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 Runner V2] Support sharing kv cache layers
- feat: Support MXFP4 quantized dense models on AMD CDNA2/CDNA3 GPUs
- Add engine KV checkpoint rewind and lifecycle tools
- [RFC]: Adding Support for Single Batch Overlap (SBO) With FlashInfer DeepEP LL NVFP4
- [Feature]: Remove embedding initialization in cases where embedding is not needed in gpu_model_runner init
- Allow _dummy_run to use _model_forward for hardware backends with compiled execution
- [Feature]: Infrastructure Improvements for ROCm CI
- [Core]Optimize SlidingWindowManager.find_longest_cache_hit by skipping positions on cache miss
- [GGUF] Fix loading of fused/shard-less quantized weights
- [Bug]: FlashInfer attn-fp4 fused kernel performs worse than unfused
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- Python not yet supported