OvisOCR2: A 0.8B End-to-End Document Parsing Model Achieves SOTA on OmniDocBench

Jul 16, 2026

OvisOCR2 is a 0.8B parameter end-to-end document parsing model that converts document page images into Markdown in natural reading order, handling text, formulas, tables, and visual regions. It achieves state-of-the-art scores of 96.58 on OmniDocBench v1.6 and 75.06 on PureDocBench, surpassing previous pipeline-based methods. The model's training involves a data engine combining real and synthetic data, reinforcement learning, and model fusion.

Why it matters: This result shows that compact end-to-end models can outperform complex pipeline methods in document parsing, potentially simplifying deployment and improving accuracy for document understanding tasks.

Full story at: arXiv Computer Vision ↗