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]: Model Runner V2 + Gemma-4: memory profiler reports ~0.9 GiB more "available KV" than MRv1 → no runtime headroom → CUDA OOM under saturating load (no spec involved); with EAGLE it crashes earlier at cudagraph capture (stable-ABI aten::empty)
- [Doc]: Update Quickstart documentation with Apple Silicon / Metal execution requirements and compatibility note
- LUT-B quantization accuracy prototype
- [Feature] Qwen3-Next (GDN): mamba_cache_mode="all" prefix caching with speculative decoding (MTP) on V1
- [Bugfix][Core][Spec Decode] Skip spec-decode block reservation on the external-KV-load step (P/D)
- [1/N][warmup][DSv4] Migrate shared NVIDIA and MLA kernels
- [2/N][warmup][DSv4] Migrate attention kernels
- [3/N][warmup][DSv4] Migrate MoE kernels
- [4/N][warmup][DSv4] Migrate MHC TileLang kernels
- [Bugfix] Only require symm-mem multicast when multimem is the selected algorithm
- Docs
- Python not yet supported