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
- Add routed-expert prefix omission for AuxOutput
- [AuxOutput] Add Mooncake backend with keys-only R3 output
- [Bugfix][Responses API] Execute parallel built-in tool calls
- [Bugfix] step3 tool parser: record streamed arguments so the finalizer does not duplicate them
- [Bugfix][Spec Decode] Reject ngram_gpu with pipeline parallelism
- fix(security): harden media URL fetching against SSRF
- [Bugfix] Use 64-bit token offsets in fused GDN post-conv prep
- [ROCm][Model][MiniMax-M3] Context-parallel sparse lightning indexer (Triton, opt-in)
- [Bug]: RowWiseTorchFP8ScaledMMLinearKernel is selected on RDNA4 (gfx1201) from v0.28 and costs 5-24% decode
- [ROCm][Model][MiniMax-M3] Context-parallel AITER sparse indexer (fp8, opt-in)
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- Python not yet supported