Text-side special tokens (Qwen2 BPE vocabulary). qwen3_tts_pipeline.py:54-56.
+// Text-side special tokens (Qwen2 BPE vocabulary). Matches the recipe's
+// `_TTS_BOS`/`_TTS_EOS`/`_TTS_PAD` in `qwen3_tts_pipeline.py`.
 const int _ttsBos = 151672;
 const int _ttsEos = 151673;
 const int _ttsPad = 151671;
@@ -53,7 +56,7 @@ class Qwen3PromptResult {
 
   /// Flattened prefill embeddings, row-major `[promptLen * 1024]`. Fed to
   /// the talker's `prefill_32` signature (right-padded to 32 rows by the
-  /// caller — see `_run_prefill`, a later task).
+  /// caller — see `Qwen3TtsCore.runPrefill`, which ports `_run_prefill`).
   final Float32List prefill;
 
   /// Number of rows in [prefill] (`prefill.length == promptLen * 1024`).
@@ -65,7 +68,8 @@ class Qwen3PromptResult {
   /// Per-frame streamed text-conditioning rows, each `[1024]`: the
   /// remaining text embeddings (`ids[4:-5]`) followed by the `tts_eos`
   /// embedding. Consumed one row per decoded audio frame; once exhausted,
-  /// [ttsPad] is added instead (see the decode loop, a later task).
+  /// [ttsPad] is added instead (see the decode loop, `synthesize`, in
+  /// `qwen3_tts_core.dart`).
   final List<Float32List> trailing;
 
   /// The `[1024]` TTS pad embedding, added once [trailing] is exhausted.
@@ -74,9 +78,8 @@ class Qwen3PromptResult {
 
 /// Builds the Qwen3-TTS talker prompt.
 ///
-/// Ports `Qwen3TtsPipeline._build_prompt`
-/// (`text_to_speech_lm/python/qwen3_tts_pipeline.py:279-313`) verbatim,
-/// given already-tokenized [ids] (the frontend's chat-template encoding —
+/// Ports `Qwen3TtsPipeline._build_prompt` verbatim, given already-tokenized
+/// [ids] (the frontend's chat-template encoding —
 /// see `Qwen2BpeEncoder`), a `[1024]` speaker x-vector [speaker], and a
 /// [language] (one of [languageIds]' keys, case-insensitive, or `'auto'`).
 class Qwen3Prompt {
@@ -104,7 +107,7 @@ class Qwen3Prompt {
       );
     }
 
-    // qwen3_tts_pipeline.py:295-299.
+    // qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     final List<int> control;
     if (language == 'auto') {
       control = [_codecNothink, _codecThinkBos, _codecThinkEos];
@@ -123,7 +126,7 @@ class Qwen3Prompt {
     }
 
     // tts_bos, tts_eos, tts_pad = embedText([_TTS_BOS, _TTS_EOS, _TTS_PAD]).
-    // qwen3_tts_pipeline.py:293-294.
+    // qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     final ttsSpecial = tables.embedText([_ttsBos, _ttsEos, _ttsPad]);
     final ttsBosRow = Float32List.sublistView(ttsSpecial, 0, _hidden);
     final ttsEosRow = Float32List.sublistView(ttsSpecial, _hidden, 2 * _hidden);
@@ -134,7 +137,7 @@ class Qwen3Prompt {
     );
 
     // codec_pre = codec_emb[control] ++ [speaker] ++ codec_emb[[PAD, BOS]].
-    // qwen3_tts_pipeline.py:300-304.
+    // qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     final codecPreLen = control.length + 1 + 2;
     final codecPre = List<Float32List>.generate(codecPreLen, (i) {
       if (i < control.length) return tables.codecEmbRow(control[i]);
@@ -143,12 +146,12 @@ class Qwen3Prompt {
       return tables.codecEmbRow(_codecBos);
     });
 
-    // role = embedText(ids[0:3]). qwen3_tts_pipeline.py:306.
+    // role = embedText(ids[0:3]). qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     final role = tables.embedText(ids.sublist(0, 3));
 
     // pads = repeat(tts_pad, len(codec_pre) - 2);
     // body = concat([pads, tts_bos]) + codec_pre[:-1]  (element-wise add).
-    // qwen3_tts_pipeline.py:307-308.
+    // qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     final bodyLen = codecPreLen - 1;
     final padsLen = codecPreLen - 2;
     final body = Float32List(bodyLen * _hidden);
@@ -161,7 +164,7 @@ class Qwen3Prompt {
       }
     }
 
-    // first_text = embedText(ids[3:4]) + codec_pre[-1]. qwen3_tts_pipeline.py:309.
+    // first_text = embedText(ids[3:4]) + codec_pre[-1]. qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     final firstTextEmbed = tables.embedText([ids[3]]);
     final firstText = Float32List(_hidden);
     final lastCodecPre = codecPre[codecPreLen - 1];
@@ -169,14 +172,14 @@ class Qwen3Prompt {
       firstText[k] = firstTextEmbed[k] + lastCodecPre[k];
     }
 
-    // prefill = concat(role, body, first_text). qwen3_tts_pipeline.py:310.
+    // prefill = concat(role, body, first_text). qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     final promptLen = 3 + bodyLen + 1;
     if (promptLen > 32) {
-      // Defensive sanity check mirroring `_run_prefill`'s `p > 32` guard
-      // (qwen3_tts_pipeline.py:318-319) — the talker's prefill signature is
-      // a fixed 32-row buffer. This is NOT a text-length limit: only role +
+      // Defensive sanity check mirroring `Qwen3TtsPipeline._run_prefill`'s
+      // `p > 32` guard — the talker's prefill signature is a fixed 32-row
+      // buffer. This is NOT a text-length limit: only role +
       // control/x-vector rows enter the prefill (promptLen is fixed at 10
-      // for every supported language), so it never trips in practice.
+      // for a named language, 9 for 'auto'), so it never trips in practice.
       throw StateError(
         'Qwen3Prompt.build: prefill length $promptLen exceeds the talker '
         'prefill_32 signature (32)',
@@ -187,7 +190,7 @@ class Qwen3Prompt {
     prefill.setRange(3 * _hidden, (3 + bodyLen) * _hidden, body);
     prefill.setRange((3 + bodyLen) * _hidden, promptLen * _hidden, firstText);
 
-    // trailing = concat(embedText(ids[4:-5]), tts_eos). qwen3_tts_pipeline.py:311-312.
+    // trailing = concat(embedText(ids[4:-5]), tts_eos). qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt.
     // Mirrors Python's permissive `ids[4:-5]` slicing (clamped to empty
     // rather than throwing) for very short inputs where `len(ids) - 5 < 4`.
     final trailingStop = ids.length - 5 < 4 ? 4 : ids.length - 5;
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart
index 1ed0fba5..1b003028 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_sampler.dart
@@ -1,10 +1,12 @@
 // Sampler + cb0 scoring for the Qwen3-TTS talker's per-frame codebook-0
 // (cb0) token pick.
 //
-// Ports `_pick` (`text_to_speech_lm/python/qwen3_tts_pipeline.py:467-490`)
-// and the per-step scoring edits applied before it in the decode loop
-// (`qwen3_tts_pipeline.py:223-225` for `suppress`, `:231-237` for the
-// min-new-tokens guard + HF repetition penalty) verbatim.
+// Ports `Qwen3TtsPipeline._pick` (the recipe's `qwen3_tts_pipeline.py` —
+// see `qwen3_tts_core.dart`'s file header for where it's vendored and why
+// citations below name Python symbols, not line numbers) and the per-step
+// scoring edits applied before it in `Qwen3TtsPipeline.synthesize`
+// (`suppress`, the min-new-tokens guard, and the HF repetition penalty)
+// verbatim.
 //
 // This file is pure Dart (`dart:math` / `dart:typed_data` only) — no
 // Flutter import — so it can be unit-tested without a device and needs no
@@ -13,15 +15,15 @@
 import 'dart:math';
 import 'dart:typed_data';
 
-/// Talker codec-token vocabulary size. qwen3_tts_pipeline.py:44.
+/// Talker codec-token vocabulary size. qwen3_tts_pipeline.py _CODEC_VOCAB.
 const int _codecVocab = 3072;
 
-/// Codec end-of-sequence token id. qwen3_tts_pipeline.py:47.
+/// Codec end-of-sequence token id. qwen3_tts_pipeline.py _CODEC_EOS.
 const int _codecEos = 2150;
 
 /// Large negative "suppressed" score, added to logits to rule a token out
 /// of the argmax/sampling pick without producing `-inf` arithmetic hazards.
-/// qwen3_tts_pipeline.py:77.
+/// qwen3_tts_pipeline.py _NEG_INF.
 const double _negInf = -1e9;
 
 /// Builds the per-step control-token suppression vector.
@@ -30,7 +32,7 @@ const double _negInf = -1e9;
 /// `< 2048` are audible codebook-0 codes), so those are suppressed by
 /// `_negInf` — except [_codecEos], which is always a legal pick (the talker
 /// must be able to end the utterance). Ports
-/// `qwen3_tts_pipeline.py:223-225` verbatim:
+/// `qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize` verbatim:
 /// ```python
 /// suppress = np.zeros(_CODEC_VOCAB, np.float32)
 /// suppress[2048:] = _NEG_INF
@@ -51,7 +53,7 @@ Float32List buildSuppress() {
 /// array that is safe to mutate, e.g. a fresh copy of the raw logits, since
 /// the original logits are still needed elsewhere in the decode loop).
 ///
-/// Ports `qwen3_tts_pipeline.py:231-237` verbatim:
+/// Ports `qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize` verbatim:
 /// ```python
 /// scores = logits + suppress
 /// if len(frames) < 2:  # min_new_tokens=2
@@ -62,7 +64,7 @@ Float32List buildSuppress() {
 ///                      else scores[token] * repetition_penalty)
 /// ```
 /// [minNewTokensGuard] is the caller-evaluated `len(frames) < 2` condition
-/// (frame-count bookkeeping lives in the decode loop, a later task — this
+/// (frame-count bookkeeping lives in the decode loop, `synthesize` — this
 /// function only applies the resulting edit).
 void applyCb0Scoring(
   Float32List scores, {
@@ -86,7 +88,7 @@ void applyCb0Scoring(
 /// Deterministic, RNG-free pick: the argmax index of [logits].
 ///
 /// This is the golden-decode path (`do_sample=False` in the recipe):
-/// `return int(np.argmax(logits))` (`qwen3_tts_pipeline.py:482`). Matches
+/// `return int(np.argmax(logits))` (`qwen3_tts_pipeline.py _pick`). Matches
 /// numpy's `argmax` tie-break — the **first** (lowest-index) maximum wins.
 int pickGreedy(Float32List logits) {
   if (logits.isEmpty) {
@@ -110,7 +112,7 @@ int pickGreedy(Float32List logits) {
 /// Top-k / temperature sampling pick (production quality — not the golden
 /// gate, which uses [pickGreedy]).
 ///
-/// Ports `qwen3_tts_pipeline.py:483-490`'s sampling branch:
+/// Ports `qwen3_tts_pipeline.py _pick`'s sampling branch:
 /// ```python
 /// scaled = logits.astype(np.float64) / max(temperature, 1e-6)
 /// if top_k and top_k < len(scaled):
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart
index a8edd096..ade51675 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tables.dart
@@ -193,7 +193,7 @@ class Qwen3Tables {
   /// Applies the 2048->1024 text-projection MLP (SiLU activation) to [rows]
   /// (flat `[n * 2048]`, row-major). Returns a flat `[n * 1024]` array.
   ///
-  /// Ports `Qwen3TtsPipeline._project_text` (`qwen3_tts_pipeline.py:268`):
+  /// Ports `Qwen3TtsPipeline._project_text`:
   /// `h = rows @ w1.T + b1; h = h * sigmoid(h); out = h @ w2.T + b2`.
   /// `w1` is `(2048,2048)` so `h[j] = sum_k rows[k] * w1[j,k] + b1[j]`;
   /// `w2` is `(1024,2048)` so `out[i] = sum_j h[j] * w2[i,j] + b2[i]`.
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
index d646d9cf..ac3c498c 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
@@ -2,14 +2,13 @@
 // (`talker_int4.tflite` / `talker_fp32.tflite`), pinned by a spike ("C1",
 // 2026-08-03) that introspected the REAL graph out-of-band (independent of
 // this package's Dart FFI bindings) before any Dart code existed to load
-// it — see `docs/superpowers/plans/2026-08-03-qwen3-tts.md`'s "C1 de-risk"
-// section. This file's job is narrow: (1) name the frozen numbers so the
-// rest of the Qwen3 port (Tasks 2.2/2.3+) references `TalkerLayout.xxx`
-// instead of magic numbers, and (2) a load-time [TalkerLayout.assertLayout]
-// that re-verifies as much of the C1 spike's findings as the EXISTING bound
-// LiteRT C API surface allows, so a future model revision that reorders the
-// graph fails loud at load time instead of silently corrupting the decode
-// loop weeks later.
+// it. This file's job is narrow: (1) name the frozen numbers so the rest of
+// the Qwen3 port (`Qwen3TtsCore.runPrefill`/`runDecode`) references
+// `TalkerLayout.xxx` instead of magic numbers, and (2) a load-time
+// `TalkerLayout.assertLayout` that re-verifies as much of the C1 spike's
+// findings as the EXISTING bound LiteRT C API surface allows, so a future
+// model revision that reorders the graph fails loud at load time instead
+// of silently corrupting the decode loop weeks later.
 //
 // Talker signatures, in index order (there is no signature-NAME binding —
 // signatures are told apart purely by the `embeddings` input's time-dim: 1
@@ -49,9 +48,9 @@
 // `numTalkerInputs == 59` this per-index accessor allows.
 //
 // What it CANNOT check with the CURRENTLY bound API, and therefore treats
-// as trusted, frozen constants instead (the plan's explicit ruling: do NOT
-// add a new native binding, and do NOT probe an out-of-range index to
-// "discover" a count, to work around this): [numLayers], [numKvTensors],
+// as trusted, frozen constants instead (deliberately: do NOT add a new
+// native binding, and do NOT probe an out-of-range index to "discover" a
+// count, to work around this): [numLayers], [numKvTensors],
 // the exact output COUNTS (57 for decode / 56 for prefill_32/prefill_128),
 // the individual per-tensor shape of each of the 56 KV tensors, and the KV
 // input-order == KV output-order identity. `LiteRtGetCompiledModelOutput
@@ -187,8 +186,8 @@ class TalkerLayout {
 
