LLM-Based Manuscript Paper OCR Performance Comparison: Verification of Vertical Japanese Recognition Accuracy
Introduction In this article, we compared and verified the OCR performance of major LLM models using actual manuscript paper images. While many OCR benchmarks target printed documents and horizontally written text, we evaluate recognition accuracy on the special format of Japanese vertical manuscript paper to more practically verify each model’s Japanese document understanding capabilities. Features of This Verification Using the uniquely Japanese manuscript paper format: Verification with images containing complex elements such as characters placed in grid cells, vertical writing layout, and distinctive margin composition Assuming practical use cases: Performance evaluation on manuscript paper used in actual writing scenarios such as essays, novels, and academic papers Comprehensive comparison of the latest models: Comparison of the latest models – GPT-5, GPT-4.1, Gemini 2.5 Pro, Claude Opus 4.1, and Claude Sonnet 4 – under identical conditions Verification Overview Image Used Image source: Canva template (400-character manuscript paper) URL: https://www.canva.com/ja_jp/templates/EAFbqUoH7P8/ Image characteristics: 20x20 grid, 400-character manuscript paper Vertical writing layout Faint grid lines (cells) Distinction between title area and body area ...
