When should you use RAG instead of fine-tuning?

Use RAG when knowledge changes frequently, when you need to cite sources, when your data is too large to fit in model weights, or when you need to control which information the model uses. Use fine-tuning when you need consistent output style, domain-specific reasoning patterns, or when you want a smaller model to replicate a larger one. Many production systems combine both.