     // `mask` (input 2): [1, 1, T, cacheLen] — cacheLen (the KV cache's
     // fixed capacity) is the load-bearing dim here; checked for every
-    // signature, not just its last dim (the brief's stated minimum), since
-    // the full shape is just as cheap to check via the same call.
+    // signature, not just its last dim (the minimum needed), since the
+    // full shape is just as cheap to check via the same call.
     _assertInputShape(bindings, talker, prefill32Sig, 2, 'prefill_32.mask', [
       1,
       1,
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index 99dbeb31..4fd6f976 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -1,35 +1,44 @@
 // Qwen3-TTS talker/MTP/codec graph loader + talker KV-cache prefill.
 //
+// This file (plus `qwen3_prompt.dart`, `qwen3_sampler.dart`,
+// `qwen3_talker_layout.dart`, `qwen3_tables.dart`) ports
+// `google-ai-edge/litert-samples`' `Qwen3TtsPipeline` reference recipe
+// (`samples/litert/text_to_speech_lm/python/qwen3_tts_pipeline.py`), a
+// frozen snapshot of which is vendored at `tool/qwen3/qwen3_tts_pipeline.py`
+// for citation/reproducibility. Citations below name the recipe's Python
+// symbols (class/method/constant), NOT line numbers — the vendored copy
+// carries an extra provenance-comment line versus upstream, so any :NNN
+// anchor would silently drift; see that file's own header comment.
+//
 // `Qwen3TtsCore.load` opens the 3 LiteRT graphs that make up the Qwen3-TTS
 // pipeline (`talker_int4.tflite`, `mtp_fp32.tflite`,
 // `codec_decoder_fp32.tflite`), the host embedding tables + text-projection
 // MLP (`Qwen3Tables`), and the Qwen2 byte-level BPE text encoder
 // (`Qwen2BpeEncoder`); asserts the talker's graph layout against the frozen
 // `TalkerLayout` constants; and introspects the MTP/codec graphs' fixed-size
-// inputs (`mtpCacheLen`, `mtpKvShape`, `codecChunk`) so later tasks (the MTP
-// inner loop, the codec sliding-window decode) don't need to re-open the
-// graphs to read them. Ports the constructor of
-// `Qwen3TtsPipeline.__init__` (`text_to_speech_lm/python/
-// qwen3_tts_pipeline.py:130-171`).
+// inputs (`mtpCacheLen`, `mtpKvShape`, `codecChunk`) so the MTP inner loop
+// ([Qwen3TtsCore.runMtp]) and the codec sliding-window decode
+// ([Qwen3TtsCore.decodeCodes]) don't need to re-open the graphs to read
+// them. Ports the constructor of `Qwen3TtsPipeline.__init__`.
 //
-// [Qwen3TtsCore.runPrefill] ports `Qwen3TtsPipeline._run_prefill`
-// (`qwen3_tts_pipeline.py:315-328`): right-pads the (<=32-row) prompt
-// embedding into the talker's fixed 32-row `prefill_32` signature, builds
-// the matching causal `mask`, runs it against an all-zero initial KV cache
-// (`qwen3_tts_pipeline.py:216-217`), and returns the 56 filled KV tensors —
-// this initializes the KV cache the decode loop ([Qwen3TtsCore.runDecode])
-// threads forward one step at a time.
+// [Qwen3TtsCore.runPrefill] ports `Qwen3TtsPipeline._run_prefill`:
+// right-pads the (<=32-row) prompt embedding into the talker's fixed
+// 32-row `prefill_32` signature, builds the matching causal `mask`, runs
+// it against an all-zero initial KV cache (`Qwen3TtsPipeline.synthesize`'s
+// KV-dict init), and returns the 56 filled KV tensors — this initializes
+// the KV cache the decode loop ([Qwen3TtsCore.runDecode]) threads forward
+// one step at a time.
 //
-// [Qwen3TtsCore.runDecode] ports `Qwen3TtsPipeline._run_decode`
-// (`qwen3_tts_pipeline.py:330-340`): builds the one-row causal `mask`
-// (`mask[...,:pos+1] = 0`, else `qwen3NegInf`) for the current KV-cache
-// write position, runs the talker's `decode` signature against the
-// threaded-forward KV cache, and splits the `[1,1,4096]` logits output into
-// codebook-0 logits (`[:3072]`) and the hidden-state tail (`[3072:]`)
-// consumed by the MTP graph (a later task). This is the correctness
-// milestone for the whole talker path: prefill -> decode -> KV threading ->
-// logit split -> cb0 scoring must reproduce the PyTorch reference's frame-0
-// cb0 exactly (see `qwen3_talker_decode_test.dart`'s golden gate).
+// [Qwen3TtsCore.runDecode] ports `Qwen3TtsPipeline._run_decode`: builds
+// the one-row causal `mask` (`mask[...,:pos+1] = 0`, else `qwen3NegInf`)
+// for the current KV-cache write position, runs the talker's `decode`
+// signature against the threaded-forward KV cache, and splits the
+// `[1,1,4096]` logits output into codebook-0 logits (`[:3072]`) and the
+// hidden-state tail (`[3072:]`) consumed by [runMtp]. This is the
+// correctness milestone for the whole talker path: prefill -> decode ->
+// KV threading -> logit split -> cb0 scoring must reproduce the PyTorch
+// reference's frame-0 cb0 exactly (see `qwen3_talker_decode_test.dart`'s
+// golden gate).
 //
 // FFI style + graph load/run machinery: same as `TtsCore`/`SttCore` — see
 // `litert_graph.dart`'s file header for the create -> run -> lock(Read) ->
@@ -41,48 +50,47 @@
 // directly; annotated `@visibleForTesting` to say so, mirroring
 // `TtsCore.planMelWindows`/`concatSegments`.
 //
-// [Qwen3TtsCore.runMtp] ports `Qwen3TtsPipeline._run_mtp`
-// (`qwen3_tts_pipeline.py:342-380`): the 16-step MTP inner loop that
-// predicts the 15 residual codebooks of one frame from the talker's hidden
-// state ([runDecode]'s `hidden`) + the already-picked codebook-0 token. The
-// MTP graph is single-signature (`args_0..4` -> `output_0..2`, no
-// prefill/decode split like the talker); [load] introspects `output_0`'s
-// shape (the 15-head residual-logit tensor, `[15, vocab]`) via the bulk
-// `getOutputTensorLayouts` accessor (there is no per-output-index
-// accessor — see [_readOutputShapes]'s doc) so this file never hardcodes
-// the residual vocabulary size.
+// [Qwen3TtsCore.runMtp] ports `Qwen3TtsPipeline._run_mtp`: the 16-step
+// MTP inner loop that predicts the 15 residual codebooks of one frame from
+// the talker's hidden state ([runDecode]'s `hidden`) + the already-picked
+// codebook-0 token. The MTP graph is single-signature (`args_0..4` ->
+// `output_0..2`, no prefill/decode split like the talker); [load]
+// introspects `output_0`'s shape (the 15-head residual-logit tensor,
+// `[15, vocab]`) via the bulk `getOutputTensorLayouts` accessor (there is
+// no per-output-index accessor — see [_readOutputShapes]'s doc) so this
+// file never hardcodes the residual vocabulary size.
 //
-// [Qwen3TtsCore.decodeCodes] ports `Qwen3TtsPipeline._decode_codes`
-// (`qwen3_tts_pipeline.py:382-399`): turns the accumulated `[T, 16]` codec
-// frames (codebook-0 + the 15 MTP residuals, one row per talker frame) into
-// 24 kHz PCM by running them through the codec-decoder graph in fixed-size
-// [codecChunk]-frame windows, each carrying 25 frames of LEFT CONTEXT from
-// the previous window (`ctx = 25`) that is decoded but then cropped back
-// out of the emitted audio — the codec is a small causal-ish conv stack, not
-// a fully streaming one, so re-feeding a tail of already-seen frames as
-// context on every step is what keeps chunk boundaries from producing
-// audible seams. Every codec call decodes exactly [codecChunk] frames'
-// worth of PCM (`[1, 1, codecChunk * _upsampleFactor]`) regardless of how
-// many of the window's rows are real (the rest of `buf` is left as
-// zero-padding); only the `window.length`-worth of frames actually fed are
-// kept from each call's output.
+// [Qwen3TtsCore.decodeCodes] ports `Qwen3TtsPipeline._decode_codes`: turns
+// the accumulated `[T, 16]` codec frames (codebook-0 + the 15 MTP
+// residuals, one row per talker frame) into 24 kHz PCM by running them
+// through the codec-decoder graph in fixed-size [codecChunk]-frame
+// windows, each carrying 25 frames of LEFT CONTEXT from the previous
+// window (`ctx = 25`) that is decoded but then cropped back out of the
+// emitted audio — the codec is a small causal-ish conv stack, not a fully
+// streaming one, so re-feeding a tail of already-seen frames as context on
+// every step is what keeps chunk boundaries from producing audible seams.
+// Every codec call decodes exactly [codecChunk] frames' worth of PCM
+// (`[1, 1, codecChunk * _upsampleFactor]`) regardless of how many of the
+// window's rows are real (the rest of `buf` is left as zero-padding); only
+// the `window.length`-worth of frames actually fed are kept from each
+// call's output.
 //
-// [Qwen3TtsCore.synthesize] ports `Qwen3TtsPipeline.synthesize`
-// (`qwen3_tts_pipeline.py:173-266`) verbatim — the host-orchestrated,
-// end-to-end AR loop that ties [runPrefill]/[runDecode]/[runMtp]/
-// [decodeCodes] together: tokenize the chat-template-wrapped text
-// (`Qwen2BpeEncoder`), build the prompt embeddings (`Qwen3Prompt.build`),
-// prefill + one initial decode step, then loop — score + pick cb0
-// ([buildSuppress]/[applyCb0Scoring]/[pickGreedy]/[pickSampled], EOS
-// breaks), run the MTP inner loop for the 15 residuals, accumulate the
-// frame, assemble the next step's talker embedding (codec-token embedding
-// of cb0 plus all 15 MTP-residual embeddings plus the next streamed-text/pad
-// row), and decode one more talker step — until EOS or [maxFrames]. This is
-// the culmination correctness gate for the whole pipeline: fp32-greedy
-// waveform correlation ≈ 1.0 vs the PyTorch reference
-// (`qwen3_synthesize_test.dart`). [Qwen3TtsCore.synthesizePcm16] is the same
-// loop, returning int16 LE mono PCM instead of `[-1, 1]` float samples, for
-// the background-isolate worker (a later task).
+// [Qwen3TtsCore.synthesize] ports `Qwen3TtsPipeline.synthesize` verbatim —
+// the host-orchestrated, end-to-end AR loop that ties [runPrefill]/
+// [runDecode]/[runMtp]/[decodeCodes] together: tokenize the
+// chat-template-wrapped text (`Qwen2BpeEncoder`), build the prompt
+// embeddings (`Qwen3Prompt.build`), prefill + one initial decode step,
+// then loop — score + pick cb0 ([buildSuppress]/[applyCb0Scoring]/
+// [pickGreedy]/[pickSampled], EOS breaks), run the MTP inner loop for the
+// 15 residuals, accumulate the frame, assemble the next step's talker
+// embedding (codec-token embedding of cb0 plus all 15 MTP-residual
+// embeddings plus the next streamed-text/pad row), and decode one more
+// talker step — until EOS or [maxFrames]. This is the culmination
+// correctness gate for the whole pipeline: fp32-greedy waveform
+// correlation ≈ 1.0 vs the PyTorch reference (`qwen3_synthesize_test.dart`).
+// [Qwen3TtsCore.synthesizePcm16] is the same loop, returning int16 LE mono
+// PCM instead of `[-1, 1]` float samples, for the isolate worker
+// (`_runQwen3Worker` in `tts_worker.dart`).
 
