diff --git a/scripts/performance/argument_parser.py b/scripts/performance/argument_parser.py
index aaf399cce9..ea5b8bbb3e 100644
--- a/scripts/performance/argument_parser.py
+++ b/scripts/performance/argument_parser.py
@@ -772,5 +772,17 @@ def parse_cli_args():
     testing_args.add_argument(
         "--memory_threshold", type=float, default=0.05, help="Memory validation threshold (default: 0.05 = 5%%)"
     )
+    testing_args.add_argument(
+        "--eval_time_start_step",
+        type=int,
+        default=None,
+        help="Start step (0-indexed, inclusive) for timing average window. Overrides skip_first_percent_time when set.",
+    )
+    testing_args.add_argument(
+        "--eval_time_end_step",
+        type=int,
+        default=None,
+        help="End step (0-indexed, exclusive) for timing average window. If None, averages to end.",
+    )
 
     return parser
diff --git a/scripts/performance/setup_experiment.py b/scripts/performance/setup_experiment.py
index 6afd3bcd50..b9fd5f5832 100755
--- a/scripts/performance/setup_experiment.py
+++ b/scripts/performance/setup_experiment.py
@@ -132,6 +132,8 @@ def build_performance_config(args) -> Optional[Dict[str, Any]]:
     performance_params = {
         "timing_threshold": args.timing_threshold,
         "skip_first_percent_time": args.skip_first_percent_time,
+        "eval_time_start_step": args.eval_time_start_step,
+        "eval_time_end_step": args.eval_time_end_step,
     }
 
     for key, value in performance_params.items():
@@ -639,6 +641,8 @@ def main(
         performance_params={
             "timing_threshold": args.timing_threshold,
             "skip_first_percent_time": args.skip_first_percent_time,
+            "eval_time_start_step": args.eval_time_start_step,
+            "eval_time_end_step": args.eval_time_end_step,
         },
         memory_params={
             "memory_threshold": args.memory_threshold,
diff --git a/scripts/performance/utils/evaluate.py b/scripts/performance/utils/evaluate.py
index 89f83c4453..c86d35d959 100644
--- a/scripts/performance/utils/evaluate.py
+++ b/scripts/performance/utils/evaluate.py
@@ -325,9 +325,12 @@ def validate_performance(
     config = default_config
 
     # Discard first N% of iterations for stable comparison
-    skip = max(1, int(len(steps) * config["skip_first_percent_time"]))
-    current_stable = current_gpu_util_values[skip:]
-    golden_stable = golden_gpu_util_values[skip:]
+    start = config.get("eval_time_start_step")
+    if start is None:
+        start = max(1, int(len(steps) * config["skip_first_percent_time"]))
+    end = config.get("eval_time_end_step")
+    current_stable = current_gpu_util_values[start:end]
+    golden_stable = golden_gpu_util_values[start:end]
 
     current_avg = float(np.nanmean(current_stable))
     golden_avg = float(np.nanmean(golden_stable))
@@ -339,7 +342,8 @@ def validate_performance(
     is_improvement = signed_diff > config["timing_threshold"]
 
     logger.info(
-        f"GPU utilization comparison (excluding first {config['skip_first_percent_time'] * 100:.1f}% of iterations):"
+        f"GPU utilization comparison (steps [{start}:{end if end is not None else len(steps)}] "
+        f"out of {len(steps)} total):"
     )
     logger.info(f"  Current average GPU util: {current_avg:.4f}%")
     logger.info(f"  Golden average GPU util: {golden_avg:.4f}%")
@@ -677,9 +681,12 @@ def calc_convergence_and_performance(
         wandb_run=wandb_run,
     )
     # Add iter-time averages for debugging (not used for pass/fail)
-    skip = max(1, int(len(steps) * performance_config.get("skip_first_percent_time", 0.1)))
-    performance_result["metrics"]["current_avg_iter_time_ms"] = float(np.nanmean(current_iter_time_values[skip:]))
-    performance_result["metrics"]["golden_avg_iter_time_ms"] = float(np.nanmean(golden_iter_time_values[skip:]))
+    start = performance_config.get("eval_time_start_step")
+    if start is None:
+        start = max(1, int(len(steps) * performance_config.get("skip_first_percent_time", 0.1)))
+    end = performance_config.get("eval_time_end_step")
+    performance_result["metrics"]["current_avg_iter_time_ms"] = float(np.nanmean(current_iter_time_values[start:end]))
+    performance_result["metrics"]["golden_avg_iter_time_ms"] = float(np.nanmean(golden_iter_time_values[start:end]))
     if not performance_result["passed"]:
         direction = performance_result["metrics"]["direction"]
         signed_diff = performance_result["metrics"]["signed_diff"]