v0.24.0
# 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 Flash
来自 vLLM 发布记录 的官方公开更新；本站仅提供短摘要与原始出处链接。
v0.24.0
# 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 Flash
来自 vLLM 发布记录 的官方公开更新；本站仅提供短摘要与原始出处链接。
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