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
- [Model] do normalize and rescale in device.
- [Model] Fix weight prefix mapping for native Qwen3.5 text-only checkp…
- [Misc] Warn when --block-size is silently discarded by backend alignment
- [Bugfix][Spec Decode] Capture the widest uniform decode batch by default
- [Bugfix] Preserve truncated Kimi K3 reasoning
- VLLM_ATTENTION_BACKEND env var is silently ignored — attention_backend= LLM()/EngineArgs kwarg is the only mechanism that works
- [Kernel][Model] Optimize FA4 mm_prefix range lookup
- [Test] Add per-parser tool-call format conformance tests
- [Core] Add TP-invariant tree kernels across TP sizes
- [ROCm] Implement is_integrated_gpu() for APU unified-memory accounting
- Docs
- Python not yet supported