 import 'dart:ffi';
 import 'dart:io' show Platform;
@@ -126,7 +134,7 @@ const int _upsampleFactor = 1920;
 
 /// Number of MTP residual codebooks — matches `qwen3_tts_pipeline.py`'s
 /// module-level implicit `15` (the `arange(15)` in [Qwen3TtsCore.synthesize]'s
-/// embed-accumulation step, `qwen3_tts_pipeline.py:250`). Distinct from
+/// embed-accumulation step, `qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize`). Distinct from
 /// [_numCodeGroups] (`16` = cb0 + these 15 residuals).
 const int _mtpResidualGroups = 15;
 
@@ -140,7 +148,7 @@ const int _codecEos = 2150;
 
 /// Left-context frame count [Qwen3TtsCore.decodeCodes]'s sliding window
 /// re-feeds from the previous window on every step but one (`ctx`/`c` in
-/// `qwen3_tts_pipeline.py:384-392` — see this file's header). [codecChunk]
+/// `qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes` — see this file's header). [codecChunk]
 /// must exceed this or [Qwen3TtsCore.decodeCodes]'s window advance
 /// (`codecChunk - c`) never makes progress — checked at [Qwen3TtsCore.load]
 /// time, see the guard there.
@@ -293,9 +301,9 @@ class Qwen3TtsCore {
   final LoadedGraph _codec;
 
   /// Host embedding tables + text-projection MLP — used by the decode loop
-  /// (Task 2.3+) to turn codec-token / MTP-residual / text-token ids into
-  /// 1024-d talker-space embeddings. Not read by this task's [runPrefill]
-  /// (the caller supplies already-embedded prompt rows, e.g. via
+  /// (`runDecode`/`synthesize`) to turn codec-token / MTP-residual /
+  /// text-token ids into 1024-d talker-space embeddings. Not read by
+  /// [runPrefill] (the caller supplies already-embedded prompt rows, e.g. via
   /// `Qwen3Prompt.build`), but loaded here so a single [Qwen3TtsCore] owns
   /// every table the full pipeline needs.
   final Qwen3Tables _tables;
@@ -434,8 +442,8 @@ class Qwen3TtsCore {
       ];
 
       // MTP/codec are each single-signature graphs (signature index 0);
-      // their inputs are positional `args_N` == input index N (recipe
-      // `:162-171`).
+      // their inputs are positional `args_N` == input index N (recipe's
+      // `Qwen3TtsPipeline.__init__`).
       final mtpMaskShape = _readInputShape(
         bindings,
         mtp.compiledModel,
@@ -452,13 +460,14 @@ class Qwen3TtsCore {
         'mtp.args_3 (k-cache)',
       );
 
-      // MTP has 3 outputs (recipe `:373-376`: `output_0` residual-head
-      // logits, `output_1`/`output_2` the new k/v cache) — read all 3 via
+      // MTP has 3 outputs (recipe `Qwen3TtsPipeline._run_mtp`: `output_0`
+      // residual-head logits, `output_1`/`output_2` the new k/v cache) —
+      // read all 3 via
       // the bulk accessor (see [_readOutputShapes]'s doc for why a single
       // call must ask for all of them) and pick out `output_0` by shape:
       // it's the one that does NOT match [mtpKvShape] (k/v are both
       // `mtpKvShape`-shaped). Verified once, at load time, against the
-      // REAL compiled graph — not hardcoded — per Task 3.1's brief.
+      // REAL compiled graph — not hardcoded.
       final mtpOutputShapes = _readOutputShapes(
         bindings,
         mtp.compiledModel,
@@ -491,7 +500,7 @@ class Qwen3TtsCore {
         );
       }
       // `[15, vocab]` (observed) or `[1, 15, vocab]` (a leading batch dim,
-      // tolerated defensively — see Task 3.1's brief) — either way the
+      // tolerated defensively) — either way the
       // flat `output_0` buffer is row-major `[15 * vocab]`, so only
       // `vocab` (the last dim) is actually needed by [runMtp].
       final int mtpResidualVocab;
@@ -584,7 +593,7 @@ class Qwen3TtsCore {
   }
 
   /// All-zero initial KV cache — 56 tensors sized to [_kvShapes]. Port of
-  /// `qwen3_tts_pipeline.py:216-217`'s
+  /// `qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize`'s
   /// `kv = {n: np.zeros(shape, np.float32) for n in kv_names}`.
   List<Float32List> _zeroKv() => [
     for (final shape in _kvShapes)
@@ -593,12 +602,11 @@ class Qwen3TtsCore {
 
   /// Prefills the talker's KV cache from the (<=32-row) prompt embedding
   /// [prefillEmb] (flat `[promptLen * 1024]`, row-major — e.g.
-  /// `Qwen3Prompt.build`'s `prefill`). Port of
-  /// `Qwen3TtsPipeline._run_prefill` (`qwen3_tts_pipeline.py:315-328`):
+  /// `Qwen3Prompt.build`'s `prefill`). Port of `Qwen3TtsPipeline._run_prefill`:
   /// right-pads into the fixed 32-row `prefill_32` signature, builds the
   /// matching causal `mask`, runs against an all-zero initial KV cache
   /// ([_zeroKv]), and returns the 56 filled KV tensors — the new KV state a
-  /// caller threads into the first decode step (`runDecode`, Task 2.3).
+  /// caller threads into the first decode step (`runDecode`).
   ///
   /// Not true public API (no v1 consumer outside this package calls it
   /// directly) — exposed (not underscore-private) so
@@ -627,15 +635,15 @@ class Qwen3TtsCore {
       );
     }
 
-    // buf[1,32,1024]: right-padded prompt (qwen3_tts_pipeline.py:320-321).
+    // buf[1,32,1024]: right-padded prompt (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_prefill).
     final buf = Float32List(32 * TalkerLayout.embeddingDim);
     buf.setRange(0, prefillEmb.length, prefillEmb);
 
-    // input_pos = arange(32) (qwen3_tts_pipeline.py:326).
+    // input_pos = arange(32) (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_prefill).
     final inputPos = Int32List.fromList([for (var i = 0; i < 32; i++) i]);
 
     // mask[1,1,32,cacheLen]: causal, `mask[0,0,i,:min(i,p-1)+1] = 0.0` else
-    // qwen3NegInf (qwen3_tts_pipeline.py:322-324). Flattened row-major —
+    // qwen3NegInf (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_prefill). Flattened row-major —
     // row i occupies mask[i*cacheLen .. (i+1)*cacheLen).
     final cacheLen = TalkerLayout.cacheLen;
     final mask = Float32List(32 * cacheLen);
@@ -670,14 +678,14 @@ class Qwen3TtsCore {
 
   /// Runs one autoregressive talker decode step, threading [kv] (the 56
   /// tensors from the previous [runPrefill]/[runDecode] call) forward one
-  /// position. Port of `Qwen3TtsPipeline._run_decode`
-  /// (`qwen3_tts_pipeline.py:330-340`).
+  /// position. Port of `Qwen3TtsPipeline._run_decode`.
   ///
   /// [embed] (`[1024]`) is the current step's input embedding — for the
-  /// very first decode step this is the last prefill row
-  /// (`prefill[0, -1]`, recipe `:219-220`); for later steps (Task 4.2's
-  /// loop) it's the assembled next-frame embedding. [pos] is the KV-cache
-  /// write position (0-indexed, matching `input_pos` passed to the graph).
+  /// very first decode step this is the last prefill row (`prefill[0, -1]`,
+  /// recipe's `Qwen3TtsPipeline.synthesize`); for later steps (the AR loop
+  /// in [synthesize]) it's the assembled next-frame embedding. [pos] is the
+  /// KV-cache write position (0-indexed, matching `input_pos` passed to the
+  /// graph).
   ///
   /// Builds the one-row causal `mask` (`[1,1,1,cacheLen]`,
   /// `mask[...,:pos+1] = 0.0` else [qwen3NegInf]), runs the talker's
@@ -726,7 +734,7 @@ class Qwen3TtsCore {
     }
 
     // mask[1,1,1,cacheLen]: mask[...,:pos+1] = 0.0 else qwen3NegInf.
-    // qwen3_tts_pipeline.py:330-340 (the decode-step causal mask — every
+    // qwen3_tts_pipeline.py Qwen3TtsPipeline._run_decode (the decode-step causal mask — every
     // KV-cache slot up to and including `pos` is attendable, everything
     // after is not-yet-written).
     final mask = Float32List(cacheLen);
@@ -775,7 +783,7 @@ class Qwen3TtsCore {
   /// the 15 residual codebooks of one frame from the talker's last hidden
   /// state [hidden] (`[1024]`, [runDecode]'s `hidden` output) and the
   /// already-picked codebook-0 token [cb0]. Port of
-  /// `Qwen3TtsPipeline._run_mtp` (`qwen3_tts_pipeline.py:342-380`).
+  /// `Qwen3TtsPipeline._run_mtp`.
   ///
   /// The MTP graph is a single decode step over a fixed [mtpCacheLen]-slot
   /// (17) KV cache, invoked 16 times per frame (`t = 0..15`): two seed
@@ -798,7 +806,7 @@ class Qwen3TtsCore {
   /// [greedy] selects [pickGreedy] (`do_sample=False`, the golden path —
   /// `qwen3_mtp_test.dart`'s gate) when `true`, else [pickSampled] with
   /// [topK]/[temperature]/[rng] (`do_sample=True`, ported from
-  /// `qwen3_tts_pipeline.py:377-379`'s `_pick(..., do_sample, top_k,
+  /// `qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp`'s `_pick(..., do_sample, top_k,
   /// temperature, rng)` — the same top-k/temperature knobs are threaded
   /// through every one of the 15 residual heads, exactly as the recipe
   /// does). [rng] is required (and only consulted) when `greedy` is `false`.
@@ -834,7 +842,7 @@ class Qwen3TtsCore {
       );
     }
 
-    // k_all/v_all: qwen3_tts_pipeline.py:364-365
+    // k_all/v_all: qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp
     // (`k_all = np.zeros(self._mtp_kv_shape, np.float32); v_all =
     // np.zeros_like(k_all)`) — reassigned each step to the graph's own
     // `output_1`/`output_2`, same "thread the previous step's output back
@@ -843,7 +851,7 @@ class Qwen3TtsCore {
     var kAll = Float32List(kvCount);
     var vAll = Float32List(kvCount);
 
-    // feeds = [hidden, self._codec_emb[cb0]] (qwen3_tts_pipeline.py:366).
+    // feeds = [hidden, self._codec_emb[cb0]] (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp).
     final feeds = <Float32List>[hidden, _tables.codecEmbRow(cb0)];
     final codes = <int>[];
 
@@ -855,11 +863,11 @@ class Qwen3TtsCore {
 
     for (var t = 0; t < 16; t++) {
       // embed = (feeds[t] if t < 2 else self._mtp_emb[t - 2][codes[-1]])
-      // .reshape(1, 1, _HIDDEN) (qwen3_tts_pipeline.py:369-370).
+      // .reshape(1, 1, _HIDDEN) (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp).
       final embed = t < 2 ? feeds[t] : _tables.mtpEmbRow(t - 2, codes.last);
 
       // mask = np.where(np.arange(cache) <= t, 0.0, _NEG_INF)...
-      // .reshape(1, 1, 1, -1) (qwen3_tts_pipeline.py:371-372).
+      // .reshape(1, 1, 1, -1) (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp).
       final mask = Float32List(mtpCacheLen);
       for (var j = 0; j <= t; j++) {
         mask[j] = 0.0;
@@ -870,7 +878,7 @@ class Qwen3TtsCore {
 
