vllm-project/vllm-omni

**vllm-project/vllm-omni**

A framework for efficient model inference with omni-modality models Easy, fast, and cheap omni-modality model serving for everyone | Documentation | User Forum | Developer Slack | WeChat | Paper | Slides | Latest News 🔥 [2026/03] Check out our first public project deepdive at the vLLM Hong Kong Meetup. [2026/03] vllm-omni-skills is a community-driven collection of AI assistant skills that help developers work with vLLM-Omni more effectively. These skills can be used with popular agentic AI coding assistants like Cursor IDE, Claude, Codex, and more. [2026/02] We released 0.16.0 - A major alignment + capability release that rebases onto upstream vLLM v0.16.0 and significantly expands performance, distributed execution, and production readiness across Qwen3-Omni / Qwen3-TTS, Bagel, MiMo-Audio, GLM-Image and the Diffusion (DiT) image/video stack—while also improving platform coverage (CUDA / ROCm / NPU / XPU), CI quality, and documentation. [2026/02] We released 0.14.0 - This is the first stable release of vLLM-Omni that expands Omni’s diffusion / image-video generation and audio / TTS stack, improves distributed execution and memory efficiency, and broadens platform/backend coverage (GPU/ROCm/NPU/XPU)...

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