If you've ever tried to OCR handwritten notes or math equations from a screenshot, you know the standard tools (Google Vision, Tesseract, AWS Textract) all hit a wall once you leave printed Latin text.

I spent some time benchmarking what's out there in 2026. Here's what's actually working.

What breaks in generic OCR

Handwriting — especially cursive in non-Latin scripts. Most OCRs were trained on printed text and treat ligatures as noise.

Math equations — generic OCR returns "x2 + y2 = 1" instead of x² + y² = 1 or LaTeX.

Tables — column structure flattens into a paragraph; you lose the relationships.

CJK — character recognition is OK; vertical-text and traditional-character handling are not.

Tools I tried

ScanRead.ai — free OCR for the gap cases

Built on PP-OCRv5 + PaddleOCR-VL (~2M params). Has a dedicated Math → LaTeX path that actually preserves multi-line derivations when there's clear bracketing, and CJK accuracy that's competitive with Vision/Textract on my test set.…