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-**PaddleOCR-VL - Multilingual Document Parsing via a 0.9B VLM**
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**The SOTA and resource-efficient model tailored for document parsing**, that supports 109 languages and excels in recognizing complex elements (e.g., text, tables, formulas, and charts), while maintaining minimal resource consumption.
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-**PaddleOCR-VL-1.5** is a new iterative version of the PaddleOCR-VL series. Based on comprehensive optimization of the core capabilities of version 1.0, **the model achieves 94.5% accuracy on the authoritative document parsing benchmark OmniDocBench v1.5**, surpassing top global general-purpose large models and document parsing–specific models.
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PaddleOCR-VL-1.5 innovatively supports irregular-shaped bounding box localization of document elements, enabling excellent performance in real-world application scenarios such as scanning, skew, warping, screen-photography, and complex illumination, achieving comprehensive SOTA performance. In addition, the model further integrates seal recognition and spotting tasks, with key metrics continuing to lead mainstream models.
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You can use it online on the [PaddleOCR official website](https://www.paddleocr.com) or call the model API.
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<details>
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<summary><strong>2025.10.16: Release of PaddleOCR 3.3.0</strong></summary>
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- Released PaddleOCR-VL:
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-**Model Introduction**:
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- Released PP-OCRv5 Multilingual Recognition Model:
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- Improved the accuracy and coverage of Latin script recognition; added support for Cyrillic, Arabic, Devanagari, Telugu, Tamil, and other language systems, covering recognition of 109 languages. The model has only 2M parameters, and the accuracy of some models has increased by over 40% compared to the previous generation.
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<summary><strong>2025.08.21: Release of PaddleOCR 3.2.0</strong></summary>
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Since its initial release, PaddleOCR has gained widespread acclaim across academia, industry, and research communities, thanks to its cutting-edge algorithms and proven performance in real-world applications. It’s already powering popular open-source projects like Umi-OCR, OmniParser, MinerU, and RAGFlow, making it the go-to OCR toolkit for developers worldwide.
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On May 20, 2025, the PaddlePaddle team unveiled PaddleOCR 3.0, fully compatible with the official release of the [PaddlePaddle 3.0](https://github.com/PaddlePaddle/Paddle) framework. This update further **boosts text-recognition accuracy**, adds support for **multiple text-type recognition** and **handwriting recognition**, and meets the growing demand from large-model applications for **high-precision parsing of complex documents**. When combined with the **ERNIE 4.5**, it significantly enhances key-information extraction accuracy. PaddleOCR 3.0 also introduces support for domestic hardware platforms such as **KUNLUNXIN** and **Ascend**.
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**On January 29, 2026, PaddleOCR open-sourced the advanced and efficient document parsing model PaddleOCR-VL-1.5.** PaddleOCR-VL-1.5 is a new iterative version of the PaddleOCR-VL series. Based on comprehensive optimization of the core capabilities of version 1.0, **the model achieves 94.5% accuracy on the authoritative document parsing benchmark OmniDocBench v1.5**, surpassing top global general-purpose large models and document parsing–specific models.
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PaddleOCR-VL-1.5 innovatively supports irregular-shaped bounding box localization of document elements, enabling excellent performance in real-world application scenarios such as scanning, skew, warping, screen-photography, and complex illumination, achieving comprehensive SOTA performance. In addition, the model further integrates seal recognition and spotting tasks, with key metrics continuing to lead mainstream models.
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You can use it online on the [PaddleOCR official website](https://www.paddleocr.com) or call the model API.
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