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Baidu's Unlimited-OCR-2: 3B MIT-licensed model for parsing long multi-page PDFs

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Baidu has released Unlimited-OCR-2, a 3B-parameter OCR model under the MIT license, designed to handle long documents without the context overflow and repetition problems that affect many multi-page OCR systems. Version 2 introduces Sparse Reference Sliding Window Attention, which limits each decoder layer to a fixed set of working references, and an Unlimited-Horizon Decoding scheme that splits documents into overlapping chunks and reuses boundary-page KV caches. Baidu reports large memory and throughput gains on its MarathonDocBench, including a peak KV cache of 1.77 GB versus 47 GB under standard decoding at batch size 1. These speed figures compare attention variants rather than complete OCR pipelines, and the card lists no minimum VRAM requirement. The article also walks through local setup with Transformers, including pinned dependency versions and the trust_remote_code caveat, and notes that the author had not independently reproduced Baidu's numbers.

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