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
- [Bugfix][Quantization] Keep unquantized routed experts unquantized under AutoGPTQ
- [Bugfix][MM] Profile the multimodal embedding merge during memory profiling
- [Doc][Core] Clarify FlashInfer spec-decode PIECEWISE cudagraph downgrade warning
- [Models][Quantization] Qwen3.5 MTP: honor checkpoint per-layer quantization config for draft layers
- [Feature] implement return indexer topk of sparse attention
- [Bugfix][NIXL] Mark transfer as failed when check_xfer_state() raises
- [Bugfix][Tool Parser] Preserve whitespace in Step3 parameter values
- [EPLB] Support custom initial expert maps
- [Bug]: FlashInfer b12x SM120 MoE workspace allocated inside `profile_run` → OOM on 16 GB Blackwell (NVFP4 Qwen3.6-35B-A3B); regressed between vLLM dev552/FlashInfer 0.6.12 and v0.25.1/FlashInfer 0.6.13
- [Bug]: vllm bench serve - huggingface datasets - "TypeError: string indices must be integers, not 'str'"
- Docs
- Python not yet supported