Unverified50% confidenceFactExact time
The reasoning process of large models is billed based on the number of tokens consumed, with one token roughly equivalent to 3/4 of an English word
1
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50%
Confidence
Long-term
Relevance
9/3/2026
First Seen
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Related Claims
UnverifiedWhen generating each token, large language models perform probabilistic sampling over all possible next words in the vocabulary, rather than deterministically selecting a unique answer.74% similarUnverifiedThe inference cost of large language models is variable and usage-based; a single Agent handling a complex task may trigger dozens of model calls and consume millions of tokens.71% similarUnverified带有Chain-of-Thought推理功能的Thinking模型，由于需要生成大量中间推理token，其实际token消耗量可能是普通对话的5-20倍70% similarUnverifiedThere is a positive correlation between the reasoning ability of large language models and the length of the token sequences they output, which academia refers to as the "computational depth hypothesis."70% similarVerifiedThe essence of large language models is learning the conditional probability distribution of what the next word is given the preceding text70% similar
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