deepseek-ai/deepseek-ocr is an open-source model repository that reads characters and structure information out of document images. The README explains inference methods using vLLM and Transformers, along with examples of recognizing text in images and converting documents to Markdown, and PDF processing code. The repository was created on October 17, 2025, and there is no public release with a version listed.
It is a model that studies document images and optical compression. The README states that the model explores the boundaries of visual text compression and studies the role of the vision encoder from a large-language-model-centric perspective. The center of this repository is model inference that extracts text and structure information from visual documents, and the examples are divided into text recognition, Markdown conversion, and PDF processing. The implementation language is Python, the license is MIT, and the GitHub stars number 24028.
That said, no performance figures or evaluation scores are given for this repository. The scope of the README extends only to inference methods and example code, so unless you run the code yourself, there is no way to know what level of accuracy it reaches or how faithfully the structure is carried over. There are also no performance criteria for comparison with other tools in this material. With no versioned release either, it is hard to decide which state to treat as the baseline. Based on this material alone, it is difficult to conclude that it can be applied directly to work where precision matters.