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MonkeyOCRv2-B-Parsing

zenosai

* `2026.09.07` 🚀 MonkeyOCRv2-Parsing is now supported by RAGFlow as a PDF parser. Thanks to the RAGFlow team and community for the support! * `2026.08.22` 🖥️ We now support running MonkeyOCRv2-Parsing on CPU. See the CPU support instructions. * `2026.08.17` ⚡ Releasing training and evaluation instructions for Recognition, Detection, Overlapping Text Segmentation and Formula. * `2026.07.24` ⚡ We released MonkeyOCRv2-B-Parsing-DFlash, enabling vLLM serving with DFlash for up to 2× faster inference. * `2026.07.22` 🏆 MonkeyOCRv2-B-Parsing ranks #1 among evaluated open-source models on the official MDPBench Leaderboard, achieving 83.3 overall across 17 languages, including digital-born and photographed documents. * `2026.07.21` 📦 We release MonkeyDoc v2, an open multilingual corpus for document-oriented pretraining. We hope it can serve as a shared data foundation for more transparent, reproducible, and fair comparisons in Document AI. * `2026.07.14` 🚀 We release MonkeyOCRv2, including MonkeyOCRv2 vision encoder, MonkeyOCRv2-Parsing for multilingual document parsing, MonkeyOCRv2-Und for efficient document understanding. MonkeyOCRv2 is released as a standalone, document-native vision encoder. It can be integrated into different OCR and document AI systems as a visual backbone. The current release has been evaluated on document parsing, document understanding, text recognition, formula recognition, text detection, document tampering detection, and overlapping-text segmentation.

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MonkeyOCRv2-B-Parsing

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