GOT-OCR2.0

GOT-OCR2.0 (General OCR Theory) is a unified end-to-end OCR model developed by Haoran Wei and collaborators and released under the StepFun org in September 2024. It pushes OCR toward a '2.0' paradigm: a single vision-language model that handles text recognition across documents, scenes, and structured layouts without the traditional detection-then-recognition pipeline. The release was a community hit — it reached #1 on Hugging Face trending on September 19, 2024, passed 1 million downloads by December 2024, and spawned ONNX, MNN, llama.cpp, and PaddleMIX ports plus fine-tuning support via ms-swift, with Hugging Face transformers integration merged in February 2025.

Limitations: as a research-origin model, production robustness on unusual scripts, dense layouts, or low-quality scans should be validated against your own data; the original authors' evaluation skews toward standard benchmarks. Confirm the current license on the Hugging Face model card (stepfun-ai/GOT-OCR2_0) before commercial use, since community ports may carry different terms. For very high-accuracy document pipelines it is worth comparing against newer dedicated document models.