Baidu open-sources its Unlimited OCR 2 document parsing model
Baidu released Unlimited OCR 2 on Hugging Face and GitHub on Oct 27 under the MIT license (about 3.3B parameters). Its Sparse Reference Sliding Window Attention (SR-SWA) compresses attention over very long sequences into a fixed set of references (e.g. 512 tokens), so per-step latency and memory stay nearly flat as documents grow. Baidu claims SOTA on dozens- and hundred-page parsing benchmarks.
Why it matters
Long-document parsing feeds RAG and agent pipelines; this one is open weights, runs locally, and keeps memory flat as page counts grow.
Sources2
Hugging Face · baiduMediabaidu/Unlimited-OCR-2 · Hugging FaceView original
- @Baidu_IncXUnlimited OCR 2 is here, and it's open source. 📖 ✨ Longer documents can mean a lot more attention computation. Our new SR-SWA mechanism keeps that in check by condensing text-visual attention interactions into a fixed-size set of working references. Here's what it delivers: - Document parsing at virtually any length, within a finite context window - Nearly constant per-step decoding latency and memory footprint as documents grow longer - State-of-the-art performance on MPDocBench and MarathonDocBench, covering documents from dozens to hundreds of pages Check out the model here ↓View original
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