China Telecom's TeleOCR Tops Global Document Parsing Benchmarks

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China Telecom Artificial Intelligence Technology Co., Ltd. announced that TeleOCR, its self-developed document parsing model, has set a new state-of-the-art result on OmniDocBench v1.6 with an overall score of 96.87 out of 100. The model, open-sourced by China Telecom's Xingchen AGI Lab with roughly 1.2 billion parameters, also ranked first on two other benchmarks and took first place in the ICDAR 2026 Sci-ImageMiner Challenge for scientific figure understanding. On Wild-OmniDocBench v1.5 it scored 88.53 on camera-captured documents, about one point ahead of the runner-up, while on PureDocBench it averaged 78.41 across three tracks, including a four-point lead on the most challenging real degradation track. TeleOCR outperformed larger specialized models including MinerU 2.5-Pro and PaddleOCR-VL-1.6 as well as general-purpose models such as Gemini 3 Pro and GPT-5.2, with its code and weights open-sourced on GitHub and Hugging Face and a production-ready API available on China Telecom's Tianyi AI Open Platform. The research team said the next phase will focus on integration into enterprise scenarios including financial document processing, medical record digitization, academic research workflows and government archives.

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China Telecom's TeleOCR document parsing model sets state-of-the-art benchmark results and is open-sourced with a production API

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China Telecom AI subsidiary's TeleOCR tops global document parsing benchmarks and plans enterprise integration

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