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
- [Bug]: required numpy version mismatch between modules
- fix: optimize cold start compilation by triggering torch.compile with minimal batch size
- [ROCm][CI] Fix serving tokens test failures
- [Bug]: pd disaggregation on the same host with nixl connector can not use nvlink to transfer kv cache
- [Bug]: Qwen3-1.7B apparently not respecting max-model-len (can't generate >2048 tokens)
- [Feature]: W4A16 (int4) GEMM / Grouped GEMM Kernels for AMD
- [Feature]: MXFP8 GEMM / Grouped GEMM Kernels for AMD
- [RFC]: Helix (Context + Tensor) Parallelism for Efficient Long-Context Decoding
- [Doc]: Setting Encoder Cache for MultiModal LLMs
- [Feature][Scheduler] Add split prefix caching feature to eliminate bf16 GEMM tiling divergence across cache-hit/miss paths
- Docs
- Python not yet supported