Unverified60% confidenceFactTime unknown
大语言模型每次调用的费用与输入token数量正相关，在Agent循环中随着对话历史积累每次调用成本会线性增长
2
Sources
60%
Confidence
Long-term
Relevance
5/31/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe 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.82% similarUnverifiedEach model response includes the full conversation history (context window) in billing, and as the number of dialogue turns increases, the token consumption per call grows linearly or even super-linearly.79% similarUnverifiedThe cost structure of large language models includes a massive one-time investment during the training phase and ongoing operational costs during the inference phase.78% similarUnverifiedThe total inference cost of large models exceeds the training cost, because inference continues to occur and grows linearly with user scale.74% similarUnverified大型语言模型的推理成本与参数规模并非线性关系，参数量从千亿级跃升至万亿级时推理所需的GPU显存、带宽和计算量会指数级攀升72% similar
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