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English(EN) How much VRAM do you need to run or fine-tune a 70B model?

70B LLM VRAM 要求:推理与微调详解

运行和微调大型语言模型,特别是 700 亿参数模型,需要大量的 GPU 内存。对于推理,一个 70B 模型在 16 位精度下大约需要 141 GB VRAM,FP8 下需要 73 GB,4 位下需要 40 GB,此外还需要 KV 缓存的内存。微调需求更高,QLoRA 需要约 50 GB,完全微调则需要高达 1.1 TB。实际配置表明,单个 80 GB GPU 可以处理 4 位推理和 QLoRA 微调,而 FP8 推理可能需要 H200 或多个 H100 GPU,完全微调则需要 8x B200 机器等大型设备。 AI

影响 确定了高效部署和训练大型语言模型所需的特定 GPU 硬件和配置。

排序理由 对运行和微调大型语言模型的硬件要求进行了详细的技术分析。[lever_c_demoted from research: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

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70B LLM VRAM 要求:推理与微调详解

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对运行和微调大型语言模型的硬件要求进行了详细的技术分析。[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) · Viswaretas Kotra ·

    运行或微调70B模型需要多少显存?

    <p>Serving a 70B model takes about 141 GB of GPU memory for the weights at 16-bit, 73 GB at FP8 and 40 GB at 4-bit, plus about 0.33 GB of KV cache for every 1,000 tokens in flight. Fine-tuning takes about 50 GB with QLoRA, 150 GB with LoRA and 1.1 TB for full fine-tuning with Ada…