       // out = self._mtp(args_0=embed, args_1=[t], args_2=mask,
       //                  args_3=k_all, args_4=v_all)
-      // (qwen3_tts_pipeline.py:373-375).
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp).
       final inputs = <GraphInput>[
         F32Input([1, 1, TalkerLayout.embeddingDim], embed),
         I32Input([1], Int32List.fromList([t])),
@@ -888,12 +896,12 @@ class Qwen3TtsCore {
       );
 
       // k_all, v_all = out['output_1'], out['output_2']
-      // (qwen3_tts_pipeline.py:376).
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp).
       kAll = out[1];
       vAll = out[2];
 
       // if t >= 1: codes.append(_pick(out['output_0'][t - 1], ...))
-      // (qwen3_tts_pipeline.py:377-379). `out[0]` is the flat, row-major
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_mtp). `out[0]` is the flat, row-major
       // `[15 * vocab]` (or `[1, 15, vocab]`) buffer — head `t - 1` is the
       // `vocab`-wide slice at that row, regardless of a leading batch dim
       // (row-major layout is unaffected by a leading size-1 axis).
@@ -921,9 +929,8 @@ class Qwen3TtsCore {
   /// Decodes the accumulated `[T, 16]` codec [frames] (row `t` = codebook-0
   /// + the 15 MTP residuals for talker frame `t`, e.g. every row of
   /// [runMtp]'s output prefixed with its `cb0`) into 24 kHz PCM in `[-1,
-  /// 1]`. Port of `Qwen3TtsPipeline._decode_codes`
-  /// (`qwen3_tts_pipeline.py:382-399`) — see this file's header for the
-  /// sliding-window-with-left-context rationale.
+  /// 1]`. Port of `Qwen3TtsPipeline._decode_codes` — see this file's header
+  /// for the sliding-window-with-left-context rationale.
   ///
   /// Walks [frames] in windows of at most [codecChunk] rows: each window
   /// after the first carries up to 25 rows of left context (`c = min(25,
@@ -959,21 +966,21 @@ class Qwen3TtsCore {
       }
     }
 
-    // chunk, ctx = self._codec_chunk, 25 (qwen3_tts_pipeline.py:384).
+    // chunk, ctx = self._codec_chunk, 25 (qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes).
     const ctx = _codecLeftContext;
     final chunk = codecChunk;
     final pieces = <Float32List>[];
     var i = 0;
     while (i < frames.length) {
       // c = min(ctx, i); j = min(i + chunk - c, len(codes))
-      // (qwen3_tts_pipeline.py:388-391).
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes).
       final c = math.min(ctx, i);
       final j = math.min(i + chunk - c, frames.length);
-      // window = codes[i - c:j] (qwen3_tts_pipeline.py:392).
+      // window = codes[i - c:j] (qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes).
       final window = frames.sublist(i - c, j);
 
       // buf = zeros(1, 16, chunk); buf[0, :, :len(window)] = window.T
-      // (qwen3_tts_pipeline.py:393-394) — flat row-major `[1,16,chunk]`:
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes) — flat row-major `[1,16,chunk]`:
       // codebook k, window position n -> buf[k * chunk + n].
       final buf = Int32List(_numCodeGroups * chunk);
       for (var n = 0; n < window.length; n++) {
@@ -984,7 +991,7 @@ class Qwen3TtsCore {
       }
 
       // out = self._codec(args_0=buf); wav = out.values()[0][0, 0]
-      // (qwen3_tts_pipeline.py:395-396).
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes).
       final out = runLiteRtGraph(
         _bindings,
         _codec.compiledModel,
@@ -999,7 +1006,7 @@ class Qwen3TtsCore {
       final wav = out[0];
 
       // pieces.append(wav[c * _UPSAMPLE:len(window) * _UPSAMPLE])
-      // (qwen3_tts_pipeline.py:397) — drop the left-context samples.
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes) — drop the left-context samples.
       pieces.add(
         Float32List.sublistView(
           wav,
@@ -1010,7 +1017,7 @@ class Qwen3TtsCore {
       i = j;
     }
 
-    // return np.concatenate(pieces) (qwen3_tts_pipeline.py:399).
+    // return np.concatenate(pieces) (qwen3_tts_pipeline.py Qwen3TtsPipeline._decode_codes).
     final total = pieces.fold<int>(0, (sum, p) => sum + p.length);
     final result = Float32List(total);
     var offset = 0;
@@ -1022,8 +1029,8 @@ class Qwen3TtsCore {
   }
 
   /// Synthesizes speech for [text] in the voice identified by [speaker].
-  /// Port of `Qwen3TtsPipeline.synthesize` (`qwen3_tts_pipeline.py:173-266`)
-  /// — see this file's header for the full loop shape.
+  /// Port of `Qwen3TtsPipeline.synthesize` — see this file's header for the
+  /// full loop shape.
   ///
   /// [speaker] is a `[1024]` x-vector identifying the target voice (see
   /// `Qwen3Prompt.build`'s doc comment). [language] is one of
@@ -1037,7 +1044,7 @@ class Qwen3TtsCore {
   /// [temperature] / [repetitionPenalty] are only consulted by the sampled
   /// path — [repetitionPenalty] scores the cb0 pick only (`applyCb0Scoring`
   /// over the `history` of previously-picked cb0 tokens), matching the
-  /// recipe's `history` set (`qwen3_tts_pipeline.py:228,234-237`). [seed]
+  /// recipe's `history` set (`Qwen3TtsPipeline.synthesize`). [seed]
   /// seeds the `dart:math.Random` [pickSampled]/[runMtp]'s sampled path
   /// draws from; the greedy path never touches it. [maxFrames] caps the
   /// number of generated 12.5 Hz frames (512 frames ≈ 41 s of audio).
@@ -1071,11 +1078,11 @@ class Qwen3TtsCore {
   }
 
   /// Same as [synthesize], but returns mono 16-bit PCM (little-endian)
-  /// bytes instead of `[-1, 1]` float samples — for the background-isolate
-  /// worker (a later task) that streams audio to a player expecting int16
-  /// PCM. Every float sample is clamped to `[-1, 1]`, scaled by `32767`,
-  /// and rounded before being written little-endian: `(sample.clamp(-1, 1)
-  /// * 32767).round()`.
+  /// bytes instead of `[-1, 1]` float samples — for the isolate worker
+  /// (`_runQwen3Worker` in `tts_worker.dart`) that streams audio to a
+  /// player expecting int16 PCM. Every float sample is clamped to `[-1, 1]`,
+  /// scaled by `32767`, and rounded before being written little-endian:
+  /// `(sample.clamp(-1, 1) * 32767).round()`.
   Uint8List synthesizePcm16(
     String text, {
     required Float32List speaker,
@@ -1109,9 +1116,8 @@ class Qwen3TtsCore {
 
   /// The end-to-end AR loop shared by [synthesize]/[synthesizePcm16], split
   /// out so both can call [decodeCodes] on the same `frames` without
-  /// duplicating the loop. Port of `Qwen3TtsPipeline.synthesize`
-  /// (`qwen3_tts_pipeline.py:173-266`, the part before `_decode_codes` at
-  /// `:259`).
+  /// duplicating the loop. Port of `Qwen3TtsPipeline.synthesize` — the part
+  /// before its `_decode_codes` call.
   List<List<int>> _synthesizeFrames({
     required String text,
     required Float32List speaker,
@@ -1129,7 +1135,7 @@ class Qwen3TtsCore {
     final rng = math.Random(seed);
 
     // ids = tokenizer.encode(f'<|im_start|>assistant\n{text}<|im_end|>\n
-    // <|im_start|>assistant\n').ids (qwen3_tts_pipeline.py:289-291).
+    // <|im_start|>assistant\n').ids (qwen3_tts_pipeline.py Qwen3TtsPipeline._build_prompt).
     final ids = _encoder.encode(
       '<|im_start|>assistant\n$text<|im_end|>\n<|im_start|>assistant\n',
     );
@@ -1152,15 +1158,15 @@ class Qwen3TtsCore {
     );
     var (cb0Logits, hidden, kv) = runDecode(initialKv, firstEmbed, pos);
 
-    // suppress = ...; qwen3_tts_pipeline.py:223-225.
+    // suppress = ...; qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize.
     final suppress = buildSuppress();
     final frames = <List<int>>[];
     final history = <int>{};
     var hitEos = false;
 
-    // while len(frames) < max_frames: ... (qwen3_tts_pipeline.py:230-256).
+    // while len(frames) < max_frames: ... (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
     while (frames.length < maxFrames) {
-      // scores = logits + suppress; ... (qwen3_tts_pipeline.py:231-237).
+      // scores = logits + suppress; ... (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
       // COPY cb0Logits first — applyCb0Scoring mutates its argument in
       // place (see its doc), and the original decode-step logits must not
       // be corrupted (nothing else reads them again this iteration, but
@@ -1173,24 +1179,24 @@ class Qwen3TtsCore {
         suppress: suppress,
         history: history,
         repetitionPenalty: repetitionPenalty,
-        // len(frames) < 2: min_new_tokens=2 (qwen3_tts_pipeline.py:232).
+        // len(frames) < 2: min_new_tokens=2 (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
         minNewTokensGuard: frames.length < 2,
       );
 
       // cb0 = _pick(scores, do_sample, top_k, temperature, rng); history.
-      // add(cb0) (qwen3_tts_pipeline.py:238-239).
+      // add(cb0) (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
       final cb0 = doSample
           ? pickSampled(scores, topK: topK, temperature: temperature, rng: rng)
           : pickGreedy(scores);
       history.add(cb0);
-      // if cb0 == _CODEC_EOS: break (qwen3_tts_pipeline.py:240-241).
+      // if cb0 == _CODEC_EOS: break (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
       if (cb0 == _codecEos) {
         hitEos = true;
         break;
       }
 
       // residual = _run_mtp(hidden, cb0, do_sample, top_k, temperature,
-      // rng) (qwen3_tts_pipeline.py:244-245).
+      // rng) (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
       final residual = runMtp(
         hidden,
         cb0,
@@ -1199,11 +1205,11 @@ class Qwen3TtsCore {
         temperature: temperature,
         rng: rng,
       );
-      // frames.append([cb0] + residual) (qwen3_tts_pipeline.py:247).
+      // frames.append([cb0] + residual) (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
       frames.add([cb0, ...residual]);
 
       // embed = codec_emb[cb0] + mtp_emb[arange(15), residual].sum(0)
-      // (qwen3_tts_pipeline.py:249-250) — element-wise add over ALL 15 MTP
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize) — element-wise add over ALL 15 MTP
       // residual groups (unlike [runMtp]'s own inner loop, which only ever
       // embeds groups 0..13 while picking; group 14 is used here, for the
       // FIRST time, to assemble the NEXT talker step's input).
@@ -1219,7 +1225,7 @@ class Qwen3TtsCore {
         }
       }
       // step = len(frames) - 1; embed += trailing[step] if step <
-      // len(trailing) else tts_pad (qwen3_tts_pipeline.py:251-252).
+      // len(trailing) else tts_pad (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
       final step = frames.length - 1;
       final addend = step < prompt.trailing.length
           ? prompt.trailing[step]
@@ -1229,7 +1235,7 @@ class Qwen3TtsCore {
       }
 
       // pos += 1; logits, hidden, kv = _run_decode(kv, embed, pos)
-      // (qwen3_tts_pipeline.py:253-255).
+      // (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
       pos++;
       (cb0Logits, hidden, kv) = runDecode(kv, embed, pos);
     }
diff --git a/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart b/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart
index f252aaf5..10e8d748 100644
--- a/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart
+++ b/packages/flutter_gemma_speech/lib/src/tts/tts_text_frontend.dart
@@ -1,7 +1,7 @@
 /// Text-frontend seam: resolves the pipeline-specific frontend (currently
 /// only Matcha-CFM's `MatchaTextFrontend`) from a [TtsModelProfile]. The
-/// analog of STT's tokenizer seam — `TtsCore` (Task 2.3) only ever talks to
-/// this interface, never to a concrete frontend class.
+/// analog of STT's tokenizer seam — `TtsCore` only ever talks to this
+/// interface, never to a concrete frontend class.
 library;
 
 import '../model/tts_model_profile.dart';
@@ -9,8 +9,8 @@ import 'matcha_text_frontend.dart';
 import 'tts_frontend_input.dart';
 
 /// Resolves an out-of-dictionary word to its IPA transcription via a neural
-/// G2P model (`TtsCore.neuralG2p`, Task 7), wired in by the worker (Task 11).
-/// A frontend built without a resolver still throws on OOV.
+/// G2P model (`TtsCore.neuralG2p`), wired in by the worker. A frontend
+/// built without a resolver still throws on OOV.
 typedef NeuralG2pResolver = String Function(String word);
 
