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
- [Feature] Add mamba ssu kernel autotune at warmup time
- [ROCm] DeepSeek-V4-Pro PD Disaggregation through MORI IO KV Connector on AMD GPUs
- [Kernel][Helion] Add packed per-token group FP8 quant
- [Helion] Route fusion-only kernels to Helion during CUDA-graph capture
- [ROCm][Bugfix] Fix Triton W4A16 bug in determining if transpose is required for GPTQ/AutoGPTQ
- [Bug]: Speculative Decoding + Structured Output(tool call)组合下,decode 阶段出现秒级卡顿
- [XPU] Support sequence parallelism for block fp8 on XPU
- [Feature]: nvfp4 KV cache on SM120 — flashinfer ships the kernels, vLLM isn't wired to them (working prototype, 245K ctx on a 5090)
- [Bug]: nvfp4 reshape_and_cache_flash assumes NHD layout — silently mis-swizzles HND caches when num_kv_heads % 4 == 0
- [Perf] ~2x decode throughput regression for structured outputs since #45424: apply_grammar_bitmask staging rewrite (bisected to commit, file, and hunk)
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