English(EN) Fine-tuning a 7B model needs 112 GB. The model is only 14 GB of it.

微调LLM：内存成本解析，LoRA & QLoRA解决方案

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-03 04:00

微调一个拥有70亿参数的模型所需的内存远超模型本身的权重大小，完全微调大约需要112GB。如此大的内存需求主要是因为梯度和优化器状态，它们大约占用了84GB，而模型fp16权重仅需14GB。LoRA和QLoRA等技术通过冻结基础模型权重并仅训练一小部分适配器参数，极大地降低了内存需求，其中QLoRA通过以4位精度存储基础模型进一步优化。 AI

影响强调了LoRA和QLoRA等内存优化技术，这些技术对于使LLM微调更加普及至关重要。

排序理由关于LLM微调内存需求和优化技术的技术解释。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

dev.to — LLM tag TIER_1 English(EN) · Arun Kumar · 2026-10-03 04:00

微调一个7B模型需要112GB。模型本身只占14GB。

<p>Ask how much memory it takes to fine-tune a 7B model and the instinct is "the model's 14 GB in fp16, so a bit more than that". The real figure is about 112 GB, before you've stored a single activation. The model is 14 GB of it.</p> <p>Once you see where the other 98 GB goes, L…

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微调一个7B模型需要112GB。模型本身只占14GB。

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