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Optical character recognition, text extraction from images and scans. Ranked by quality, cost, and real-world performance.
5 models compared · Data powered by Artificial Analysis
Ranked comparison of 5 AI models for ocr tasks. Gemini 3.5 Flash leads on quality (score 50), while Gemini 3.5 Flash provides the most affordable entry point.
OCR (optical character recognition) requires vision-capable models that can extract text from images, scans, photos, and handwritten documents. Not every vision model handles OCR well; accuracy varies widely by font, language, and image quality.
For production OCR workflows, Google's Gemini models tend to excel due to their multimodal training on diverse document types. Premium models handle complex layouts (multi-column, tables, forms) better than budget alternatives.
If you're processing high volumes, consider Gemini 3 Flash for its combination of vision capability, speed (160 tok/s), and low cost ($0.075/$0.30 per 1M tokens). For free OCR, Qwen 2.5 VL handles basic text extraction.
| # | Model | Tier | Quality | Price (In/Out) | Est. Cost (100/mo) |
|---|---|---|---|---|---|
| 1 | Gemini 3.5 Flash Google | Budget | 50 | $1.50 / $9.00 | $2.25 |
| 2 | Gemini 3.1 Pro Google | Frontier | 47 | $2.50 / $15.00 | $3.75 |
| 3 | Gemini 3 Flash Google | Budget | 46 | $0.07 / $0.30 | $0.08 |
| 4 | Gemini 3 Pro Google | Premium | 40 | $2.00 / $12.00 | $3.00 |
| 5 | Qwen 2.5 VL 72B (Free) Alibaba | Free | 15 | Free / Free | Free |
Vision models ranked by cost and accuracy, with use-case recommendations