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
- [Core] Release the CUDA graph pool on sleep instead of backing it up
- [Bugfix][Frontend] Count prompt-opened Inkling reasoning tokens
- [Kernel] Add opt-in LiteTopK FP32 decode with producer histograms
- [DeepSeek-V4-P3] deterministic MoE DeepEP
- [Bug] DeepSeek-V4-Flash tool-call format failures associated with prefix-cache reuse; worst for short cached head + long uncached suffix; `cache_salt` reduces failures but is confounded with hit shape (v0.27.1, fp8 KV, MTP)
- [Bugfix] Bound prompt_embeds decode budget per request
- [Core] Release DeepEP all2all buffers on sleep with comm suspend
- [Bug]: gemma4 loader requires k_proj/v_proj/k_norm for KV-shared layers that transformers 5.5.4 never saves; any transformers-saved gemma4 checkpoint is refused
- [Bugfix][NIXL] Count pull completion notifications per transfer
- docs: add Gemma 4 Models tool-calling section
- Docs
- Python not yet supported