> If the latter, assuming the cost of fine-tuning is a fraction of the cost of training from scratch, the low cost of inference does indeed make a bullish case for these companies.

On the other hand, this may also turn into cost effective methods such as model distillation and spot training of large companies (similarly to Deepseek). This would erode the comparative advantage of Anthropic and OpenAI, and result in a pure value-add play for integration with data sources and features such as SSO.

It isn't clear to me that a slowing of retraining will result in advantages to incumbents if model quality cannot be readily distinguished by end-users.