vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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- Issues
- [Feature][CLI] Unify configuration for structured outputs via `--structured-outputs-config`
- [torch.compile][ROCm] Fuse quantization onto attention using a torch.compile pass
- [Kernel] Adding basic Triton JitCache for triton_attn
- [V1] Add request-level, per-step acceptance counts tracking for spec dec.
- [Usage] Qwen3 Usage Guide
- [CI] Add mteb testing to test the accuracy of the embedding model
- [New Model]: Multimodal Embedding Model GME.
- Support embedding models in V1
- Add FlexAttention to V1
- [V0][V1][Core] Add outlines integration for V1, and update V0 integration.
- Docs
- Python not yet supported