AI 产品的定价是一门玄学
50 英镑客单价，30 英镑 API 成本。用户越多，亏得越多。
这不是段子，是一家英国 AI 公司的真实账单。他们的定价模型和传统 SaaS 完全一样，按人头收月费，每用户每月 50 英镑。但 LLM 推理成本占了 60%，剩下的钱连服务器和客服都撑不住。
这就是 AI 产品定价最魔幻的地方：你用了最成熟的 SaaS 定价方法论，却得出了最不可持续的商业模式。
传统定价为什么失效了
传统 SaaS 有一个底层假设：边际成本趋近于零。多一个用户，多一台服务器，成本几毛钱，但收入几十块。毛利率能做到 70%-90%。
AI 产品把这个假设撕碎了。
LLM 推理成本和用户使用量正相关，而且相关性极强。不同用户之间的成本差异可以到 50 倍：轻度用户一个月消耗 20 万 Token，成本不到 2 毛钱；重度用户消耗 200 万 Token，用高端模型，单算推理成本就要 10 美元，占客单价的 50%。
这还不是最离谱的。Anthropic 公开承认，重度 Claude Code 用户每人每月亏损"数万美元"。GitHub Copilot 发布时，每个用户都在亏钱。OpenAI 2025 年烧掉 80 亿美元算力费用。
用户用得越爽，你亏得越快。 这是传统定价里不可能出现的悖论。
四种定价模式，各有各的坑
市面上能看到的 AI 定价模式，基本就四类：
| 模式 | 怎么收 | 致命问题 |
|---|---|---|
| 捆绑免费 | AI 功能塞进现有套餐 | 使用量暴涨，毛利率被悄悄吃掉，季度财报才发现出血 |
| 分层配额 | 每月给 Token 上限，超了停用 | 重度用户恰恰是口碑传播主力，触达上限就流失 |
| 计量超额 | 基础套餐包额度，超出按量付费 | 用户收到意外账单，直接炸了 |
| 按结果付费 | 按完成的结果收费 | 需要清晰可量化的结果定义，且防作弊 |
56% 的 AI 公司选择了混合模式，因为单独用哪一种都会在某个极端场景下崩掉。
没有完美的定价模式，只有和你的产品经济学匹配的定价模式。
选择前，先回答四个问题：
- 你的重度用户是谁，服务他们的真实成本是多少？ 按 P95 测算，不是中位数。P95 能赚钱，捆绑模式才安全。
- AI 的产出能不能被客户独立验证？ 能验证，按结果付费的大门就打开了。
- 你的用户使用方差大不大？ 方差小，套餐制没问题；方差大，必须有上限或计量机制。
- 推理成本下降有多快？ 如果每年降 50 倍，按 Token 收费等于把收入锚在下跌的价格上。
按结果付费：标杆案例和硬性前提
行业标杆是 Intercom Fin。每自动解决一张客服工单，收 0.99 美元。人类介入就不收。
为什么这个模式跑得通？因为激励对齐了。
Intercom Fin 用这个模式，两年内从 100 万美元 ARR 跑到超过 1 亿美元，毛利率 98%。
但按结果付费有三个硬性前提：
| 条件 | 什么意思 |
|---|---|
| 结果可定义 | "解决一张工单"有清晰标准，客户能独立确认 |
| 归因可追溯 | 能证明是 AI 做的，不是人工兜底 |
| 价值可量化 | 客户为此付的钱，远低于他省下来的人力成本 |
这三个条件不同时满足，按结果付费就变成了一笔糊涂账。
被低估的杠杆：模型路由
很多人把定价问题的解法想复杂了，其实有一个最简单粗暴的办法：不是所有问题都需要最贵的模型。
当前模型之间的成本差距：
| 模型 | 百万 Token 成本 | 倍数差 |
|---|---|---|
| DeepSeek V3 | 0.55 美元 | 1x |
| Claude Sonnet | 3 美元 | 5x |
| GPT-4o | 5 美元 | 9x |
| Claude Opus | 15 美元 | 27x |
实际操作中，把 80% 的请求路由到便宜模型，只把真正需要强推理的任务交给顶级模型，整体成本能降一个数量级。
这不需要改定价，改后台架构就行。但大多数团队第一步就选了最贵的模型，然后回头抱怨成本高。
三个实操建议
① 双指标追踪
对外跟用户说"额度"和"消息数"，用户不需要理解 Token。但内部必须追踪每用户的真实 Token 消耗和算力成本。
问题出现在损益表之前，你就能在运营数据里看到。
② 软上限先于硬上限
用户配额用到 80% 时通知，给对方选择升级的时间。直接用到 100% 突然降级，用户要么流失，要么找客服吵架。
Anthropic 的做法值得参考：限速只针对最密集的 5% 用户，保护中位数体验。
③ 定价锚定价值，不锚定成本
Token 成本两年下降了 280 倍，如果你按成本加成定价，价格就得跟着一直降。但客户感受到的价值并没有缩水 280 倍。
定价的上限不是你的成本，而是你为客户省下来的钱。 帮客服团队省了一个人的人力，收年费 5 万，客户觉得便宜。因为一个人力一年 15 万，你的产品是 1/3 的价格解决了同样的事。
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