vLLM v0.24.0 Release Notes Highlights This release features 571 commits from 256 contributors (77 new)! MiniMax-M3: Added support for the new MiniMax-M3 model (#45381), with a fast follow-on of BF16/FP8 indexer via MSA (#45892), MXFP4 support (#45896), FP8 sparse GQA (#45744), and extensive AMD/ROCm tuning — mxfp8 MoE/linear on gfx950 (#45725), fp8_per_channel for bf16 weights on MI300X (#45854), FP8 KV-cache fix (#45720), and packed-modules mapping (#45794). A MiniMax-M2 perf regression was also fixed (#45935). DeepSeek-V4 keeps maturing: Following its debut, DeepSeek-V4 received another large optimization pass — a FlashInfer sparse index cache (2–4% TTFT) (#45863), prefill chunk-planning optimization (4% E2E throughput) (#45061), a cluster-cooperative topK kernel for low-latency (#43008), contiguous per-block KV allocations (#44577), TEP=16 for the block-FP8 shared expert (#46001), and native DSA indexer decode for `next_n > 2` on SM100 (#45322).

It is now enabled on SM120 alongside GLM-5.1 (#43477), with XPU (#44144, #44517, #45240) and ROCm (#44899, #45103, #45681) attention/MoE paths added. Model Runner V2 (MRv2) continues to expand: MRv2 now supports quantized models by…