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
- [Usability] Engine fails to start when available Mamba cache blocks < max_num_seqs (hybrid models + LoRA) — suggest auto-clamping with a warning
- fix(v1): skip full GC during EngineCore process exit
- [Doc] Add health probes to the AMD deployment example in k8s.md
- [Model Runner V2][Spec Decode] Add multi-layer MTP speculator
- [Bug]: EAGLE-3 + prompts >2048 tokens: device-side assert (Triton `index < 2048`) in inductor-compiled eagle_head kernels; eager works, cudagraph_mode=NONE still crashes (v0.24.0)
- [Attention] Add direct symmetric-memory DCP A2A
- [Frontend][Core][Spec Decode] Per-request acceptance stats in OpenAI API responses
- [ROCm] Support MiniMax-M3 NVFP4 SwiGLU-OAI
- [ROCm][Quark][7/N] Use MXFP4 linear kernel abstraction for `emulation` backend
- Add pushed-based ZMQ metrics logger support
- Docs
- Python not yet supported