OvisOCR3 has landed: a unified 0.8B model that turns document images into structured, usable data across five OCR and document-understanding tasks.
🤖 https://modelscope.ai/models/ATH-MaaS/OvisOCR3
🏆 SOTA at its size across five document tasks: In the team’s reported comparisons, OvisOCR3 leads comparable-size models across document parsing, general OCR, key information extraction, figure captioning, and cross-page table reconstruction.
📄 Parse documents into usable formats: Generate structured JSON, layout JSON, or Markdown with LaTeX formulas and HTML tables from a page image.
🔎 Go beyond reading text: Extract specified fields into a JSON schema, answer image-grounded questions, recover chart data, or return text locations as bounding boxes.
🖼️ Understand visuals inside documents: Add localized captions for figures and create Mermaid representations for flowcharts as part of the parsed page content.
📊 Reconnect tables across pages: Use consecutive page images and parsed Markdown to rebuild a complete HTML table, with source-page associations retained.
🛠️ One compact checkpoint, prompt-selected tasks: Switch capabilities through task prompts instead of deploying a separate model for each OCR or document-processing workflow.
📜 Apache-2.0 License.