Fine-tuning costs more than RAG, where the model looks up information for each question instead. The tuned model also needs maintenance over time. Still, fine-tuning is valuable when fast responses (low latency), an exact format or a fixed tone is decisive.
Our standpoint
We only choose fine-tuning when RAG isn't enough or when we have to run on a smaller, faster model.