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A new open-source OCR model outperformed all major commercial tools on standard text and handwriting tests. It accurately transcribed a 1913 handwritten letter by Ramanujan, preserving layout, math notation, and faint ink details.
- New open-source OCR model (Vision Transformers + glyph-aware training) beat commercial tools like ABBYY and Google Cloud Vision on IFOCR, MLT, and ICDAR benchmarks, with word-error-rates below 1.5%—30-50% better than competitors
- Successfully transcribed a faded 1913 handwritten Ramanujan letter, correctly capturing layout, math notation, and faint ink strokes
- Trained on millions of scanned pages including medieval manuscripts and dense handwritten notes
- Released under Apache license with CPU/GPU deployment scripts, enabling free text extraction from receipts, legal documents, and historical archives without per-page fees