GOT-OCR 2.0

by StepFun

Open SourceSelf-HostedApache-2.0

General OCR Theory model with end-to-end OCR capabilities for diverse document types

OCRLayout AnalysisTable Extraction
🤗 Hugging FaceGitHub

Overview

GOT-OCR 2.0 (General OCR Theory) is a unified OCR model from StepFun that handles text recognition across various document types including plain text, formatted documents, tables, and mathematical formulas.

Unlike traditional OCR that requires separate models for different document elements, GOT-OCR uses a single end-to-end architecture. It excels at understanding document structure while extracting text, making it particularly effective for complex layouts.

The model supports multiple output formats and can handle both printed and handwritten text, positioning it as a versatile alternative to pipeline-based approaches.

Strengths

  • Unified model for diverse document types
  • Strong on tables and formatted content
  • Handles mathematical formulas
  • End-to-end architecture without pipeline complexity
  • Active community and ongoing development

Limitations

  • Requires GPU for inference
  • Larger model size than specialized OCR
  • May be overkill for simple text extraction

Best Use Cases

  • Academic paper digitization
  • Technical document processing
  • Form and table extraction
  • Mixed-content document understanding