The debate between fine-tuning and Retrieval-Augmented Generation continues to evolve as enterprise adoption accelerates.
When Fine-Tuning Wins
Fine-tuning excels when you need consistent output formatting, domain-specific terminology, or when your knowledge base is relatively static.
When RAG Wins
RAG shines with frequently updated knowledge bases, when you need source attribution, or when operating under strict data governance requirements.