 /// text -> `TtsCore`-ready frontend input, dispatched by
@@ -38,8 +38,8 @@ abstract class TtsTextFrontend {
     ),
     // Qwen3 does its own BPE tokenization (`Qwen2BpeEncoder` +
     // `Qwen3Prompt`) and is driven by `Qwen3TtsCore`, not this
-    // Matcha-only frontend seam — the worker (Task 5.3) dispatches to it
-    // directly and never calls `TtsTextFrontend.load` for this pipeline
+    // Matcha-only frontend seam — the worker (`_runQwen3Worker`) dispatches
+    // to it directly and never calls `TtsTextFrontend.load` for this pipeline
     // kind. Fail-loud rather than silently running Matcha's phoneme
     // frontend against a Qwen3 bundle.
     TtsPipelineKind.qwen3ArCodec => throw StateError(
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart
index 997a0c2b..db65aed7 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_prefill_test.dart
@@ -81,7 +81,7 @@ void main() {
     );
     try {
       expect(core.sampleRate, 24000);
-      // recipe (qwen3_tts_pipeline.py:162-163): mtp_cache_len == 17 (16
+      // recipe (qwen3_tts_pipeline.py Qwen3TtsPipeline.__init__): mtp_cache_len == 17 (16
       // MTP residual steps + 1).
       expect(core.mtpCacheLen, 17);
       expect(core.mtpKvShape, isNotEmpty);
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart
index 48dd325f..73bd1d31 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_sampler_test.dart
@@ -3,9 +3,9 @@
 //
 // Pure unit tests — no model tables, no artifacts, no `@Tags` skip-guard.
 // Every input is a small hand-constructed vector so the expected output can
-// be hand-checked against the recipe's arithmetic
-// (`text_to_speech_lm/python/qwen3_tts_pipeline.py:223-225, 231-237,
-// 467-490`).
+// be hand-checked against the recipe's arithmetic — `synthesize`'s
+// `suppress`/scoring edits and `_pick`, both on `Qwen3TtsPipeline` in the
+// recipe's `qwen3_tts_pipeline.py`.
 
 import 'dart:math';
 import 'dart:typed_data';
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
index 980b6dce..34ca8cad 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
@@ -2,7 +2,7 @@
 // test for the whole Qwen3-TTS port: text in, waveform out, driving the
 // REAL talker + MTP + codec graphs through the host-orchestrated AR loop
 // (`Qwen3TtsCore.synthesize`, ported verbatim from
-// `Qwen3TtsPipeline.synthesize`, `qwen3_tts_pipeline.py:173-266`).
+// `Qwen3TtsPipeline.synthesize` in the recipe's `qwen3_tts_pipeline.py`).
 //
 // Every prior Qwen3 test isolated one stage of the pipeline against a
 // golden fixture generated by feeding that stage's REAL inputs straight
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart
index 4b6948b4..6764879a 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_talker_decode_test.dart
@@ -147,11 +147,11 @@ void main() {
           tables: tables,
         );
 
-        // _run_prefill (qwen3_tts_pipeline.py:315-328).
+        // _run_prefill (qwen3_tts_pipeline.py Qwen3TtsPipeline._run_prefill).
         final kv = core.runPrefill(prompt.prefill, prompt.promptLen);
 
