Unverified50% confidenceFactExact time
大语言模型的注意力机制计算复杂度与序列长度的平方成正比，处理200K token上下文的计算成本远超过处理50K token
1
Sources
50%
Confidence
Long-term
Relevance
8/25/2026
First Seen
Sources
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Related Claims
VerifiedThe self-attention mechanism causes computational complexity to grow quadratically with sequence length, so expanding the context from 1,000 to 4,000 tokens increases the computation by 16 times.80% similarUnverified在推理阶段内存带宽往往比纯算力更早成为瓶颈，注意力机制需在每步生成时读取全部KV缓存，上下文长度增大时内存读写开销呈平方级增长72% similarUnverifiedEven large language models that support context lengths of 128K or longer will experience attention dilution when all capability instructions are injected at once, causing a decline in execution quality for specific tasks.71% similar
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