vllm-omni/docs/user_guide/examples/offline_inference/qwen3_omni.md

Qwen3-Omni

Source https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/qwen3_omni.

Run examples (Qwen3-Omni)

Multiple Prompts

Download dataset from seed_tts. For processing dataset please refer to Qwen2.5-Omni README.md Get into the example folder

cd examples/offline_inference/qwen3_omni

Then run the command below.

bash run_multiple_prompts.sh

Single Prompt

Get into the example folder

cd examples/offline_inference/qwen3_omni

Then run the command below.

bash run_single_prompt.sh

If you have not enough memory, you can set thinker with tensor parallel. Just run the command below.

bash run_single_prompt_tp.sh

Modality control

If you want to control output modalities, e.g. only output text, you can run the command below:

python end2end.py --output-wav output_audio \
                  --query-type use_audio \
                  --modalities text

Using Local Media Files

The end2end.py script supports local media files (audio, video, image) via command-line arguments:

# Use local video file
python end2end.py --query-type use_video --video-path /path/to/video.mp4

# Use local image file
python end2end.py --query-type use_image --image-path /path/to/image.jpg

# Use local audio file
python end2end.py --query-type use_audio --audio-path /path/to/audio.wav

If media file paths are not provided, the script will use default assets. Supported query types:

• use_video: Video input
• use_image: Image input
• use_audio: Audio input
• text: Text-only query

Example materials

??? abstract "end2end.py" py --8<-- "examples/offline_inference/qwen3_omni/end2end.py" ??? abstract "run_multiple_prompts.sh" sh --8<-- "examples/offline_inference/qwen3_omni/run_multiple_prompts.sh" ??? abstract "run_single_prompt.sh" sh --8<-- "examples/offline_inference/qwen3_omni/run_single_prompt.sh" ??? abstract "run_single_prompt_tp.sh" sh --8<-- "examples/offline_inference/qwen3_omni/run_single_prompt_tp.sh"