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
- [Startup] Add --flashinfer-autotune-cache-only to load the FlashInfer autotune cache and skip startup autotuning
- [Feature][Spec Decode] ngram_hint: draft tool calls from the chat template's rendered call syntax
- [Feature]: Integrate Cake kernels via FlashInfer: model-by-model tracker
- [Doc] Document NVLS non-determinism on Hopper NVSwitch nodes
- [RFC]: Handle empty responses in synthetic acceptance benchmarks
- [Performance]: Nemotron-3.5-Lightning NVFP4 decode ~16% slower on DGX Spark (GB10/SM121) since v0.29.0
- [RFC]: Octave KV, a native 3-bit KV cache for AMD GPUs
- [Bugfix][Weight Cache] Fingerprint sampled tensor bytes, not headers only
- [Bug]: [Bug]: deepseek_r1 streaming reasoning deltas are not detokenized (byte-level BPE glyphs)
- [Bug]: ~2% output throughput regression on DeepSeek-R1 NVFP4 (DP4 + EP, GB300) from #48247 (AITER custom AG/RS)
- Docs
- Python not yet supported