Support Qwen3-VL

README.md

@@ -162,6 +162,7 @@ LMDeploy is a toolkit for compressing, deploying, and serving LLM, developed by
   <li>Qwen-VL (7B)</li>
   <li>Qwen2-VL (2B, 7B, 72B)</li>
   <li>Qwen2.5-VL (3B, 7B, 72B)</li>
+  <li>Qwen3-VL (2B - 235B)</li>
   <li>DeepSeek-VL (7B)</li>
   <li>DeepSeek-VL2 (3B, 16B, 27B)</li>
   <li>InternVL-Chat (v1.1-v1.5)</li>

README_ja.md

@@ -148,6 +148,7 @@ LMDeploy TurboMindエンジンは卓越した推論能力を持ち、さまざ
   <li>Qwen-VL (7B)</li>
   <li>Qwen2-VL (2B, 7B, 72B)</li>
   <li>Qwen2.5-VL (3B, 7B, 72B)</li>
+  <li>Qwen3-VL (2B - 235B)</li>
   <li>DeepSeek-VL (7B)</li>
   <li>DeepSeek-VL2 (3B, 16B, 27B)</li>
   <li>InternVL-Chat (v1.1-v1.5)</li>

README_zh-CN.md

@@ -163,6 +163,7 @@ LMDeploy TurboMind 引擎拥有卓越的推理能力，在各种规模的模型
   <li>Qwen-VL (7B)</li>
   <li>Qwen2-VL (2B, 7B, 72B)</li>
   <li>Qwen2.5-VL (3B, 7B, 72B)</li>
+  <li>Qwen3-VL (2B - 235B)</li>
   <li>DeepSeek-VL (7B)</li>
   <li>DeepSeek-VL2 (3B, 16B, 27B)</li>
   <li>InternVL-Chat (v1.1-v1.5)</li>

docs/en/supported_models/supported_models.md

@@ -87,6 +87,7 @@ The following tables detail the models supported by LMDeploy's TurboMind engine
 |             Qwen3              |   0.6B - 235B   | LLM  |    Yes    |   Yes   |  Yes\*  |  -   | Yes\* |
 |            QWen2-VL            |     2B, 7B      | MLLM |    Yes    |   Yes   |   No    |  No  |  Yes  |
 |           QWen2.5-VL           |    3B - 72B     | MLLM |    Yes    |   No    |   No    |  No  |  No   |
+|            QWen3-VL            |    2B - 235B    | MLLM |    Yes    |   No    |   No    |  No  |  No   |
 |          DeepSeek-MoE          |       16B       | LLM  |    Yes    |   No    |   No    |  No  |  No   |
 |          DeepSeek-V2           |    16B, 236B    | LLM  |    Yes    |   No    |   No    |  No  |  No   |
 |         DeepSeek-V2.5          |      236B       | LLM  |    Yes    |   No    |   No    |  No  |  No   |

docs/zh_cn/supported_models/supported_models.md

@@ -87,6 +87,7 @@
 |             Qwen3              |   0.6B - 235B   | LLM  |    Yes    |   Yes   |  Yes\*  |  -   |  Yes  |
 |            QWen2-VL            |     2B, 7B      | MLLM |    Yes    |   Yes   |   No    |  No  |  Yes  |
 |           QWen2.5-VL           |    3B - 72B     | MLLM |    Yes    |   No    |   No    |  No  |  No   |
+|            QWen3-VL            |    2B - 235B    | MLLM |    Yes    |   No    |   No    |  No  |  No   |
 |          DeepSeek-MoE          |       16B       | LLM  |    Yes    |   No    |   No    |  No  |  No   |
 |          DeepSeek-V2           |    16B, 236B    | LLM  |    Yes    |   No    |   No    |  No  |  No   |
 |         DeepSeek-V2.5          |      236B       | LLM  |    Yes    |   No    |   No    |  No  |  No   |

