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]: Gemma4 engine-based tool parser returns all bare-value arguments as strings (scilent behavior change)
- [Bug]: gigachat3, granite and granite-20b-fc tool parsers lose tool calls when the whole message arrives in a single streaming delta
- [Bug]: V1 + Ray distributed executor + LoRA — execute_model returns NoneType on NVIDIA GPU
- [RFC] guard-gated sparse MLA topology index policy
- [KV Cache] Native simulator
- Preserve DeepSeek sigmoid grouped routing metadata
- [Performance]: How to set allow_hybrid_mode in DeepEP V2
- [Bug]: vllm 校验arguments合法性
- [Perf] SM120 PCIe serving stack: SP/async-TP enablement, FlashInfer spec-decode FULL cudagraphs, and PCIe-safe multi-GPU comms
- Support attention-HMA PP prefill in NixlPushConnector
- Docs
- Python not yet supported