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
- [Attention][TurboQuant] Preserve configured FlashAttention version
- [Bug]: Combination of sleep mode and speculative decoding cause crash (ROCm / MI250)
- fix(quant): forward MiniMax M3 SwiGLU parameters to FusedMoEQuantConfig in int8 paths
- [Bug]: Gemma4 (probably other models with missing v_proj) breaks with mixed quantization
- [CI/Build] Remove stale xfail marks from min_tokens e2e tests
- [Bugfix] Allow untyped tool schemas to coerce JSON values
- [Feature]: Support NVIDIA Nemotron 3.5 ASR Streaming (nemotron-3.5-asr-streaming-0.6b)
- [Perf] Maintain persistent penalty statistics instead of per-step CPU rebuild in V1 sampler
- [Bug]: Incoherent output depending on tensor-parallel-size during inference on Leanstral (Mistral Small 4 family)
- [Bug]: CPU DP affinity regression
- Docs
- Python not yet supported