定制AI模型如何影响你应用的退出估值
收购方为防御性付费。在专有数据上训练的微调模型是增加收购倍数的硬资产。以下是在退出背景下如何思考模型所有权。
Micro-SaaS应用估值通常从标准SaaS的2-4倍ARR到拥有可防御护城河的4-8倍ARR。2倍和6倍ARR之间的差异通常是一件事：别人复制你构建的东西有多容易？
在专有用户数据上训练的微调模型不容易复制。这在退出时值钱。
API依赖惩罚： 纯GPT-4包装应用被打折因为收购方知道OpenAI可以添加相同功能。预期倍数：2-3倍ARR。
专有模型溢价： 拥有在专有数据上训练的微调模型的应用是不同的。数据无法在没有模型的情况下复制。模型无法在没有数据的情况下复制。预期倍数：4-8倍ARR。
示例计算：
- 应用A：GPT-4包装，$50,000 ARR → 估值$100,000-150,000
- 应用B：微调模型+18个月专有数据，$50,000 ARR → 估值$250,000-400,000
相同收入。2-3倍的退出价值差异。
从第一天为退出构建
- 记录数据集
- 版本化模型——展示准确率随版本提升
- 量化护城河——"竞争对手需要18-24个月从头复制此数据集"
- 突出切换成本
出售时包含什么
GGUF模型文件、训练数据集、Ertas项目（含完整训练历史）、Ollama部署配置、数据收集管道、准确率基准。
Ship AI that runs on your users' devices.
Ertas early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
延伸阅读
- The Vibecoder's Guide to Building an AI Moat — 完整护城河策略
- Bootstrap AI SaaS Without API Costs — 本地推理经济学
Ship AI that runs on your users' devices.
Early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
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