Vision LLMs are PDF Parsers Too: Reading Charts and Diagrams for RAG

Vision Large Language Models can function as effective PDF parsers, particularly for content that traditional text-based methods cannot process. By treating a page as an image, these models can interpret charts, diagrams, and other visuals, generating searchable text descriptions for use in Retrieval-Augmented Generation (RAG) systems. This capability makes previously unsearchable visual content discoverable. However, this method is slower, more expensive, and its accuracy depends heavily on the specific vision model used, with more powerful models yielding significantly better results on complex images. Therefore, it is best used selectively for visually dense pages where standard parsers fail, rather than as a complete replacement.