Unverified50% confidenceFactExact time

序列长度为4096时，N×N注意力矩阵在FP16精度下仅此一项就消耗约64MB显存

1

Sources

50%

Confidence

Long-term

Relevance

7/15/2026

First Seen

Sources

CUDA内核融合：减少显存带宽消耗与启动开销的实战指南

Related Claims

Unverified128K长度的序列所需的注意力计算量是4K长度序列的1024倍76% similar Unverified170k tokens场景下，注意力得分矩阵在BF16精度下约需54GB显存（170000×170000×2字节）76% similar Verified以70B参数模型、FP16精度、32层注意力头为例，单条200K长度请求的KV Cache约需80-120GB显存，远超单张A100 GPU的80GB显存上限74% similar

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