Altman 的坦白戳中了所有用 AI 做产品的团队痛点——智能体看似高效，但 token 消耗可能让预算失控。做 AI 应用或部署智能体的开发者，建议算一笔账再上线。
OpenAI 的 Sam Altman 表示，AI 预算正变成“巨大问题”，外部客户每月消耗的 token 数量高达 6030 亿，远超 OpenAI 内部顶级用户的 1000 亿。问题在 AI 智能体上更严重，因为它们会多次规划、调用工具、读取文件、重试失败步骤和验证结果，导致 token 消耗激增。这引发了企业从“AI 是否令人印象深刻”到“边际 token 是否产生边际价值”的转变。杰文斯悖论解释了部分原因：当每 token 成本下降时，使用量反而大幅上升，总账单可能不降反升。
Sam Altman admits AI budgets are turning into a “h…
Sam Altman admits AI budgets are turning into a “huge issue,” with customers burning more tokens than even OpenAI’s top in-house users.
Altman said OpenAI’s top internal user spends about 100B tokens/month, while one outside customer hit 603B tokens/month.
The cost problem gets worse with AI agents because they do not just answer once, they plan, call tools, read files, retry failed steps, check their own work, and create long chains of hidden token spending. Every plan, retry, code review, context window, tool call, and verification step becomes metered cognition.
A human asks once; an agent may ask hundreds of times in a second.
Companies are no longer asking whether AI is impressive, but whether the marginal token is producing marginal value.
Jevons paradox explains part of the trap: when AI gets cheaper per token, people use far more tokens, so the total bill can still rise.