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]: Let Platforms customize fused MoE Router construction
- [Bug]: int8_per_token_head KV with prefix caching DISABLED corrupts the FIRST generated tokens (Gemma-4 hybrid, Triton, idle KV pool)
- [Bug]: Responses API Returns Raw Malformed Kimi Tool Marker as Assistant Text Instead of function_call
- [Bug]: NVFP4 MoE falls back to Marlin on sm_121 (GB10) in published builds, making the model unservable on a unified 121 GiB pool
- [Bugfix] Resolve $ref/$defs in tool schemas and preserve definitions
- perf: skip re-validating reused sampling params in streaming input loop
- [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
- Docs
- Python not yet supported