Unverified50% confidenceFactExact time
Under a linear conversation structure, token consumption is cumulative—every request requires retransmitting the entire history, increasing inference latency and driving up API call costs.
1
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50%
Confidence
Long-term
Relevance
8/24/2026
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Related Claims
Unverified随着对话轮次增加，每轮需携带完整历史上下文，输入token数量持续膨胀，导致推理时间呈现非线性增长80% similarUnverifiedAgent间通信会导致上下文窗口线性增长使成本呈指数级攀升，以及长对话链中的「目标漂移」现象76% similarUnverifiedThe KV cache VRAM usage of ultra-long context windows grows linearly with context length, causing inference latency and costs to rise significantly.75% similarUnverifiedAs multi-turn tool calls and conversations accumulate in Agent tasks, context expansion causes inference costs to rise exponentially and response latency to increase74% similar
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