PaddleOCR-VL: A Lightweight Multilingual Document Intelligence Solution for 109 Languages
As AI systems move beyond text, the efficient flow and structured processing of information have become central to enterprise digital transformation. The automated recognition and parsing capabilities of documents directly influence business efficiency and decision quality. However, traditional Optical Character Recognition (OCR) technology frequently encounters challenges in balancing accuracy and efficiency when confronted with real-world scenarios, including multiple languages, complex layouts, and low-quality images. This has created a demand for lighter, more powerful, and more easily deployable technological advancements.
Key Points
On December 4th, the Baidu PaddleOCR team participated in an AI Insight OCR special live broadcast. This event, co-initiated by Shanghai AI Lab OpenMMLab, Synapse, Hugging Face, ModelScope, and Zhihu, focused on discussing advancements and technical practices in document intelligence. The broadcast aimed to provide a comprehensive overview, ranging from general recognition to professional parsing, from single-language to global multilingual support, and from theoretical breakthroughs to practical application.
Under the Hood
Baidu Senior Engineer Sun Ting delivered a presentation titled "PaddleOCR-VL: A Lightweight Multimodal Document Parsing Solution Supporting 109 Languages." This presentation detailed PaddleOCR-VL, the latest development in document intelligence from PaddleOCR. The model, centered around PaddleOCR-VL-0.9B, integrates a dynamic resolution visual encoder and the ERNIE lightweight language model. This combination enables accurate recognition of complex elements such as text, tables, formulas, and charts with a minimal parameter count.
Notable Details
PaddleOCR-VL supports 109 languages and has demonstrated leading performance in various public and internal evaluations. From a structural standpoint, it exhibits strong inference speed and adaptability for deployment. The live broadcast also featured a round-table discussion with multiple developers, fostering an exchange of ideas and innovation.
What Comes Next
The event highlighted several capabilities, including 109-language support, lightweight deployment, and multi-element parsing. It also included comparisons with industry-leading models and shared practical deployment experiences. The round-table discussion explored various technical routes and the collaborative development of an open-source ecosystem.
For developers, PaddleOCR model experience is available on GitHub, Hugging Face, and ModelScope.