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
- [Performance]: DeepSeek-V3.2 under DCP: FP8 sparse attention processes other ranks' masked top-k slots on Hopper
- [Benchmark] Record output token counts and output tok/s in bench throughput --output-json
- [Kernel] Add distributed Triton autotune foundation
- [Perf][DCP] DeepSeek-V3.2: skip other ranks' top-k slots in FP8 sparse attention on Hopper
- [Perf][MoE] Prefer Triton for block FP8 MoE on SM120
- [Roadmap] Q4 2026 vLLM × RL
- [Weight Reload][GLM5-next] Refresh derived caches in stable storage
- [Weight Reload][Kimi K3] Refresh MLA inverse scales in stable storage
- [Weight Reload][DeepSeek] Refresh hyperconnection broadcast buffers
- [Weight Reload][CPU] Preserve DeepSeek packed projection and norm caches
- Docs
- Python not yet supported