Vision LLMs Expand PDF Parsing to Charts, Diagrams, and...

OCR and layout cannot, by definition, because there were never any characters to read. It also parses text and tables, like the others The figure is the unique part, but a parser that only read pictures would be useless. A vision model reads the text and the tables too, and not worse than the textual engines on clean material.

We pointed parse_page_vision at page 30 of the NIST Cybersecurity Framework, the Framework Core table, and asked for markdown. It returned the table columns intact, merged cells handled (the Function name sits on the first row of its block and the continuation rows leave it blank). This is the same cell structure Docling and Azure produce from the same page in the two previous articles: they emit markdown tables too, so the format is not what sets vision apart.

The vision model never built a table object; it read the grid off the picture and wrote markdown (it returns HTML just as well). So the claim from the lead holds: it is a parser, returning the reusable model the others return, plus the figures they cannot. The model matters: gpt-4o-mini misses charts that gpt-4.1 reads How good the parse is depends heavily on the model, and the gap shows precisely where it counts, on the figures.