lmdeploy/archs.py

@@ -109,9 +109,9 @@ def check_vl_llm(config: dict) -> bool:
         'LlavaLlamaForCausalLM', 'LlavaMistralForCausalLM', 'CogVLMForCausalLM', 'InternLMXComposer2ForCausalLM',
         'InternVLChatModel', 'MiniCPMV', 'LlavaForConditionalGeneration', 'LlavaNextForConditionalGeneration',
         'Phi3VForCausalLM', 'Qwen2VLForConditionalGeneration', 'Qwen2_5_VLForConditionalGeneration',
-        'MllamaForConditionalGeneration', 'MolmoForCausalLM', 'Gemma3ForConditionalGeneration',
-        'Llama4ForConditionalGeneration', 'InternVLForConditionalGeneration', 'InternS1ForConditionalGeneration',
-        'Glm4vForConditionalGeneration'
+        'Qwen3VLForConditionalGeneration', 'Qwen3VLMoeForConditionalGeneration', 'MllamaForConditionalGeneration',
+        'MolmoForCausalLM', 'Gemma3ForConditionalGeneration', 'Llama4ForConditionalGeneration',
+        'InternVLForConditionalGeneration', 'InternS1ForConditionalGeneration', 'Glm4vForConditionalGeneration'
     ])
     if arch == 'QWenLMHeadModel' and 'visual' in config:
         return True

lmdeploy/pytorch/config.py

@@ -28,9 +28,9 @@ def _update_torch_dtype(config: 'ModelConfig', dtype: str):
         config.dtype = torch.float16
         return config
 
-    torch_dtype = getattr(config.hf_config, 'dtype', None)
+    torch_dtype = getattr(config.llm_config, 'dtype', None)
     if torch_dtype is None:
-        torch_dtype = getattr(config.hf_config, 'torch_dtype', None)
+        torch_dtype = getattr(config.llm_config, 'torch_dtype', None)
 
     # deal with case when torch_dtype is not string but torch.dtype
     if isinstance(torch_dtype, torch.dtype):

lmdeploy/pytorch/configurations/default.py

@@ -14,8 +14,16 @@ def condition(cls, hf_config):
     @classmethod
     def build(cls, hf_config, model_path: str = None, **kwargs):
         """build."""
+
+        # for multi-modal models, get the language model config to build model config
+        if hasattr(hf_config, 'text_config'):
+            hf_config = hf_config.text_config
+        elif hasattr(hf_config, 'llm_config'):
+            hf_config = hf_config.llm_config
+
         head_dim = getattr(hf_config, 'head_dim', None)
         head_dim = head_dim or hf_config.hidden_size // hf_config.num_attention_heads
+
         # head_dim should not be None
         hf_config.head_dim = head_dim
         num_attention_heads = hf_config.num_attention_heads

lmdeploy/pytorch/models/module_map.py

@@ -147,6 +147,18 @@
     f'{LMDEPLOY_PYTORCH_MODEL_PATH}.qwen2_5_vl.Qwen2_5_VLForConditionalGeneration',
 })
 
+# qwen3_vl
+MODULE_MAP.update({
+    'Qwen3VLForConditionalGeneration':
+    f'{LMDEPLOY_PYTORCH_MODEL_PATH}.qwen3_vl.Qwen3VLForConditionalGeneration',
+})
+
+# qwen3_vl_moe
+MODULE_MAP.update({
+    'Qwen3VLMoeForConditionalGeneration':
+    f'{LMDEPLOY_PYTORCH_MODEL_PATH}.qwen3_vl_moe.Qwen3VLMoeForConditionalGeneration',
+})
+
 # starcoder2
 MODULE_MAP.update({
     'Starcoder2ForCausalLM': f'{LMDEPLOY_PYTORCH_MODEL_PATH}.starcoder2.Starcoder2ForCausalLM',

lmdeploy/pytorch/models/qwen3.py

@@ -47,7 +47,7 @@ def __init__(self, config: PretrainedConfig, dtype: torch.dtype = None, device:
             head_dim,
             num_kv_heads=num_key_value_heads,
             v_head_size=head_dim,
-            sliding_window=config.sliding_window,
+            sliding_window=getattr(config, 'sliding_window', None),
         )
 
         # o_proj

lmdeploy/pytorch/models/qwen3_moe.py

@@ -52,7 +52,7 @@ def __init__(self, config: PretrainedConfig, dtype: torch.dtype = None, device:
             head_dim,
             num_kv_heads=num_key_value_heads,
             v_head_size=head_dim,
-            sliding_window=config.sliding_window,
+            sliding_window=getattr(config, 'sliding_window', None),
         )
 
         # o_proj