Practical RAG vs. Fine-Tuning: When to Use Each for LLM Apps
As the field of large language models (LLMs) matures, developers building intelligent applications are increasingly faced with a strategic choice: Should they use retrieval-augmented generation (RAG) or fine-tuning to enhance a model’s accuracy and relevance? Both techniques aim to optimize LLM performance, but they differ significantly in terms of complexity, cost, data requirements, and use-case…







