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
- feat(spec_decode): Grammar-aware draft token sampling for structured outputs
- [Bug]: OffloadingConnector: DSpark draft-model KV-cache group's sparse storage causes external_prefix_cache_hits_total to be permanently 0
- Reject unsafe FlashInfer BF16-Q + spec decode + SWA on SM100
- [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
- [ROCm]: Bump torch 2.12, torchvision, torchaudio, triton 3.7
- [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
- [Core] Pre-size cudagraph output staging buffers to the max capture descriptor
- Docs
- Python not yet supported