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
- [MyPy] Fix mypy errors in kimi model family (3/5 files)
- [Feature/Gap] DSA models (GLM-5.1 / DeepSeek-V3.2-family, use_sparse=True) cannot select any attention backend on SM121 (GB10 / DGX Spark)
- [Feature]: Expose LoRA Adapter Cache Residency in vLLM Metrics
- [Kernel] [vLLM IR] [Perf] Add support for mixed input/weight dtype to rms norm quant fusion ops
- [Bug] test_w8a8_block_fp8_fused_moe uses fixed atol that K=7168 quantization noise legitimately exceeds (fails on SM120/RTX PRO 6000)
- [Feature][ModelOpt]: Support NVFP4_AWQ checkpoints with native NVFP4 linear kernels
- [KV Connector][NIXL][Mooncake] CP-scaled scheduler block accounting for PD disaggregation with aligned DCP/PCP
- Fix Responses Harmony instructions placement
- [Kernel] Fix strict-aliasing UB in scalar_type and minimax RMS kernel
- [Feature]: IndexCache support for DeepSeek V4
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