Sep 8, 2025
LLM Fine-Tuning vs. RAG: Choosing the Right Path for Your Enterprise App
Struggling to choose between RAG and fine-tuning for your LLM? This guide breaks down the pros, cons, and costs to help you decide.
Choosing the right customization method is critical for LLM success. Retrieval-Augmented Generation (RAG) is ideal for apps needing real-time, factual data from specific documents, offering lower costs and faster implementation. Fine-tuning is powerful for teaching an LLM a specific style, tone, or niche knowledge not found in its base training. We explore the key decision factors: data requirements, update frequency, and budget constraints to help you build a smarter, more efficient AI-powered application that delivers tangible business results.