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
- [RFC]: Stable runtime tensor lifecycle for sleep and live weight reload
- [Experimental] Add CUDA graph discard and lazy recapture to sleep/wake
- [Spec Decode] Support Kimi-K3 MLA drafts in DFlash2
- [Bugfix][EC Connector] Size transfers by measured encoder output widths
- [ROCm][DO NOT MERGE] RDNA3 (gfx1100) full inference stack — tracking branch for splitting into landable PRs
- [Bug]: --kv-cache-memory suggestion double-counts CUDAGraph memory (regression of #37426, reintroduced by #49208)
- [Bug]: FunctionGemma rejects hyphenated tool names only in non-streaming responses
- [KV offload] Add max_recompute_pending_tokens to skip waiting on short in-flight offloads
- [Feature]: [ROCm][AITER][Hy4] Enable gfx950 MXFP8 MoE and dense linear backends
- [Model] Add AliceAI support
- Docs
- Python not yet supported