Verified80% confidenceFactTime unknown
Transformer架构的自注意力机制在处理长序列时面临二次方复杂度的计算开销，上下文长度翻倍则计算量增长四倍
7
Sources
80%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
Windsurf续杯插件实测：积分自动刷新+多窗口并发教程
bilibili默然萧璃
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UnverifiedTransformer的KV Cache随序列长度呈二次方增长，导致长上下文推理对GPU显存的非线性消耗75% similarUnverifiedPure Transformer architectures see inference costs grow quadratically with sequence length75% similarUnverifiedSSM在长序列处理上具有线性时间复杂度优势，而标准Transformer的注意力计算复杂度为序列长度的平方75% similarVerified注意力机制的计算复杂度随上下文窗口长度呈平方级增长，导致推理延迟与成本急剧上升73% similar
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