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English(EN) How much RAM does a local LLM need on a Mac? Measurements on 16 GB and a 16–128 GB sizing table

Mac 本地大语言模型的 RAM 要求:内存使用深度解析

在 Mac 上本地运行大语言模型需要仔细考虑 RAM 使用情况,这部分 RAM 分配给模型权重、上下文窗口(KV 缓存)以及操作系统。测量结果表明,大语言模型实际可用的 RAM 约占总 RAM 的四分之三,上下文大小显著影响内存预留,尤其是在较旧的模型架构中。Qwen 和 Gemma 等较新模型显示出更高效的上下文缓存,减少了长文档的内存开销。 AI

影响 了解 RAM 要求对于希望在本地运行大语言模型的用户至关重要,它会影响硬件购买决策和模型选择。

排序理由 该项目详细介绍了在特定硬件上运行大语言模型的测量和技术要求分析,属于研究类别。[lever_c_demoted from research: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

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Mac 本地大语言模型的 RAM 要求:内存使用深度解析

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该项目详细介绍了在特定硬件上运行大语言模型的测量和技术要求分析,属于研究类别。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Kirill Lukyanov ·

    本地 LLM 在 Mac 上需要多少 RAM?16 GB 实测及 16–128 GB 容量表

    <p>"Will this model run on my Mac?" usually gets answered with the model's file size. That's only a third of the answer. While a model runs, memory goes to three things: the weights, the context (KV cache) and macOS with everything else you have open. I measured three models on m…