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][Model] Kimi-K3: delegate FusedMoE padding to the selected quantization backend
- [K3 Perf] Optimize k3 dspark fused kv, 3.8~4x kernel performance improvement
- [Feature]: Kimi K3 Performance Optimization
- [Bugfix][Frontend] Fix run_batch upload retrying on success and unawaited error body
- [Bugfix] disagg MTP: keep first handoff step unpadded
- [Kimi-K3][AMD] Return KDA projection output directly
- [Kimi-K3][AMD] Fuse AttnRes state updates and norms
- [Bugfix][Structured Output] Mask request stop tokens in xgrammar until grammar terminates
- fix(config): serialize remote lazy config mappings
- [Docs] Fix stale FusedMoE references in custom quantization guide
- Docs
- Python not yet supported