Unverified50% confidenceOpinionExact time
Fully automated agent mode requires a large number of multi-turn reasoning steps, file reads, code generation, and self-verification, causing token consumption to rise exponentially.
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50%
Confidence
Long-term
Relevance
9/12/2026
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Related Claims
UnverifiedIn Agent scenarios, each tool call requires the full context to be re-input into the model, causing token consumption to grow exponentially.75% similarUnverifiedModern Agent systems can maintain a context window of up to tens of thousands of tokens within a single session and perform multi-step logical decomposition of complex experimental plans through chain-of-thought reasoning mechanisms74% similarUnverifiedAgents repeatedly execute the perception-planning-action loop in cycles, and each round requires packing the complete history into the context window, causing input tokens to grow linearly or even exponentially.74% similarUnverifiedCompleting a complex task in an agent application often requires multiple rounds of reasoning and invocation, with each step generating token consumption73% similar
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