Unverified50% confidenceFactExact time
Reasoning models and verbose system prompts can significantly change the actual number of tokens consumed by a task.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedMainstream large models are all billed by token, and a single complex multi-agent task may trigger dozens of model calls.79% similarUnverifiedThe study observes that as task diversity increases, the model undergoes a transition from memorizing specific tasks to generalizing to new tasks.77% similarUnverified在Agent应用中，每一轮推理-行动-观察循环都需要将完整历史上下文重新输入模型，导致Token消耗随任务复杂度呈非线性增长76% similarUnverifiedThe high consumption triggered by the combination of Extra High reasoning and multi-tool agent tasks is expected behavior, not a system bug.76% similarUnverifiedEach step of the iterative loop consumes API call quota for the large model, and costs can accumulate quickly for complex tasks.76% similar
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