[Model] Default Qwen3-TTS to experimental Model Runner V2 (#7930)

Signed-off-by: Sy03 <1370724210@qq.com>

docs/configuration/stage_configs.md

@@ -293,19 +293,25 @@ vllm serve Qwen/Qwen2.5-Omni-7B --omni --port 8091 --deploy-config /path/to/depl
 
 ## Qwen3-TTS with Model Runner V2
 
-Qwen3-TTS can opt into the native CUDA Model Runner V2 pipeline on vLLM
-0.29.0. Select one of these deployment profiles:
+Qwen3-TTS runs the native CUDA Model Runner V2 pipeline by default on vLLM
+0.29.0. MRV2 is an experimental feature for this model: the bundled default
+profile selects it on CUDA only, and its scheduler and delivery paths are
+still being qualified. Set `model_runner: v1` in a copy of the deploy config
+to opt out; the `platforms:` sections of `qwen3_tts.yaml` keep V1 on NPU, XPU,
+ROCm and MUSA. Select one of these deployment profiles:
 
 | Profile | Runner | Code2Wav graph batches | Intended use |
 | --- | --- | --- | --- |
-| `qwen3_tts.yaml` | V1 | Existing defaults | Existing deployment / regression control |
-| `qwen3_tts_mrv2.yaml` | V2 | B1 | Native runner validation |
+| `qwen3_tts.yaml` | V2 (default) | Existing defaults | Shipped default; experimental |
+| `qwen3_tts_mrv2.yaml` | V2 | B1 | Explicit MRV2 profile (same runner selection as the default) |
 | `qwen3_tts_high_concurrency_mrv2.yaml` | V2 | B1, B2 | Opt-in throughput tuning |
 | `qwen3_tts_high_concurrency_mrv2_b4.yaml` | V2 | B1, B2, B3, B4 | Experimental throughput / buffered playback |
+| `qwen3_tts_high_concurrency.yaml` | V1 | Existing defaults | V1 high-concurrency control |
 
 ```bash
+# MRV2 is the default; pass a copy with `model_runner: v1` to force V1.
 vllm serve Qwen/Qwen3-TTS-12Hz-1.7B-Base --omni \
-  --deploy-config vllm_omni/deploy/qwen3_tts_mrv2.yaml
+  --deploy-config /path/to/qwen3_tts_v1.yaml
 ```
 
 The V2 profiles bound Talker prefill to 512 tokens per step and select the

recipes/Qwen/Qwen3-TTS.md

@@ -71,8 +71,10 @@ Alternatively, use the convenience script:
 ```
 
 The bundled deploy config (`vllm_omni/deploy/qwen3_tts.yaml`) enables async
-chunking for low first-audio latency. For advanced deployment tuning, pass a
-custom deploy config:
+chunking for low first-audio latency, and selects the experimental Model
+Runner V2 on CUDA. Copy it and set `model_runner: v1` to run V1; NPU, XPU,
+ROCm and MUSA keep V1 through the `platforms:` sections. For advanced
+deployment tuning, pass a custom deploy config:
 
 ```bash
 vllm serve Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice \

tests/config/test_omni_config.py

@@ -816,19 +816,25 @@ def test_mrv2_fails_fast_on_platforms_without_native_workers(platform: str):
         _apply_platform_overrides(DeployConfig(model_runner="v2"), platform=platform)
 
