Verified65% confidenceFactExact time
In multi-turn conversations, before each new response is generated, the system must re-input all prior conversation history into the model, causing token consumption to accumulate and grow with each turn
3
Sources
65%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
UnverifiedMulti-turn dialogue is implemented by re-inputting all previous conversation history to the model with each request, rather than the model having genuine memory capability.84% similarUnverifiedEach model response includes the full conversation history (context window) in billing, and as the number of dialogue turns increases, the token consumption per call grows linearly or even super-linearly.83% similarUnverified传统ReAct框架要求模型在每次工具调用后将结果写回上下文再重新读取整个对话历史决定下一步，导致Token消耗和延迟累积76% similarUnverifiedDue to the cyclic reasoning nature of Agent systems, the complete conversation history is resent to the model after each tool call, causing Token consumption to grow super-linearly.76% similarUnverifiedIn each iteration of the loop, an agent needs to repackage the system prompt, conversation history, tool descriptions, and all outputs from previous steps before feeding them into the model, causing token consumption to grow linearly or even super-linearly with the number of steps.75% similar
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