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
- [Kernel] Optimize fused_add_rms_norm with software pipelining
- Add DeepSeek-V4 DCP decode support
- [Refactor] Extract _bucket_layers_by_page_size from DSV4 KV cache config
- [Bugfix] Fix DeepSeek-V4 init errors for compressed tensors
- [Model Runner V2] Enable all dense models for mrv2 [4/N]
- Lwilkinson/kv layout/kv content pack
- KV events: BlockStored token_ids can span skipped Mamba align blocks while block_hashes omit them
- [Kernel][MoE] Delegate finalize output-buffer allocation to prepare_finalize
- [Experiment][Model Runner V2][Spec Decode] sharded rejection sampling
- [2/N][KV-Cache Layout Refactor] Pack K/V into the content dim across attention backends
- Docs
- Python not yet supported