RolmOCR by Reducto AI Earlier this year, the Allen Institute for AI released olmOCR, an open source tool that performs document OCR using the Qwen2 VL 7B vision language model (VLM). We were excited to see a high quality, openly available approach to parsing PDFs and other complex documents — and curious to explore what else might be possible using newer foundation models and some lightweight optimizations. The result is RolmOCR , a drop in alternative to olmOCR that’s faster, uses less memory, and still performs well on a variety of document types. We're releasing it under Apache 2.0 for anyone to try out, explore, or build on. This model is a fine tuned version of Qwen/Qwen2.5 VL 7B Instruct on the full allenai/olmOCR mix 0225 dataset. Key changes We made three notable changes: 1. New Base Model : We swapped in a more recent version of the existing model (Qwen2.5 VL 7B) as the foundation. 2. No Metadata inputs : Unlike the original, we don’t use metadata extracted from PDFs. This significantly reduces prompt length, which in turn lowers both processing time and VRAM usage — without hurting accuracy in most cases. 3. Rotation of training data: About 15% of the training data was ro…
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