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
- [Kernel] Add opt-in cuda cache update for flash_attn_diffkv
- SWA Hybrid attention integrated with FlashInfer MLA + DCP
- DCP + split-q for speculative decoding support
- [Bugfix] Verify functional P2P before enabling MiniMax fused allreduce+RMSNorm
- [Model] Allow Gemma4 to use FlashInfer when FA4 is unavailable
- [Bug]: REGRESSION : FP8 KV cache FlashInfer no longer available as attention backend on SM75 (Turing) in v0.24.0
- perf: add DiffusionGemma consumer-sufficient TP vocab state
- DOC: clarify Windows support in quickstart prerequisites
- Revert "Xqa decode kernels" (#43232)
- [Bugfix][SM120][MLA] Support FlashInfer packed sparse MLA decode
- Docs
- Python not yet supported