Unverified50% confidenceTradeoffExact time
Expanding the context window brings quadratic growth in computational cost, and ultra-long contexts suffer from the 'lost in the middle' problem.
1
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50%
Confidence
Long-term
Relevance
9/8/2026
First Seen
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Related Claims
UnverifiedThe KV cache VRAM usage of ultra-long context windows grows linearly with context length, causing inference latency and costs to rise significantly.78% similarUnverifiedThe Context Window approach has length limitations, and costs grow linearly with the number of tokens.78% similarUnverifiedThe computational cost of ultra-long context models grows non-linearly with context length.74% similarUnverified更长的上下文窗口并未消除注意力稀释效应，反而带来更高的单次调用成本73% similar
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