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990 points pierre | 1 comments | 20 Oct 25 06:26 UTC | HN request time: 0.207s | source

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pietz ◴[20 Oct 25 08:49 UTC] No.45641449[source]▶

My impression is that OCR is basically solved at this point.

The OmniAI benchmark that's also referenced here wasn't updated with new models since February 2025. I assume that's because general purpose LLMs have gotten better at OCR than their own OCR product.

I've been able to solve a broad range of OCR tasks by simply sending each page as an image to Gemini 2.5 Flash Lite and asking it nicely to extract the content in Markdown under some additional formatting instructions. That will cost you around $0.20 for 1000 pages in batch mode and the results have been great.

I'd be interested to hear where OCR still struggles today.

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1. constantinum ◴[20 Oct 25 14:37 UTC] No.45644404[source]▶

>>45641449 #

Why PDF parsing is Hell[1]:

Fixed layout and lack of semantic structure in PDFs.

Non-linear text flow due to columns, sidebars, or images.

Position-based text without contextual or relational markers.

Absence of standard structure tags (like in HTML).

Scanned or image-based PDFs requiring OCR.

Preprocessing needs for scanned PDFs (noise, rotation, skew).

Extracting tables from unstructured or visually complex layouts.

Multi-column and fancy layouts breaking semantic text order.

Background images and watermarks interfering with text extraction.

Handwritten text recognition challenges.

[1] https://unstract.com/blog/pdf-hell-and-practical-rag-applica...

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