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Serving Qwen3-Omni with vLLM on a Blackwell GPU: setup notes and two gotchas #182
sungbin1015
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Notes from serving
Qwen3-Omni-30B-A3B-Instructwith vLLM on an AWSg7e.4xlarge(one RTX PRO 6000 Blackwell, 96 GB). Two things cost us time, so I am writing them down.Environment
uvvenv)1. Blackwell needs a torch wheel with
sm_120Install torch first and check the arch list before anything else:
uv pip install torch==2.11.0 torchaudio==2.11.0 torchvision==0.26.0 \ --index-url https://download.pytorch.org/whl/cu130 python -c "import torch; print(torch.cuda.get_arch_list())" # ['sm_75', 'sm_80', 'sm_86', 'sm_90', 'sm_100', 'sm_120']Then pin it while installing vLLM, otherwise the vLLM install can replace torch:
2. Audio input returns 400 until the audio decoders are installed
With a plain
uv pip install vllm, requests that include audio fail with:Video-only requests work, which made this confusing. The audio decoders are not installed by default:
Restart the server afterwards. To have the audio track of an mp4 processed together with the video, the request also needs
mm_processor_kwargs: {"use_audio_in_video": true}.Serve command
vllm serve /mnt/nvme/models/Qwen3-Omni-30B-A3B-Instruct \ --served-model-name qwen \ --port 8000 --host 0.0.0.0 \ --dtype bfloat16 \ --max-model-len 16384 \ --max-num-seqs 8 \ --gpu-memory-utilization 0.90 \ --mm-encoder-attn-backend TORCH_SDPA \ --moe-backend triton \ --allowed-local-media-path /mnt/nvme/vod \ --limit-mm-per-prompt '{"image":1,"video":1,"audio":1}' \ --tensor-parallel-size 1 \ --trust-remote-codeA known issue with
use_audio_in_videoOn vLLM 0.21.0 we hit HTTP 400 (
StopIterationin the processor) when two requests had different video frames but a byte-identical audio track, for example BGM-only clips from the same episode. It comes from the multimodal processor cache;--mm-processor-cache-gb 0avoids it. Reproduction: vllm-project/vllm#44538Full write-up (Korean): https://doc.scenemaker.solbox.com/docs/install/1
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