         // Initial decode step: embed = prefill[0, -1] (the last prompt
-        // row), pos = promptLen - 1 (recipe :219-220).
+        // row), pos = promptLen - 1 (recipe's `Qwen3TtsPipeline.synthesize`).
         final promptLen = prompt.promptLen;
         final pos = promptLen - 1;
         final embed = Float32List.sublistView(
diff --git a/packages/flutter_gemma_speech/tool/qwen3/qwen3_tts_pipeline.py b/packages/flutter_gemma_speech/tool/qwen3/qwen3_tts_pipeline.py
new file mode 100644
index 00000000..89583dd5
--- /dev/null
+++ b/packages/flutter_gemma_speech/tool/qwen3/qwen3_tts_pipeline.py
@@ -0,0 +1,491 @@
+# Copyright 2026 The Google AI Edge Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+# Vendored frozen snapshot from google-ai-edge/litert-samples (samples/litert/text_to_speech_lm/python/qwen3_tts_pipeline.py), pinned 2026-08-03, for citation/reproducibility only — not maintained here.
+"""Qwen3-TTS text-to-speech on LiteRT (host-orchestrated Compiled Model loop).
+
+Qwen3-TTS generates speech as 12.5 Hz frames of 16 codec tokens: a Qwen3-style
+talker LM predicts the first (semantic) codebook, a small "MTP" transformer
+autoregressively predicts the 15 residual codebooks of each frame, and a codec
+decoder turns the accumulated codes into 24 kHz PCM. LiteRT-LM's Engine decode
+loop cannot express this structure yet (multi-codebook embedding aggregation,
+per-frame inner loop, audio output), so this sample drives the three converted
+.tflite graphs from a host-side Python loop, the same pattern as the Matcha-TTS
+sample in this repository.
+
+The graphs and host-side tables are published at
+https://huggingface.co/litert-community/Qwen3-TTS-12Hz-0.6B-Base and were
+converted with the scripts in `models/qwen/qwen3_tts/converted/`. The host
+loop reproduces the PyTorch reference implementation token-for-token under
+greedy decoding (waveform correlation 1.0).
+"""
+
+import dataclasses
+import time
+
+import numpy as np
+import tokenizers
+
+from ai_edge_litert.compiled_model import CompiledModel
+from ai_edge_litert.options import CpuOptions
+from ai_edge_litert.options import Options
+
+# Talker codec-token vocabulary layout (ids >= 2048 are control tokens).
+_CODEC_VOCAB = 3072
+_CODEC_PAD = 2148
+_CODEC_BOS = 2149
+_CODEC_EOS = 2150
+_CODEC_THINK = 2154
+_CODEC_THINK_BOS = 2156
+_CODEC_THINK_EOS = 2157
+_CODEC_NOTHINK = 2155
+
+# Text-side special tokens (Qwen2 BPE vocabulary).
+_TTS_BOS = 151672
+_TTS_EOS = 151673
+_TTS_PAD = 151671
+
+# Language id map from the model config (talker_config.codec_language_id).
+LANGUAGE_IDS = {
+    'chinese': 2055,
+    'english': 2050,
+    'german': 2053,
+    'italian': 2070,
+    'portuguese': 2071,
+    'spanish': 2054,
+    'japanese': 2058,
+    'korean': 2064,
+    'french': 2061,
+    'russian': 2069,
+}
+
+_HIDDEN = 1024
+_NUM_CODE_GROUPS = 16
+_FRAME_RATE_HZ = 12.5
+_SAMPLE_RATE = 24000
+_UPSAMPLE = 1920  # codec frames -> PCM samples
+_NEG_INF = -1e9
+
+
+@dataclasses.dataclass
+class SynthesisResult:
+    """Synthesized audio plus timing metadata.
+
+    Attributes:
+        waveform: Mono float32 PCM in [-1, 1] at 24 kHz.
+        sample_rate: Output sample rate in Hz (always 24000).
+        num_frames: Number of generated 12.5 Hz codec frames.
+        prefill_seconds: Wall time of the prompt prefill.
+        talker_seconds: Wall time spent in talker decode calls.
+        mtp_seconds: Wall time spent in the MTP inner loops.
+        codec_seconds: Wall time of codec decoding.
+    """
+
+    waveform: np.ndarray
+    sample_rate: int
+    num_frames: int
+    prefill_seconds: float
+    talker_seconds: float
+    mtp_seconds: float
+    codec_seconds: float
+
+    @property
+    def rtf(self) -> float:
+        """Real-time factor (wall time / audio duration)."""
+        wall = (self.prefill_seconds + self.talker_seconds +
+                self.mtp_seconds + self.codec_seconds)
+        return wall / (len(self.waveform) / self.sample_rate)
+
+
+class Qwen3TtsPipeline:
+    """Host-orchestrated Qwen3-TTS pipeline over three LiteRT graphs.
+
+    The pipeline owns the tokenizer, the embedding tables (kept host-side as
+    NumPy arrays) and three compiled models: talker (prefill_32 + decode
+    signatures with an explicit KV cache), MTP decode step, and the codec
+    decoder. `synthesize()` runs the full text-to-waveform loop.
+    """
+
+    def __init__(self,
+                 model_dir: str,
+                 talker_file: str = 'talker_int4.tflite',
+                 num_threads: int = 8,
+                 mtp_threads: int = 1):
+        """Loads graphs and host tables.
+
+        Args:
+            model_dir: Directory with the published model files (see the
+                Hugging Face repo layout).
+            talker_file: Talker .tflite file name; `talker_int4.tflite`
+                (smaller, faster) or `talker_fp32.tflite` (bit-exact vs the
+                PyTorch reference under greedy decoding).
+            num_threads: XNNPACK threads for the talker and codec graphs.
+            mtp_threads: XNNPACK threads for the small MTP graph (1 is
+                fastest in practice; its matmuls are too small to scale).
+        """
+        self._tokenizer = tokenizers.Tokenizer.from_file(
+            f'{model_dir}/tokenizer.json')
+
+        self._codec_emb = _load_fp32(
+            f'{model_dir}/tables/codec_embedding_fp32.npy')
+        self._mtp_emb = _load_fp32(
+            f'{model_dir}/tables/mtp_embeddings_fp16.npy')
+        # The 1.2 GB (fp32) text embedding stays memory-mapped; rows are
+        # up-cast on lookup.
+        self._text_emb = np.load(
+            f'{model_dir}/tables/text_embedding_fp16.npy', mmap_mode='r')
+        proj = np.load(f'{model_dir}/tables/text_projection_fp32.npz')
+        self._proj_w1, self._proj_b1 = proj['w1'], proj['b1']
+        self._proj_w2, self._proj_b2 = proj['w2'], proj['b2']
+
+        talker = CompiledModel.from_file(f'{model_dir}/{talker_file}',
+                                         options=_cpu_options(num_threads))
+        self._prefill = _SignatureRunner(talker, 'prefill_32')
+        self._decode = _SignatureRunner(talker, 'decode')
+        self._kv_names = [n for n in self._decode.get_input_details()
+                          if n.startswith('kv_cache')]
+        self._cache_len = self._decode.get_input_details()['mask']['shape'][-1]
+
+        mtp = CompiledModel.from_file(f'{model_dir}/mtp_fp32.tflite',
+                                      options=_cpu_options(mtp_threads))
+        self._mtp = _SignatureRunner(mtp)
+        self._mtp_cache_len = self._mtp.get_input_details()['args_2'][
+            'shape'][-1]
+        self._mtp_kv_shape = self._mtp.get_input_details()['args_3']['shape']
+
+        codec = CompiledModel.from_file(
+            f'{model_dir}/codec_decoder_fp32.tflite',
+            options=_cpu_options(num_threads))
+        self._codec = _SignatureRunner(codec)
+        self._codec_chunk = self._codec.get_input_details()['args_0'][
+            'shape'][-1]
+
+    def synthesize(self,
+                   text: str,
+                   speaker_embedding: np.ndarray,
+                   language: str = 'english',
+                   do_sample: bool = True,
+                   top_k: int = 50,
+                   temperature: float = 0.9,
+                   repetition_penalty: float = 1.05,
+                   max_frames: int = 512,
+                   seed: int | None = None) -> SynthesisResult:
+        """Synthesizes speech for `text` in the given voice.
+
+        Args:
+            text: Text to speak.
+            speaker_embedding: 1024-d x-vector of the target voice (see
+                `models/qwen/qwen3_tts/converted/extract_speaker_embedding.py`
+                to enroll a new voice from ~3 s of reference audio).
+            language: One of LANGUAGE_IDS keys, or 'auto'.
+            do_sample: Sample with top-k/temperature (the model default) if
+                True; greedy argmax (deterministic, matches the PyTorch
+                reference token-for-token) if False.
+            top_k: Top-k for sampling on both talker and MTP.
+            temperature: Sampling temperature on both talker and MTP.
+            repetition_penalty: HF-semantics penalty over the generated
+                first-codebook history.
+            max_frames: Frame cap (512 frames = ~41 s of audio).
+            seed: RNG seed for sampling.
+
+        Returns:
+            A SynthesisResult with the waveform and stage timings.
+
+        Raises:
+            ValueError: If `language` is not supported.
+        """
+        if language != 'auto' and language.lower() not in LANGUAGE_IDS:
+            raise ValueError(
+                f'language must be "auto" or one of {sorted(LANGUAGE_IDS)}')
+        rng = np.random.default_rng(seed)
+
+        prefill, trailing, tts_pad = self._build_prompt(
+            text, speaker_embedding, language)
+
+        t0 = time.time()
+        kv = {n: np.zeros(self._decode.get_input_details()[n]['shape'],
+                          np.float32) for n in self._kv_names}
+        kv = self._run_prefill(kv, prefill)
+        pos = prefill.shape[1] - 1
+        logits, hidden, kv = self._run_decode(kv, prefill[0, -1], pos)
+        prefill_s = time.time() - t0
+
+        suppress = np.zeros(_CODEC_VOCAB, np.float32)
+        suppress[2048:] = _NEG_INF
+        suppress[_CODEC_EOS] = 0.0
+
+        frames = []
+        history = set()
+        talker_s = mtp_s = 0.0
+        while len(frames) < max_frames:
+            scores = logits + suppress
+            if len(frames) < 2:  # min_new_tokens=2
+                scores[_CODEC_EOS] = _NEG_INF
+            for token in history:
+                scores[token] = (scores[token] / repetition_penalty
+                                 if scores[token] > 0
+                                 else scores[token] * repetition_penalty)
+            cb0 = _pick(scores, do_sample, top_k, temperature, rng)
+            history.add(cb0)
+            if cb0 == _CODEC_EOS:
+                break
+
+            t0 = time.time()
+            residual = self._run_mtp(hidden, cb0, do_sample, top_k,
+                                     temperature, rng)
+            mtp_s += time.time() - t0
+            frames.append([cb0] + residual)
+
+            embed = (self._codec_emb[cb0] +
+                     self._mtp_emb[np.arange(15), residual].sum(0))
+            step = len(frames) - 1
+            embed += trailing[step] if step < len(trailing) else tts_pad
+            pos += 1
+            t0 = time.time()
+            logits, hidden, kv = self._run_decode(kv, embed, pos)
+            talker_s += time.time() - t0
+
+        t0 = time.time()
+        waveform = self._decode_codes(np.array(frames, np.int32))
+        codec_s = time.time() - t0
+
+        return SynthesisResult(waveform=waveform, sample_rate=_SAMPLE_RATE,
+                               num_frames=len(frames),
+                               prefill_seconds=prefill_s,
+                               talker_seconds=talker_s, mtp_seconds=mtp_s,
+                               codec_seconds=codec_s)
+
+    def _project_text(self, rows: np.ndarray) -> np.ndarray:
+        """Applies the 2048->1024 text projection MLP (SiLU)."""
+        h = rows @ self._proj_w1.T + self._proj_b1
+        h = h / (1.0 + np.exp(-h))  # SiLU: x * sigmoid(x)
+        return (h @ self._proj_w2.T + self._proj_b2).astype(np.float32)
+
+    def _embed_text(self, ids: np.ndarray) -> np.ndarray:
+        """Looks up and projects text-embedding rows to talker space."""
+        rows = np.asarray(self._text_emb[ids], np.float32)
+        return self._project_text(rows)
+
+    def _build_prompt(self, text: str, speaker_embedding: np.ndarray,
+                      language: str):
+        """Builds prefill embeddings and the streamed text conditioning.
+
+        Mirrors the reference `Qwen3TTSForConditionalGeneration.generate`
+        prompt assembly for x-vector voice cloning in streaming mode.
+
+        Returns:
+            (prefill [1, P, 1024], trailing [L, 1024], tts_pad [1024]).
+        """
+        ids = np.array(self._tokenizer.encode(
+            f'<|im_start|>assistant\n{text}<|im_end|>\n'
+            '<|im_start|>assistant\n').ids)
+
+        tts_bos, tts_eos, tts_pad = self._embed_text(
+            np.array([_TTS_BOS, _TTS_EOS, _TTS_PAD]))
+        if language == 'auto':
+            control = [_CODEC_NOTHINK, _CODEC_THINK_BOS, _CODEC_THINK_EOS]
+        else:
+            control = [_CODEC_THINK, _CODEC_THINK_BOS,
+                       LANGUAGE_IDS[language.lower()], _CODEC_THINK_EOS]
+        codec_pre = np.concatenate([
+            self._codec_emb[control],
+            speaker_embedding.reshape(1, _HIDDEN).astype(np.float32),
+            self._codec_emb[[_CODEC_PAD, _CODEC_BOS]],
+        ], 0)
+
+        role = self._embed_text(ids[:3])  # <|im_start|>assistant\n
+        pads = np.repeat(tts_pad[None], len(codec_pre) - 2, 0)
+        body = np.concatenate([pads, tts_bos[None]], 0) + codec_pre[:-1]
+        first_text = self._embed_text(ids[3:4]) + codec_pre[-1:]
+        prefill = np.concatenate([role, body, first_text], 0)[None]
+        trailing = np.concatenate(
+            [self._embed_text(ids[4:-5]), tts_eos[None]], 0)
+        return prefill.astype(np.float32), trailing, tts_pad
+
+    def _run_prefill(self, kv, prefill: np.ndarray):
+        """Prefills the talker KV cache (32-token signature, right-padded)."""
+        p = prefill.shape[1]
+        if p > 32:
+            raise ValueError(f'prompt too long for prefill_32: {p}')
+        buf = np.zeros((1, 32, _HIDDEN), np.float32)
+        buf[:, :p] = prefill
+        mask = np.full((1, 1, 32, self._cache_len), _NEG_INF, np.float32)
+        for i in range(32):
+            mask[0, 0, i, :min(i, p - 1) + 1] = 0.0
+        out = self._prefill(embeddings=buf,
+                            input_pos=np.arange(32, dtype=np.int32),
+                            mask=mask, **kv)
+        return out
+
+    def _run_decode(self, kv, embed: np.ndarray, pos: int):
+        """One talker decode step; returns (cb0 logits, hidden, new kv)."""
+        mask = np.full((1, 1, 1, self._cache_len), _NEG_INF, np.float32)
+        mask[..., :pos + 1] = 0.0
+        out = self._decode(
+            embeddings=embed.reshape(1, 1, _HIDDEN).astype(np.float32),
+            input_pos=np.array([pos], np.int32), mask=mask, **kv)
+        logits = out.pop('logits')[0, 0]
+        # The exported lm_head is [codec logits (3072) | identity (1024)]:
+        # the tail carries the last hidden state, which seeds the MTP.
+        return logits[:_CODEC_VOCAB], logits[_CODEC_VOCAB:], out
+
+    def _run_mtp(self, hidden: np.ndarray, cb0: int, do_sample: bool,
+                 top_k: int, temperature: float, rng) -> list[int]:
+        """Runs the 15-step MTP inner loop for one frame.
+
+        The MTP graph is a single decode step over a 17-slot KV cache; it is
+        invoked 17 times per frame: two seed feeds (talker hidden state, cb0
+        embedding), then one feed per residual codebook. Step k uses
+        embedding table k-1 and lm_head k (the graph outputs all 15 heads;
+        the host picks).
+
+        Args:
+            hidden: Talker last hidden state for this frame [1024].
+            cb0: Sampled first-codebook token id.
+            do_sample: Sampling vs greedy for the residual codebooks.
+            top_k: Top-k for sampling.
+            temperature: Sampling temperature.
+            rng: NumPy random generator.
+
+        Returns:
+            The 15 residual codebook token ids.
+        """
+        cache = self._mtp_cache_len
+        k_all = np.zeros(self._mtp_kv_shape, np.float32)
+        v_all = np.zeros_like(k_all)
+        feeds = [hidden, self._codec_emb[cb0]]
+        codes = []
+        for t in range(_NUM_CODE_GROUPS):
+            embed = (feeds[t] if t < 2 else
+                     self._mtp_emb[t - 2][codes[-1]]).reshape(1, 1, _HIDDEN)
+            mask = np.where(np.arange(cache) <= t, 0.0,
+                            _NEG_INF).astype(np.float32).reshape(1, 1, 1, -1)
+            out = self._mtp(args_0=embed.astype(np.float32),
+                            args_1=np.array([t], np.int32), args_2=mask,
+                            args_3=k_all, args_4=v_all)
+            k_all, v_all = out['output_1'], out['output_2']
+            if t >= 1:
+                codes.append(_pick(out['output_0'][t - 1], do_sample, top_k,
+                                   temperature, rng))
+        return codes
+
+    def _decode_codes(self, codes: np.ndarray) -> np.ndarray:
+        """Decodes [T, 16] codec frames to PCM with chunking + left context."""
+        chunk, ctx = self._codec_chunk, 25
+        pieces = []
+        i = 0
+        while i < len(codes):
+            c = min(ctx, i)
+            # Window = left context + new frames must fit the fixed-T graph, so
+            # advance by at most (chunk - c) new frames per step.
+            j = min(i + chunk - c, len(codes))
+            window = codes[i - c:j]
+            buf = np.zeros((1, _NUM_CODE_GROUPS, chunk), np.int32)
+            buf[0, :, :len(window)] = window.T
+            out = self._codec(args_0=buf)
+            wav = next(iter(out.values()))[0, 0]
+            pieces.append(wav[c * _UPSAMPLE:len(window) * _UPSAMPLE])
+            i = j
+        return np.concatenate(pieces)
+
+
+class _SignatureRunner:
+    """Callable wrapper over one CompiledModel signature.
+
+    Runs a signature as a plain function call (NumPy arrays in by input name,
+    dict of NumPy arrays out by output name) on top of the CompiledModel
+    named-buffer API. The tensor buffers are created once and rewritten on
+    every invocation, which keeps the per-step decode loops allocation-free.
+    """
+
+    def __init__(self, model: CompiledModel,
+                 signature_key: str | None = None):
+        if signature_key is None:
+            signature_key = next(iter(model.get_signature_list()))
+        self._model = model
+        self._signature_key = signature_key
+        self._input_details = model.get_input_tensor_details(signature_key)
+        self._output_details = model.get_output_tensor_details(signature_key)
+        self._input_buffers = {
+            name: model.create_input_buffer_by_name(signature_key, name)
+            for name in self._input_details}
+        self._output_buffers = {
+            name: model.create_output_buffer_by_name(signature_key, name)
+            for name in self._output_details}
+
+    def get_input_details(self) -> dict:
+        """Returns input tensor details (shape, dtype) keyed by input name."""
+        return self._input_details
+
+    def __call__(self, **inputs: np.ndarray) -> dict[str, np.ndarray]:
+        for name, array in inputs.items():
+            self._input_buffers[name].write(np.ascontiguousarray(array))
+        self._model.run_by_name(self._signature_key, self._input_buffers,
+                                self._output_buffers)
+        outputs = {}
+        for name, detail in self._output_details.items():
+            shape = detail['shape']
+            outputs[name] = self._output_buffers[name].read(
+                int(np.prod(shape)), np.dtype(detail['dtype'])).reshape(shape)
+        return outputs
+
+
+def _cpu_options(num_threads: int) -> Options:
+    """Builds CPU compilation options with the given XNNPACK thread count.
+
+    Args:
+        num_threads: Number of XNNPACK threads.
+
+    Returns:
+        LiteRT compilation Options targeting the CPU.
+    """
+    return Options(cpu_options=CpuOptions(num_threads=num_threads))
+
+
+def _load_fp32(path: str) -> np.ndarray:
+    """Loads an .npy table, up-casting fp16 storage to fp32.
+
+    Args:
+        path: Path to the .npy file.
+
+    Returns:
+        The table as a float32 numpy array.
+    """
+    return np.load(path).astype(np.float32)
+
+
+def _pick(logits: np.ndarray, do_sample: bool, top_k: int,
+          temperature: float, rng) -> int:
+    """Greedy argmax or top-k/temperature sampling over logits.
+
+    Args:
+        logits: 1-D array of unnormalized token scores.
+        do_sample: If False, returns the argmax.
+        top_k: Keep only the top_k highest logits when sampling (0 = all).
+        temperature: Softmax temperature used when sampling.
+        rng: numpy random Generator used when sampling.
+
+    Returns:
+        The selected token id as a Python int.
+    """
+    if not do_sample:
+        return int(np.argmax(logits))
+    scaled = logits.astype(np.float64) / max(temperature, 1e-6)
+    if top_k and top_k < len(scaled):
+        kth = np.partition(scaled, -top_k)[-top_k]
+        scaled = np.where(scaled < kth, -np.inf, scaled)
+    scaled -= scaled.max()
+    probs = np.exp(scaled)
+    probs /= probs.sum()
+    return int(rng.choice(len(probs), p=probs))
diff --git a/packages/flutter_gemma_speech/tool/qwen3/synthesize.py b/packages/flutter_gemma_speech/tool/qwen3/synthesize.py
new file mode 100644
index 00000000..128cc1b0
--- /dev/null
+++ b/packages/flutter_gemma_speech/tool/qwen3/synthesize.py
@@ -0,0 +1,118 @@
+# Copyright 2026 The Google AI Edge Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+# Vendored frozen snapshot from google-ai-edge/litert-samples
+# (samples/litert/text_to_speech_lm/python/synthesize.py), pinned 2026-08-03,
+# for reference/reproducibility only — not maintained here.
+r"""CLI for Qwen3-TTS on LiteRT.
+
+Example:
+    python synthesize.py \
+        --text "Hello from LiteRT running fully on device." \
+        --output hello.wav
+
+The first run downloads ~1.4 GB (int4 talker + fp32 MTP/codec + tables) from
+https://huggingface.co/litert-community/Qwen3-TTS-12Hz-0.6B-Base.
+"""
+
+import argparse
+import time
+
+import numpy as np
+import soundfile
+
+import qwen3_tts_pipeline
+
+_HF_REPO = 'litert-community/Qwen3-TTS-12Hz-0.6B-Base'
+_DEFAULT_FILES = [
+    'talker_int4.tflite',
+    'mtp_fp32.tflite',
+    'codec_decoder_fp32.tflite',
+    'tokenizer.json',
+    'tables/*',
+    'voices/*',
+]
+
+
+def _parse_args() -> argparse.Namespace:
+    """Parses the command-line arguments.
+
+    Returns:
+        The parsed argparse namespace.
+    """
+    parser = argparse.ArgumentParser(description='Qwen3-TTS on LiteRT (CPU).')
+    parser.add_argument('--text', required=True, help='Text to speak.')
+    parser.add_argument('--output', default='output.wav',
+                        help='Output wav path.')
+    parser.add_argument('--model_dir', default=None,
+                        help='Local model dir; downloads from Hugging Face '
+                             'if omitted.')
+    parser.add_argument('--language', default='english',
+                        help='"auto" or one of: %s' %
+                             ', '.join(sorted(
+                                 qwen3_tts_pipeline.LANGUAGE_IDS)))
+    parser.add_argument('--speaker', default=None,
+                        help='Speaker x-vector .npy; defaults to the bundled '
+                             'demo voice.')
+    parser.add_argument('--talker', default='int4', choices=['int4', 'fp32'],
+                        help='Talker variant. fp32 is bit-exact vs the '
+                             'PyTorch reference under --greedy.')
+    parser.add_argument('--greedy', action='store_true',
+                        help='Deterministic greedy decoding instead of '
+                             'sampling.')
+    parser.add_argument('--seed', type=int, default=None,
+                        help='Sampling seed.')
+    parser.add_argument('--threads', type=int, default=8,
+                        help='XNNPACK threads for talker/codec.')
+    return parser.parse_args()
+
+
+def main() -> None:
+    """Synthesizes speech for --text and writes it to --output."""
+    args = _parse_args()
+
+    model_dir = args.model_dir
+    if model_dir is None:
+        import huggingface_hub  # Deferred: only needed for auto-download.
+        files = list(_DEFAULT_FILES)
+        if args.talker == 'fp32':
+            files[0] = 'talker_fp32.tflite'
+        model_dir = huggingface_hub.snapshot_download(
+            _HF_REPO, allow_patterns=files)
+
+    t0 = time.time()
+    pipeline = qwen3_tts_pipeline.Qwen3TtsPipeline(
+        model_dir, talker_file=f'talker_{args.talker}.tflite',
+        num_threads=args.threads)
+    print(f'Loaded in {time.time() - t0:.1f}s')
+
+    speaker_path = args.speaker or f'{model_dir}/voices/demo_speaker.npy'
+    speaker = np.load(speaker_path)
+
+    result = pipeline.synthesize(args.text, speaker,
+                                 language=args.language,
+                                 do_sample=not args.greedy, seed=args.seed)
+    soundfile.write(args.output, result.waveform, result.sample_rate)
+
+    duration = len(result.waveform) / result.sample_rate
+    print(f'Wrote {args.output}: {duration:.2f}s audio, '
+          f'{result.num_frames} frames, RTF {result.rtf:.2f} '
+          f'(prefill {result.prefill_seconds:.2f}s, '
+          f'talker {result.talker_seconds:.2f}s, '
+          f'mtp {result.mtp_seconds:.2f}s, '
+          f'codec {result.codec_seconds:.2f}s)')
+
+
+if __name__ == '__main__':
+    main()

