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
- [Bug]: Qwen parser routes grammar-constrained JSON to reasoning when `enable_in_reasoning=true`
- [Bug][Rocm] LMcache running issues for the kimik3 Dspark
- [Perf][Multimodal] Downmix audio channels by slicing instead of reducing
- [Bug][ROCm] Remove `AITER_MXFP4_BF16` and `AITER_MXFP4_FP8` MOE routing hotfix once AITER is bumped
- [Frontend] Add Holo2 reasoning parser
- [Bug]: `BaseThinkingReasoningParser.extract_reasoning` silently discards output text when `<think>` appears mid-stream
- [XPU] Work around Battlemage oneCCL IPC handle cache device-loss failures
- [Feature] Enable AITER MXFP4 MoE on gfx942 and optimize tile configurations for MI325X Target Kimi K3 running on MI325X
- [Doc] Troubleshooting: FlashInfer JIT failure on a GPU newer than the local CUDA toolkit
- Remove attention layer name from unified_kv_cache_update for torch.compile
- Docs
- Python not yet supported