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端侧大模型内存不够怎么办？读懂DUAL-BLADE的KV缓存卸载

This story is from 2026-10-23. It is preserved in the archive; the latest stories are on the live feed.

在个人电脑和边缘设备上运行大语言模型，瓶颈不只在模型权重。上下文越长，保存注意力历史信息的KV cache也越大。把缓存放进NVMe SSD可以扩展容量，但数据搬运本身可能拖慢生成。 2026年4月公开的论文《DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference》研究的正是这一问题。作者为Bodon Jeong、Hongsu Byun、Youngjae Kim、Weikuan Yu、Kyungkeun Lee、Jihoon Yang和Sungyong Park。本文是论文解读，不是自行完成的性…

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  1. 2026-10-23 10:08 · DEV Community — AI
    端侧大模型内存不够怎么办？读懂DUAL-BLADE的KV缓存卸载

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