From 81a8f5f18d75c4ec2a98b188031b347cf4f7ccb5 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 14:11:02 +0500
Subject: [PATCH 28/30] docs(qwen3): sweep 2 residual comment refs (wrapped
 citation + Tasks tag)

---
 .../lib/src/qwen3/qwen3_talker_layout.dart                    | 2 +-
 .../flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart    | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
index ac3c498c..9cf77ce7 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_talker_layout.dart
@@ -59,7 +59,7 @@
 // accessor that can target e.g. output 56 alone without already knowing
 // the count), and there is no dedicated get-input-count / get-output-count
 // / get-signature-count binding at all. If a future model revision changes
-// any of these, the run path (Tasks 2.2/2.3) fails loud — a tensor-buffer
+// any of these, the run path fails loud — a tensor-buffer
 // create/run call against a mismatched shape returns a non-OK LiteRT
 // status, which the `.check()` extension turns into a thrown
 // [StateError] — rather than silently misbehaving.
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index 4fd6f976..a45465e5 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -1147,8 +1147,8 @@ class Qwen3TtsCore {
     );
 
     // kv = _run_prefill(...); pos = prefill.shape[1] - 1; logits, hidden,
-    // kv = _run_decode(kv, prefill[0, -1], pos) (qwen3_tts_pipeline.py:
-    // 216-220).
+    // kv = _run_decode(kv, prefill[0, -1], pos)
+    // (qwen3_tts_pipeline.py Qwen3TtsPipeline.synthesize).
     final initialKv = runPrefill(prompt.prefill, prompt.promptLen);
     var pos = prompt.promptLen - 1;
     final firstEmbed = Float32List.sublistView(

From 8c03f7c6d78071dd1cdfb31edca4a0936766d19d Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 15:00:40 +0500
Subject: [PATCH 29/30] =?UTF-8?q?fix(speech):=20review=20fixes=20D=20?=
 =?UTF-8?q?=E2=80=94=20maxFrames=20fail-loud=20throw,=20tensor-buffer=20le?=
 =?UTF-8?q?ak?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Qwen3TtsCore.synthesize now throws a StateError when the AR loop hits
maxFrames without EOS instead of a gemmaLog-only warning, which is
compile-time stripped in release and silently truncated audio.

litert_graph.dart's _createTensorBuffer now validates the payload
length before any native allocation, so a mismatch no longer leaks
the aligned buffer + type struct that used to be allocated ahead of
the check.
---
 .../lib/src/litert/litert_graph.dart          | 45 +++++++++++-----
 .../lib/src/qwen3/qwen3_tts_core.dart         | 27 ++++++++--
 .../test/qwen3/qwen3_synthesize_test.dart     | 53 +++++++++++++++++++
 3 files changed, 109 insertions(+), 16 deletions(-)

diff --git a/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart b/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
index 63e9f2b4..fecefdd1 100644
--- a/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
+++ b/packages/flutter_gemma_speech/lib/src/litert/litert_graph.dart
@@ -148,8 +148,8 @@ List<Float32List> runLiteRtGraph(
           bindings,
           shape,
           kLiteRtElementTypeFloat32,
+          data.length,
           (alloc, count) {
-            _checkPayloadLength(data.length, count);
             alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data);
           },
         ),
@@ -157,8 +157,8 @@ List<Float32List> runLiteRtGraph(
           bindings,
           shape,
           kLiteRtElementTypeInt32,
+          data.length,
           (alloc, count) {
-            _checkPayloadLength(data.length, count);
             alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data);
           },
         ),
@@ -166,7 +166,13 @@ List<Float32List> runLiteRtGraph(
     }
     for (final shape in outputShapes) {
       outHandles.add(
-        _createTensorBuffer(bindings, shape, kLiteRtElementTypeFloat32, null),
+        _createTensorBuffer(
+          bindings,
+          shape,
+          kLiteRtElementTypeFloat32,
+          null,
+          null,
+        ),
       );
     }
 
@@ -251,10 +257,10 @@ TensorHandle createF32TensorBuffer(
     bindings,
     shape,
     kLiteRtElementTypeFloat32,
+    data?.length,
     data == null
         ? null
         : (alloc, count) {
-            _checkPayloadLength(data.length, count);
             alloc.aligned.cast<Float>().asTypedList(count).setAll(0, data);
           },
   );
@@ -275,22 +281,27 @@ TensorHandle createI32TensorBuffer(
     bindings,
     shape,
     kLiteRtElementTypeInt32,
+    data?.length,
     data == null
         ? null
         : (alloc, count) {
-            _checkPayloadLength(data.length, count);
             alloc.aligned.cast<Int32>().asTypedList(count).setAll(0, data);
           },
   );
 }
 
 /// Guards every [GraphInput]/[createF32TensorBuffer]/[createI32TensorBuffer]
-/// payload write: a `data` shorter than [count] (= product of the tensor's
-/// shape) would otherwise be silently zero-padded by `setAll` into a
+/// payload: a `data` shorter than [count] (= product of the tensor's shape)
+/// would otherwise be silently zero-padded by `setAll` into a
 /// wrong-but-not-obviously-wrong tensor, and a longer one would throw a
 /// confusing `RangeError` from `setAll` itself instead of naming the actual
-/// mismatch. THROWS (not `assert` — asserts are stripped in release builds
-/// and this must fail loud in production too).
+/// mismatch. Called from [_createTensorBuffer] itself — BEFORE any native
+/// allocation (`allocAligned`/the `type` view) — so a mismatch fails loud
+/// with zero native allocation instead of leaking the aligned buffer + type
+/// struct that a throw from inside the old write-callback used to leave
+/// behind (both were allocated before the `try`/`finally` that frees them).
+/// THROWS (not `assert` — asserts are stripped in release builds and this
+/// must fail loud in production too).
 void _checkPayloadLength(int dataLength, int count) {
   if (dataLength != count) {
     throw ArgumentError(
@@ -304,16 +315,26 @@ void _checkPayloadLength(int dataLength, int count) {
 /// per-input dispatch. [elementType] is one of `kLiteRtElementTypeFloat32`/
 /// `kLiteRtElementTypeInt32` (both 4-byte elements, so `bytes = count * 4`
 /// unconditionally — matches the original F32-only arithmetic byte-for-byte
-/// when [elementType] is float32). [writeData], if non-null, is called once
-/// with the fresh aligned allocation to copy the caller's payload in before
-/// the tensor buffer is created.
+/// when [elementType] is float32). [dataLength], when non-null (a payload is
+/// being written), is validated against `count` (= product of [shape]) via
+/// [_checkPayloadLength] BEFORE any native allocation — [writeData], if
+/// non-null, is called once with the fresh aligned allocation to copy the
+/// caller's payload in AFTER that check passes, so a length mismatch throws
+/// with zero native allocation instead of leaking the aligned buffer + the
+/// `type` view (both used to be allocated before the length was checked,
+/// which sat inside [writeData] itself, past the point either could still
+/// be freed on that throw).
 TensorHandle _createTensorBuffer(
   LiteRtBindings bindings,
   List<int> shape,
   int elementType,
+  int? dataLength,
   void Function(AlignedAlloc alloc, int count)? writeData,
 ) {
   final count = shape.fold<int>(1, (a, b) => a * b);
+  if (dataLength != null) {
+    _checkPayloadLength(dataLength, count);
+  }
   final bytes = count * 4;
   final type = LiteRtRankedTensorTypeView.calloc()
     ..elementType = elementType
diff --git a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
index a45465e5..27c3a220 100644
--- a/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
+++ b/packages/flutter_gemma_speech/lib/src/qwen3/qwen3_tts_core.dart
@@ -1051,6 +1051,11 @@ class Qwen3TtsCore {
   ///
   /// Returns mono float32 PCM in `[-1, 1]` at [sampleRate]. The frames
   /// generated by this call are cached in [lastFrames] for inspection.
+  ///
+  /// Throws a [StateError] if the AR loop hits [maxFrames] without reaching
+  /// end-of-speech — i.e. [text] is too long to synthesize in a single AR
+  /// pass. This is a fail-loud guard, not a truncation: no partial audio is
+  /// ever returned silently.
   Float32List synthesize(
     String text, {
     required Float32List speaker,
@@ -1083,6 +1088,9 @@ class Qwen3TtsCore {
   /// player expecting int16 PCM. Every float sample is clamped to `[-1, 1]`,
   /// scaled by `32767`, and rounded before being written little-endian:
   /// `(sample.clamp(-1, 1) * 32767).round()`.
+  ///
+  /// Throws a [StateError] under the same condition as [synthesize] — see
+  /// its doc — when [text] is too long for one AR pass.
   Uint8List synthesizePcm16(
     String text, {
     required Float32List speaker,
@@ -1241,10 +1249,21 @@ class Qwen3TtsCore {
     }
 
