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][Parser] Fix streaming tool-call args truncated by schema coercion
- [Bugfix] Make Gemma 4 suppress-token masking CUDA-graph safe
- [Bugfix] Avoid FlashAttention 3 with batch invariance on Hopper
- [Bugfix] Share FlashInfer B12x MoE workspace across layers
- Dynamic-fork scheduling, Medusa/MTP spec decode, and InternVL resize for HPD-Parsing (based on v0.17.1)
- [RFC]: GDS support for filesystem KV-cache offloading
- [XPU][UT]Convert awq-packed MoE qweight to the gptq-equivalent layout on xpu
- [XPU] Dockerfile.xpu: LD_LIBRARY_PATH misses /opt/venv/lib -> torch sees 0 XPU devices in the built image
- fix(models): pass quant_config to eh_proj in MTP layers to prevent silent precision loss
- [Bugfix] Initialize MiniMax M3 reasoning from prompt mode
- Docs
- Python not yet supported