vllm-omni

Easy, fast, and cheap omni-modality model serving for everyone

| Documentation | Weekly Meeting |

--- *Latest News* 🔥 - [2025/11] vLLM community officially released [vllm-project/vllm-omni](https://github.com/vllm-project/vllm-omni) in order to support omni-modality models serving. --- ## About [vLLM](https://github.com/vllm-project/vllm) was originally designed to support large language models for text-based autoregressive generation tasks. vLLM-Omni extends its support for omni-modality model inference and serving: - **Omni-modality**: Text, image, video, and audio data processing - **Non-autoregressive Architectures**: extend the AR support of vLLM to Diffusion Transformers (DiT) and other parallel generation models - **Heterogeneous outputs**: from traditional text generation to multimodal outputs

vllm-omni

vLLM-omni is fast with: - Seamless AR support for efficient KV Cache management with vLLM - Pipelined stage execution overlapping - Fully disaggregation based on omniConnector and dynamic resource allocation across stages vLLM-omni is flexible and easy to use with: - Seamless integration with popular Hugging Face models - High-throughput serving with various decoding algorithms, including *parallel sampling*, *beam search*, and more - Tensor, pipeline, data and expert parallelism support for distributed inference - Streaming outputs - OpenAI-compatible API server vLLM seamlessly supports most popular open-source models on HuggingFace, including: - Multi-modality generation models (e.g. Qwen-image) - Omni-modality models (e.g. Qwen-omni) ## Getting Started Visit our [documentation](https://vllm-omni.readthedocs.io/en/latest/) to learn more. Visit our documentation to learn more. - [Installation](https://vllm-omni.readthedocs.io/en/latest/getting_started/installation/) - [Quickstart](https://vllm-omni.readthedocs.io/en/latest/getting_started/quickstart/) - [List of Supported Models](https://vllm-omni.readthedocs.io/en/latest/models/supported_models/) ## Contributing We welcome and value any contributions and collaborations. Please check out [Contributing to vLLM-omni](https://vllm-omni.readthedocs.io/en/latest/contributing/) for how to get involved. ## Weekly Meeting - vLLM Omni Weekly Meeting: https://tinyurl.com/vllm-omni-meeting - Wednesday, 11:30 - 12:30 (UTC+8, [Convert to your timezone](https://dateful.com/convert/gmt8?t=15)) ## License Apache License 2.0, as found in the [LICENSE](./LICENSE) file.