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
- [KV Connector][4/N][NIXL] Recover all dedup'd HMA pool members (FA + multi-group SSM) under PP
- [Bug][ROCm/gfx942] GPU memory access fault (worker crash) when sequences cross 2048 tokens — DeepSeek V4 flash arch, sparse_attn_indexer + fp8 KV cache, MI325X TP=4
- [ModelRunner v2] Enable MRV2 for all pooling models by default
- [Roadmap] 2026 Q3 vLLM × RL
- docs: add community health files (CHANGELOG.md)
- [Doc] Clarify that max_num_batched_tokens also shrinks the KV cache pool
- [Bugfix] YaRN RoPE: honor explicit attention_factor from the rope config
- [Model] Add GraniteSWA and GraniteMoeSWA
- [RFC] Heterogeneous rank-to-GPU mapping + Qwen3.5/3.6 GGUF enablement
- [Bugfix][Tool Parser] Stream tool calls that arrive whole in a single delta in llama3_json, jamba and ernie45 parsers
- Docs
- Python not yet supported