Unlimited-OCR: One-Step Page Parsing with Context Preservation

Standard library and technical documentation digitization methods require page-by-page processing, making work with large archives unpredictable in terms of time and resources. The Unlimited-OCR model changes this approach by offering one-step parsing of multiple pages simultaneously.

The solution architecture includes the DeepEncoder visual encoder, which compresses images to 256 tokens. The R-SWA mechanism keeps the KV-cache within fixed boundaries, ensuring contextual linkage between pages.

The model maintains linear inference speed from the first to the last word, eliminating delays caused by stitching results. This improves the efficiency of processing large data volumes without compromising recognition quality.

Model testing is available for free via the immers.cloud service to verify performance on specific OCR tasks. For industrial use, a private instance can be deployed on a GPU server.

Unlimited-OCR cloud deployment operates on a per-second billing model for server resource usage. This approach helps optimize costs when integrating the system into workflow processes.