Unverified50% confidenceFactExact time
Because the amount of computation per token is limited, the model needs to distribute reasoning across multiple tokens, which is Chain of Thought.
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50%
Confidence
Long-term
Relevance
9/25/2026
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Related Claims
VerifiedTop-tier models employ techniques such as chain-of-thought or extended reasoning, generating a large number of intermediate tokens during inference, causing per-call token consumption to be several times that of ordinary models.79% similarUnverified推理模型在生成最终答案前会先产生大量内部思维链（Chain-of-Thought）token，这些 token 不直接暴露给用户76% similarUnverifiedReasoning mode performs internal chain-of-thought reasoning before the final answer, and the thinking tokens generated are billed; in complex programming tasks, thinking tokens may account for 60%–70% of total consumption, and costs may be 3–5 times that of normal mode.76% similarUnverifiedFull chain-of-thought reasoning requires generating a large number of tokens, which is extremely demanding on computing resources.74% similarVerifiedIn prompt engineering, few-shot examples guide output format by providing 2–5 examples, while Chain-of-Thought requires the model to "think step by step" to activate reasoning capability.74% similar
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