     if (!hitEos) {
-      gemmaLog(
-        '⚠️ Qwen3 TTS reached maxFrames=$maxFrames '
-        '(~${(maxFrames / 12.5).round()}s) before EOS — output is '
-        'truncated; text may be too long for a single AR pass.',
+      // Fail loud (per the project's no-masking-fallback rule): a
+      // `gemmaLog`-only warning here is compile-time stripped in release
+      // builds (`gemma_log.dart`'s `kDebugMode` gate), so a release app
+      // synthesizing text too long for one AR pass would otherwise get
+      // silently truncated audio with no signal at all. Throw instead of
+      // returning the partial `frames` — the caller (`synthesize`/
+      // `synthesizePcm16` -> the worker's per-request `try/catch` in
+      // `_runQwen3Worker`) turns this into a clear `completeError`, not
+      // confident-but-incomplete output.
+      throw StateError(
+        'Qwen3 TTS reached the maxFrames cap ($maxFrames ≈ '
+        '${(maxFrames / 12.5).round()} s of audio) without reaching '
+        'end-of-speech — the input is too long for a single AR pass. Split '
+        'it into shorter segments (Qwen3 v1 does not chunk text the way '
+        'Matcha does).',
       );
     }
 
diff --git a/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart b/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
index 34ca8cad..cf8b3150 100644
--- a/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
+++ b/packages/flutter_gemma_speech/test/qwen3/qwen3_synthesize_test.dart
@@ -234,4 +234,57 @@ void main() {
       core.dispose();
     }
   }, timeout: const Timeout(Duration(minutes: 30)));
+
+  test('Qwen3TtsCore.synthesize: hitting maxFrames without EOS throws '
+      '(fail-loud — no silent truncation)', () async {
+    if (!Directory(modelDir).existsSync()) {
+      markTestSkipped(
+        'Qwen3-TTS model snapshot not found at $modelDir — set '
+        'QWEN3_MODEL_DIR or fetch the model snapshot to run this test.',
+      );
+      return;
+    }
+
+    final artifactPaths = _scanArtifactPaths(modelDir);
+    if (!artifactPaths.containsKey('talker_fp32.tflite')) {
+      markTestSkipped(
+        'talker_fp32.tflite not found under $modelDir — the golden '
+        'fixtures were generated against the fp32 talker (int4 is not '
+        'bit-exact vs the PyTorch reference) and this test needs it '
+        'present to run.',
+      );
+      return;
+    }
+
+    // Golden fixtures — committed, always present (no skip-guard needed).
+    final meta =
+        jsonDecode(File('test/golden/qwen3/meta.json').readAsStringSync())
+            as Map<String, dynamic>;
+    final text = meta['text'] as String;
+    final speaker = readNpyF32('test/golden/qwen3/voices/demo_speaker.npy');
+
+    final core = await Qwen3TtsCore.load(
+      artifactPaths: artifactPaths,
+      backend: PreferredBackend.cpu,
+      talkerFileName: 'talker_fp32.tflite',
+    );
+    try {
+      // The golden text reaches EOS at frame 26 (meta.json's `num_frames`)
+      // in the greedy run above — a maxFrames well below that forces the
+      // AR loop to hit the cap before EOS, so this proves the guard fires
+      // without paying for a long synthesis run just to exercise it.
+      expect(
+        () => core.synthesize(
+          text,
+          speaker: speaker,
+          language: meta['language'] as String,
+          doSample: false, // Deterministic: same greedy path as the gate above.
+          maxFrames: 5,
+        ),
+        throwsA(isA<StateError>()),
+      );
+    } finally {
+      core.dispose();
+    }
+  }, timeout: const Timeout(Duration(minutes: 30)));
 }

From 7dd17d234f6254e7969e5f99fbaefa927f2e46a3 Mon Sep 17 00:00:00 2001
From: Sasha Denisov <denisov.shureg@gmail.com>
Date: Tue, 4 Aug 2026 15:23:22 +0500
Subject: [PATCH 30/30] docs: bump site to flutter_gemma 1.5.2 / speech 0.4.1 +
 document Qwen3-TTS

- CLAUDE.md Current Version: flutter_gemma 1.5.2, flutter_gemma_speech 0.4.1
- website pubspec snippets bumped (speech.md, genkit.md, migration.md)
- speech.md: document Qwen3-TTS (2nd selectable TTS family, language: param)
- speech.md: mark Whisper/Parakeet STT shipped (were stale 'follow-on' since 0.4.0)
---
 CLAUDE.md                         |  2 +-
 website/content/docs/genkit.md    |  2 +-
 website/content/docs/migration.md |  2 +-
 website/content/docs/speech.md    | 31 ++++++++++++++++++++++++++-----
 4 files changed, 29 insertions(+), 8 deletions(-)

diff --git a/CLAUDE.md b/CLAUDE.md
index a9a7f087..8b2ad85c 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -138,7 +138,7 @@ Core has NO pigeon (dropped at the 1.0 cut; its value types are hand-written in
 - **MediaPipe Web**: v0.10.27, Android/iOS: v0.10.33
 - **LiteRT-LM**: native libs from `native-v0.14.0` GitHub Release. Android tarball bundles the Qualcomm QNN dispatch stack and Windows tarball bundles Intel NPU dispatch (`LiteRtDispatch.dll` + OpenVino runtime + TBB) for `PreferredBackend.npu` (Qualcomm Snapdragon / Intel LunarLake/PantherLake). v0.14.0: native per-session sampler (opaque session-config) + #214 GPU output-garbage fix; Dawn split static→dynamic (Linux/Windows bundle `libwebgpu_dawn`). Windows discrete GPU (WebGPU/Dawn) regressed upstream — use CPU/NPU on Windows (LiteRT-LM #2957).
 - **large_file_handler**: `^0.5.0` (core dep; 0.5.0 declares all 6 platforms — needed for pana platform support + the dart2wasm-clean web graph)
-- **Current Version**: core `flutter_gemma` `1.5.1`, `flutter_gemma_rag_sqlite` `1.1.0`, `flutter_gemma_rag_qdrant` `1.1.0`; `flutter_gemma_litertlm` `1.3.1`, `flutter_gemma_mediapipe` `1.0.4`, `flutter_gemma_embeddings` `1.0.4`, `flutter_gemma_speech` `0.4.0`; `flutter_gemma_agent` `0.1.0`, `flutter_gemma_builtin_ai` `0.1.0`
+- **Current Version**: core `flutter_gemma` `1.5.2`, `flutter_gemma_rag_sqlite` `1.1.0`, `flutter_gemma_rag_qdrant` `1.1.0`; `flutter_gemma_litertlm` `1.3.1`, `flutter_gemma_mediapipe` `1.0.4`, `flutter_gemma_embeddings` `1.0.4`, `flutter_gemma_speech` `0.4.1`; `flutter_gemma_agent` `0.1.0`, `flutter_gemma_builtin_ai` `0.1.0`
 - **0.15.2**: embedding unified on LiteRT C API via Dart FFI on all native platforms (Android + iOS + Desktop). Drops `localagents-rag` JVM dep on Android and the separate TFLite C 0.12.7 tarball on Desktop; `TensorFlowLiteC` pod no longer needed on iOS. Single source of truth for `TaskType.prefix` in Dart, fixes cross-platform embedding drift (#264).
 
 ## Platform-Specific Setup
diff --git a/website/content/docs/genkit.md b/website/content/docs/genkit.md
index f9e1c118..e9aa4222 100644
--- a/website/content/docs/genkit.md
+++ b/website/content/docs/genkit.md
@@ -21,7 +21,7 @@ with the on-device model exactly as it would with any cloud provider.
 ```
 dependencies:
   genkit_flutter_gemma: ^0.4.3
-  flutter_gemma: ^1.5.1
+  flutter_gemma: ^1.5.2
   # Add the inference engine(s) you need:
   flutter_gemma_litertlm: ^1.3.1   # .litertlm models (mobile + desktop)
   flutter_gemma_mediapipe: ^1.0.4  # .task / .bin models (mobile + web)
diff --git a/website/content/docs/migration.md b/website/content/docs/migration.md
index 681c27c4..df748121 100644
--- a/website/content/docs/migration.md
+++ b/website/content/docs/migration.md
@@ -29,7 +29,7 @@ dependencies:
 
 ```
 dependencies:
-  flutter_gemma: ^1.5.1                 # core — always required
+  flutter_gemma: ^1.5.2                 # core — always required
   flutter_gemma_litertlm: ^1.3.1        # add if you run .litertlm models
   flutter_gemma_mediapipe: ^1.0.4       # add if you run .task / .bin models
   flutter_gemma_embeddings: ^1.0.4      # add if you compute embeddings
diff --git a/website/content/docs/speech.md b/website/content/docs/speech.md
index 3cb07310..74389af3 100644
--- a/website/content/docs/speech.md
+++ b/website/content/docs/speech.md
@@ -10,8 +10,8 @@ speech** — speech-to-text and text-to-speech — to flutter_gemma. It runs
 no streaming a mic to a server.
 You choose the model with `SttModelType` / `TtsModelType` and a profile-driven,
 model-agnostic pipeline resolves the matching runtime, so it isn't tied to one
-model. **moonshine** (a raw-PCM seq2seq STT model) and **Matcha** (TTS) work
-end-to-end today; Whisper / Parakeet STT profiles and kokoro / supertonic TTS
+model. **moonshine**, **Whisper**, and **Parakeet** STT and **Matcha** +
+**Qwen3-TTS** (multilingual) TTS work end-to-end today; kokoro / supertonic TTS
 voices are follow-ons.
 
 <Info>
@@ -30,8 +30,8 @@ inference.
 
 ```
 dependencies:
-  flutter_gemma: ^1.5.1
-  flutter_gemma_speech: ^0.4.0
+  flutter_gemma: ^1.5.2
+  flutter_gemma_speech: ^0.4.1
 ```
 
 ## Register the backend
@@ -115,6 +115,26 @@ The Matcha repo is public, so no HuggingFace token is required. Synthesis is
 deterministic on a given arch — byte-identical on arm64, with imperceptible
 low-float-bit divergence on x86_64.
 
+### Qwen3-TTS (multilingual)
+
+A second TTS family is selectable via `TtsModelType.qwen3` — an autoregressive
+codec-LM (`litert-community/Qwen3-TTS-12Hz-0.6B-Base`, ~1.9 GB) that speaks 11
+languages, chosen at synth time with the new `language:` param. Same
+install/synthesize API as Matcha, but heavier: CPU-only, RTF≈3 (~3 s of compute
+per 1 s of audio), and needs a 6 GB-RAM-class device.
+
+```dart
+await FlutterGemma.installTts()
+    .fromNetwork('https://huggingface.co/litert-community/Qwen3-TTS-12Hz-0.6B-Base/resolve/main/')
+    .ofType(TtsModelType.qwen3)
+    .install();
+
+// language is one of qwen3SupportedLanguages (11) or 'auto'; ignored by Matcha.
+final synth = await FlutterGemma.getActiveTts(language: 'english');
+final pcm = await synth.synthesize('Bonjour le monde.'); // Uint8List, 16-bit PCM
+await synth.close();
+```
+
 ## Voice loop
 
 `VoiceSession` chains STT → LLM → TTS into one push-to-talk turn — transcribe,
@@ -168,8 +188,9 @@ requires **minSdk 30** — see
 | Model | Task | Input | Status |
 |---|---|---|---|
 | **moonshine-tiny** | STT | raw PCM (seq2seq) | ✅ end-to-end |
+| **Whisper / Parakeet** | STT | log-mel | ✅ end-to-end |
 | **Matcha** | TTS | text (Glow-TTS + CFM) | ✅ end-to-end |
-| Whisper / Parakeet | STT | log-mel | 🚧 profile follow-on |
+| **Qwen3-TTS** | TTS | text (AR codec-LM, 11 langs) | ✅ end-to-end |
 | kokoro / supertonic | TTS | text | 🚧 voice follow-on |
 
 Both pipelines are profile-driven (`SttModelProfile` / `TtsModelProfile`), so