Verified65% confidenceFactExact time
Top-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.
3
Sources
65%
Confidence
Long-term
Relevance
7/21/2026
First Seen
Sources
Related Claims
UnverifiedBecause the amount of computation per token is limited, the model needs to distribute reasoning across multiple tokens, which is Chain of Thought.79% similarUnverifiedFull chain-of-thought reasoning requires generating a large number of tokens, which is extremely demanding on computing resources.78% similarUnverifiedLarge models are billed by the number of input plus output Tokens for each inference.78% similarUnverifiedThe MAX level essentially extends the model's chain of thought within a single inference, allowing the model to perform more internal iterations before output, rather than invoking more parallel resources.77% similarUnverifiedA reasoning trace is the sequence of intermediate thinking tokens that a large language model outputs step by step before generating a final answer; it improves accuracy on complex tasks but consumes a large number of additional tokens.77% similar
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