vLLM v0.28.0: Kimi-K3 pass, DFlash2, Model Runner V2
Published 2026-08-26T09:46:30Z (Wed 5:46 AM ET). 584 commits, 270 contributors. Kimi-K3: Decode Context Parallel, fused FlashKDA, combined all-gathers with a project-reported 1.5–3× kernel-level speedup, adaptive speculative budget with a project-reported ~60% better DSpark TTFT, optional shared-expert sharding saving a project-reported ~17 GiB per GPU. DeepSeek V4 sparse MLA end-to-end. New models: Muse Glimmer, Ling 3.0 Flash, Dots3 NOTE, Interns2mobius. Default max_num_batched_tokens 8192 → 16384. Breaking: bitsandbytes is out-of-tree; Transformers 5.15.0. Audio sample-rate DoS fix. pip install vllm. vendor