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
- fix: optimize cold start compilation by triggering torch.compile with minimal batch size
- [Feature]: W4A16 (int4) GEMM / Grouped GEMM Kernels for AMD
- [Feature]: MXFP8 GEMM / Grouped GEMM Kernels for AMD
- [Feature][Scheduler] Add split prefix caching feature to eliminate bf16 GEMM tiling divergence across cache-hit/miss paths
- [RFC] Change the directory layout from `scaled_mm/` and `mixed_precision/` to backend-first .
- [Anthropic API] Fix 6 protocol compliance bugs in Messages endpoint
- [CI] Add P2pNccl integration test + rename nixl_integration to pd_integration
- [Perf] Optimize async scheduling redundant copy, 0.9% E2E throughput improvement
- [BugFix] Fix mm_encoder_only init for qwen3 vl moe model
- [Core] Add Helix (Context + Tensor) Parallelism
- Docs
- Python not yet supported