TL;DR: A practical benchmark of 14 OCR engines concludes that Gemini 3.1 Flash is the best all-rounder for mixed documents, highlighting OCR as a routing problem.
Summary: The author evaluated 14 OCR engines, including open-source tools and vision-language models, across 93 documents categorized by difficulty. The results showed Gemini 3.1 Flash is optimal for mixed production documents, Tesseract remains the best for high-volume clear prints, and Mistral OCR excels at cost-effective table extraction. The study concludes that document routing based on type, cost, and structure yields the best performance.
Why it matters: AI builders can optimize costs and accuracy by routing documents to specialized OCR engines instead of relying on a single provider. Developers should consider implementing a classifier to dynamically route documents to Gemini, Tesseract, or Mistral depending on layout complexity.
Source: bestblogs.dev
原文 (Original):
📌 One-Sentence Summary 本文对 14 个 OCR 引擎在 93 份难度各异的文档上进行了实际基准测试，结论是 OCR 是一个路由问题，没有单一的最佳引擎。 📝 Summary 作者通过动手实验，评估了 14 个不同的 OCR 引擎——从 Tesseract 等经典开源工具到现代专用模型和通用视觉语言模型——在 93 份多样化文档上的表现。这些文档涵盖了简单（清晰发票）、中等（