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][MoE] Respect padded row strides in top-k routing
- [Bug]: minimax_m2 / glm47_moe / deepseek_v4 arg converters drop the last parameter when the model omits the closing tag (same class as #57699)
- [Bug]: minimax_m2 / glm47_moe / deepseek_v4 arg converters drop the last parameter when the model omits the closing tag (same class as #57699)
- [Feature]: [WideEP][CPU]: Add a CPU-only Wide Expert Parallelism well-lit path
- [Bugfix][DSV4.1] Warm DeepGEMM mHC projection specializations
- [Bugfix] Prevent stale collective RPC response reuse
- [Bug]: DecodeBenchConnector repeats KV cache fills for shared state tensors at large batch sizes
- [Kernel][Qwen] Tune the SM103 MoE router skinny GEMM
- [Bugfix][LoRA] Handle leading missing packed groups
- [Bug]: A weight update issued while the engine is asleep segfaults the EngineCore instead of being rejected
- Docs
- Python not yet supported