cis-lmu/GlotOCR-bench-v1.0-results

GlotOCR Bench Results

This dataset contains OCR results from images in cis-lmu/GlotOCR-bench using multiple multilingual OCR models.

Quick links:

• 📃 Paper
• 🛠️ Code
• 📈 Benchmark

Download

git clone https://huggingface.co/datasets/cis-lmu/GlotOCR-bench-v1.0-results

• If you want to clone without large files - just their pointers:

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/cis-lmu/GlotOCR-bench-v1.0-results

Processing Details

• Source Dataset: cis-lmu/GlotOCR-bench
• Number of Samples: 16,375

Configuration

• Image Column: img_plain
• Output Column: markdown
• Dataset Split: test

Models Information

• rednote-hilab/dots.ocr
• rednote-hilab/dots.mocr
• zai-org/GLM-OCR
• deepseek-ai/DeepSeek-OCR-2
• allenai/olmOCR-2-7B-1025
• nanonets/Nanonets-OCR2-3B
• FireRedTeam/FireRed-OCR
• lightonai/LightOnOCR-2-1B
• reducto/RolmOCR
• tencent/HunyuanOCR
• Qwen/Qwen3-VL-8B-Instruct
• GPT-4.1
• Gemini 3.1 Flash-Lite (Disabled thinking)
• PaddlePaddle/PaddleOCR-VL-1.5

Dataset Structure

The dataset contains all original columns plus:

• markdown: The extracted text in markdown format
• inference_info: JSON list tracking all OCR models applied to this dataset

Reproduction

This dataset was generated using the uv-scripts/ocr

Citation

@misc{kargaran2026glotocrbench,
      title={GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts}, 
      author={Amir Hossein Kargaran and Nafiseh Nikeghbal and Jana Diesner and François Yvon and Hinrich Schütze},
      year={2026},
      eprint={2604.12978},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2604.12978}, 
}