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# Qwen3-Omni for multimodal chat on 1x A100 80GB
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## Summary
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- Vendor: Qwen
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- Model: `Qwen/Qwen3-Omni-30B-A3B-Instruct`
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- Task: Multimodal chat with text, image, audio, or video input
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- Mode: Online serving with the OpenAI-compatible API
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- Maintainer: Community
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## When to use this recipe
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Use this recipe when you want a known-good starting point for serving
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`Qwen/Qwen3-Omni-30B-A3B-Instruct` with vLLM-Omni on a single 80 GB A100 and
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validate the deployment with the existing multimodal client examples in this
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repository.
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## References
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- Upstream or canonical docs:
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[`docs/user_guide/examples/online_serving/qwen3_omni.md`](../../docs/user_guide/examples/online_serving/qwen3_omni.md)
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- Related example under `examples/`:
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[`examples/online_serving/qwen3_omni/README.md`](../../examples/online_serving/qwen3_omni/README.md)
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- Related issue or discussion:
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[RFC: add recipes folder](https://github.com/vllm-project/vllm-omni/issues/2645)
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## Hardware Support
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This recipe currently documents one tested-style reference configuration for
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CUDA GPU serving. Add more sections for other hardware as community validation
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lands.
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## GPU
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### 1x A100 80GB
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#### Environment
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- OS: Linux
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- Python: 3.10+
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- Driver / runtime: NVIDIA CUDA environment with an A100 80 GB GPU
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- vLLM version: Match the repository requirements for your checkout
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- vLLM-Omni version or commit: Use the commit you are deploying from
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#### Command
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Start the server from the repository root:
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```bash
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vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
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```
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To enable async chunking, use the bundled stage config:
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```bash
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vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct \
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--omni \
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--port 8091 \
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--stage-configs-path vllm_omni/model_executor/stage_configs/qwen3_omni_moe_async_chunk.yaml
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```
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#### Verification
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Run one of the existing example clients after the server is ready:
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```bash
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python examples/online_serving/openai_chat_completion_client_for_multimodal_generation.py \
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--model Qwen/Qwen3-Omni-30B-A3B-Instruct \
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--query-type use_image \
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--port 8091 \
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--host localhost
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```
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For a quick API smoke test, request text-only output:
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```bash
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curl http://localhost:8091/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "Qwen/Qwen3-Omni-30B-A3B-Instruct",
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"messages": [{"role": "user", "content": "Describe vLLM in brief."}],
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"modalities": ["text"]
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}'
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```
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#### Notes
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- Memory usage: Size depends on runtime options and output modalities; leave headroom for multimodal workloads.
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- Key flags: `--omni` is required; `--stage-configs-path` is optional for custom or async-chunk stage configs.
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- Known limitations: This starter recipe is intentionally narrow and focuses on the single-GPU online-serving path already documented in the repo examples.
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# Community Recipes
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This directory contains community-maintained recipes for answering a
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practical user question:
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> How do I run model X on hardware Y for task Z?
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Add recipes for this repository under this in-repo `recipes/` directory. To
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keep naming and layout consistent, organize recipes by model vendor in a way
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that is aligned with
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[`vllm-project/recipes`](https://github.com/vllm-project/recipes), but treat
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that external repository as a reference for structure rather than the place to
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add files for this repo. Use one Markdown file per model family by default.
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Example layout:
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```text
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recipes/
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Qwen/
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Qwen3-Omni.md
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Qwen3-TTS.md
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Tencent-Hunyuan/
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HunyuanVideo.md
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```
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## Available Recipes
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- [`Qwen/Qwen3-Omni.md`](./Qwen/Qwen3-Omni.md): online serving recipe for
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multimodal chat on `1x A100 80GB`
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Within a single recipe file, include different hardware support sections such
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as `GPU`, `ROCm`, and `NPU`, and add concrete tested configurations like
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`1x A100 80GB` or `2x L40S` inside those sections when applicable.
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See [TEMPLATE.md](./TEMPLATE.md) for the recommended format.
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# Recipe Title
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> Example: Qwen3-Omni for speech chat on 1x A100 80GB
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## Summary
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- Vendor:
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- Model:
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- Task:
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- Mode:
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- Maintainer:
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## When to use this recipe
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Briefly describe the concrete scenario this recipe covers.
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## References
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- Upstream or canonical docs:
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- Related example under `examples/`:
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- Related issue or discussion:
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||||
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||||
## Hardware Support
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|
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Add one section per platform, such as `GPU`, `ROCm`, or `NPU`. Under each
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platform section, document one or more tested hardware configurations.
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## GPU
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### 1x A100 80GB
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#### Environment
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- OS:
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- Python:
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- Driver / runtime:
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||||
- vLLM version:
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||||
- vLLM-Omni version or commit:
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||||
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#### Command
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```bash
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# Add the exact command(s) here
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```
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#### Verification
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||||
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```bash
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# Add a quick validation command or expected output here
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```
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#### Notes
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- Memory usage:
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- Key flags:
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- Known limitations:
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|
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### 2x L40S
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|
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Repeat the same structure for other hardware setups as needed.
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|
||||
## ROCm
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||||
|
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### Example hardware configuration
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||||
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Repeat the same nested structure for ROCm setups as needed:
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||||
|
||||
- `#### Environment`
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||||
- `#### Command`
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||||
- `#### Verification`
|
||||
- `#### Notes`
|
||||
|
||||
## NPU
|
||||
|
||||
### Example hardware configuration
|
||||
|
||||
Repeat the same nested structure for NPU setups as needed:
|
||||
|
||||
- `#### Environment`
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||||
- `#### Command`
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||||
- `#### Verification`
|
||||
- `#### Notes`
|
||||
Reference in new issue
Block a user