 
-@pytest.mark.parametrize(
-    ("default_name", "mrv2_name"),
-    [
-        ("qwen3_tts.yaml", "qwen3_tts_mrv2.yaml"),
-        (
-            "qwen3_tts_high_concurrency.yaml",
-            "qwen3_tts_high_concurrency_mrv2.yaml",
-        ),
-    ],
-)
-def test_qwen3_mrv2_profiles_are_explicit_opt_in(default_name: str, mrv2_name: str):
-    assert load_deploy_config(_DEPLOY_DIR / default_name).model_runner == "v1"
-    assert load_deploy_config(_DEPLOY_DIR / mrv2_name).model_runner == "v2"
+def test_qwen3_tts_high_concurrency_mrv2_profile_is_explicit_opt_in():
+    assert load_deploy_config(_DEPLOY_DIR / "qwen3_tts_high_concurrency.yaml").model_runner == "v1"
+    assert load_deploy_config(_DEPLOY_DIR / "qwen3_tts_high_concurrency_mrv2.yaml").model_runner == "v2"
+
+
+def test_qwen3_tts_default_profile_is_experimental_mrv2_with_v1_platform_fallback():
+    deploy_path = _DEPLOY_DIR / "qwen3_tts.yaml"
+    assert load_deploy_config(deploy_path).model_runner == "v2"
+
+    pipeline = _resolve_pipeline_or_skip("qwen3_tts")
+    stages = merge_pipeline_deploy(pipeline, load_deploy_config(deploy_path))
+    assert all(stage.yaml_engine_args["use_v2_model_runner"] is True for stage in stages)
+
+    assert _apply_platform_overrides(load_deploy_config(deploy_path), platform="cuda").model_runner == "v2"
+    for platform in ("npu", "xpu", "rocm", "musa"):
+        assert _apply_platform_overrides(load_deploy_config(deploy_path), platform=platform).model_runner == "v1"
+
+    # The explicit MRV2 profile resolves to the same runner selection.
+    assert load_deploy_config(_DEPLOY_DIR / "qwen3_tts_mrv2.yaml").model_runner == "v2"
 
 
 def test_qwen3_tts_mrv2_retunes_do_not_change_default_mrv1_profile():

vllm_omni/deploy/qwen3_tts.yaml

@@ -1,16 +1,23 @@
 # Qwen3-TTS deploy: talker → code2wav via shared-memory chunk streaming.
 # Verified on 1x H100.
 #
+# Runner selection:
+#   Model Runner V2 (MRV2) is EXPERIMENTAL and is the default runner on CUDA
+#   for this model. Set `model_runner: v1` to opt out. The `platforms:`
+#   sections at the end of this file keep V1 on NPU, XPU, ROCm and MUSA.
+#   See docs/configuration/stage_configs.md ("Qwen3-TTS with Model Runner V2").
+#
 # Fields omitted from a stage fall back to StageDeployConfig defaults (see
 # vllm_omni/config/stage_config.py). Notable choices for this model:
 #   * Stage 0 (talker) sets max_num_batched_tokens=512 for async-chunk
 #     latency tuning (not correctness) — small per-step batches keep
-#     first-chunk latency low.
+#     first-chunk latency low, and the MRV2 profiles rely on that bound.
 #   * Stage 1 (code2wav) sets max_num_batched_tokens=65536 for correctness:
 #     codec prefill length (Q * num_frames) exceeds the 32k default.
 #   * Stage 0 does not set enforce_eager — talker runs cudagraph by default.
 #     Stage 1 defaults to false so Code2Wav can use its inner cudagraph;
 #     set true to disable that path in eager mode.
+model_runner: v2
 async_chunk: true
 
 connectors:
@@ -71,7 +78,9 @@ stages:
     # See docs/design/feature/prefix_caching.md for the stage matrix.
     enable_prefix_caching: false
     async_scheduling: true
-    max_num_batched_tokens: 32768
+    # Bound per-step prefill work (validated MRV2 basic profile). Small
+    # per-step batches keep first-chunk latency low.
+    max_num_batched_tokens: 512
     max_model_len: 4096
     devices: "0"
     output_connectors:
@@ -124,6 +133,8 @@ stages:
 
 platforms:
   rocm:
+    # MRV2 is not qualified on ROCm; keep the legacy V1 runner.
+    model_runner: v1
     stages:
       - stage_id: 1
         # MIOpen Conv1d cannot be invoked while vLLM captures the outer
@@ -131,6 +142,7 @@ platforms:
         # Stage 1 eager on ROCm so decoder convolutions execute normally.
         enforce_eager: true
   npu:
+    model_runner: v1
     stages:
       - stage_id: 0
         enforce_eager: false
@@ -139,3 +151,7 @@ platforms:
       - stage_id: 1
         compilation_config:
           cudagraph_mode: PIECEWISE
+  xpu:
+    model_runner: v1
+  musa:
+    model_runner: v1

vllm_omni/deploy/qwen3_tts_mrv2.yaml

@@ -1,4 +1,6 @@
-# Opt-in CUDA Model Runner V2 profile. The base profile retains V1.
+# Explicit CUDA Model Runner V2 profile. `qwen3_tts.yaml` now selects V2 by
+# default (experimental); this file is kept for scripts that name the MRV2
+# profile explicitly and for the platform fallbacks below.
 base_config: qwen3_tts.yaml
 model_runner: v2