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
- benchmarks(serve): include dataset_name in result_json
- [ROCm] do not blindly pick gpu 0 for asic info, consider *_VISIBLE_DEVICES
- [Bugfix][Frontend] Apply stop strings only after reasoning ends
- [Perf][MiniMax-M3] Add opt-in FP16 sparse decode tuning
- [RFC][Experimental]: Model- and platform-customized KV cache planning
- [Bugfix][Quantization] Count only checkpoint elements for padded online-quant MoE weights
- [Bugfix] Skip request body JSON serialization when its log level is disabled
- [Bugfix][Model Loader] Evict loaded shards when checkpoint exceeds RAM
- [Attention] Support NVFP4 KV cache at head_dim 512 (Gemma 4) on SM100
- [Bug]: prompt_logprobs=0 bypasses fast-prefill guard, causing V1 crash or V2 silent errors
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- Python not yet supported