When is it worth fine-tuning your own model?

First we try the simpler route: a well-constructed prompt and connecting the model to your documents and data. Fine-tuning makes sense when you need stable output in a precisely defined structure or style, when the model has to understand your terminology, or when, with a large volume of queries, a smaller fine-tuned model is more economical to run than calling a large cloud model. We decide on the basis of measurement, not on a hunch.