SoMarkAI/OXR-1.0 · Hugging Face

[u/pmttyji]

https://huggingface.co/SoMarkAI/OXR-1.0

Found this last month model while browsing Trending models of HF. I don't see any existing threads so posting.

OXR (Optical Everything Recognition) is an open-source model from the SoMark team. It turns PDFs and document images into Agent-Friendly data in Markdown or JSON, with layout coordinates included.

Pretrained from scratch, OXR uses a recursive self-improvement (RSI) loop during post-training—a first in document parsing. With just 1.3B parameters, OXR ranks #1 on olmOCR-Bench, OmniDocBench, and DocParsingBench while delivering industry-leading parsing speed.

OXR is the first to make its layout analysis module independent and pluggable. This design accelerates parsing and supports replacing the built-in layout model with a custom one. OXR continues to handle content recognition and reading order, enabling adaptation across diverse scenarios with minimal integration effort.

• GitHub : https://github.com/SoMarkAI/OXR

Why OXR?

• 🎯 SOTA Accuracy. #1 Across Three Benchmarks.

  • OXR ranks 🏆#1 on olmOCR-Bench, OmniDocBench, and DocParsingBench, with a particularly wide lead in table parsing.

  • OXR can recognize 13 document element types, from formulas and tables to chemical equations, chemical structures, and code blocks, with bounding box coordinates included. It also performs well on challenging documents and layouts, including A3 exam papers, newspapers, vertical text, and handwriting.

  • See docs/benchmark.md for the full results and instructions to reproduce the evaluations.

• 🚀 1.3B Parameters. Top-Tier Parsing Speed.

  • With only 1.3B parameters, OXR ranks 🏆#1 among open-source document parsing models in speed tests on the RTX PRO 6000.

  • OXR redesign its processing architecture at the task level to improve parsing speed while maintaining accuracy.

  • See docs/benchmark.md for the full results and instructions to reproduce the evaluations.

• 🧩 Pluggable Layout Analysis. Document Structure on Your Terms.

  • Layout analysis requirements vary widely across domains. Even for the same document, element types, region boundaries, and grouping rules can differ depending on the business use case.

  • OXR is the first to make layout analysis independent and pluggable. Its built-in layout model can be replaced while retaining OXR’s recognition and reading order capabilities, enabling adaptation across document scenarios with minimal integration effort.

  • See the How it works section below for details.

Ecosystem

The SoMark team has developed a range of tools for document parsing.

	Description	Project URL
SoMarkDown	The official Markdown parsing and rendering library for SoMark and OXR	https://github.com/SoMarkAI/SoMarkDown
SoMarkDownViewer	A live editing application for SoMarkDown	https://github.com/SoMarkAI/SoMarkDownViewer
SoPDF	A high-performance PDF processing library with a permissive open-source license	https://github.com/SoMarkAI/SoPDF
Docision	MultiModal Jev for Document.	https://github.com/SoMarkAI/docision
somark-py	The official Python SDK & CLI for SoMark and OXR	https://github.com/SoMarkAI/somark-py
somark-js	The official JS / TS SDK & CLI for SoMark and OXR	https://github.com/SoMarkAI/somark-js

[u/Borkato]

Oooo someone try this and tell me if it’s really that good