The vLLM project (@vllm_project) released v0.30.0 with 762 commits from 315 contributors. Highlights include hybrid-attention hot paths for Kimi K3 (KDA/AttnRes/MLA), DeepSeek-V4.1-Flash (MXFP8 KV and async Engram), and Qwen3.8-Flash-Next (QSA/PLE, lower sparse-GQA overhead); plus HiSparse host-tier decode, Model Runner V2 EAGLE3 pipeline parallelism with adaptive verification, dual-key Gumbel-max watermarking, Fast Start CUDA IPC weight cache, and new models such as GLM-5.3-Flash, K2-Horizon, Cohere Compass, and Bailing V3 VL.

Key Takeaways

  • ✓Hybrid-attention hot paths cover Kimi K3, DeepSeek-V4.1-Flash, and Qwen3.8-Flash-Next.
  • ✓Model Runner V2 brings EAGLE3-style drafts to pipeline parallelism with online acceptance estimation.
  • ✓Fast Start maps post-quantized TP-sharded weights over CUDA IPC for faster restarts.
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