MinerU2.5
1.2B-param VLM that converts any document to clean structured text
The Panel's Take
MinerU2.5 is a 1.2-billion parameter vision-language model purpose-built for high-resolution document parsing. From OpenDataLab, it's the latest version of a project that's accumulated 61.5K GitHub stars — which tells you something about how painful document-to-text has been as a category. The model uses a decoupled vision-language architecture for efficient high-resolution processing with state-of-the-art recognition accuracy across tables, formulas, figures, and mixed-layout documents. The core use case is turning messy PDFs, scanned forms, academic papers, and enterprise documents into clean Markdown or structured JSON that LLMs can actually work with. Earlier MinerU versions were already widely adopted for RAG pipeline preprocessing — 2.5 tightens up accuracy on the edge cases that killed earlier tools: rotated pages, dense tables, multi-column layouts, and multilingual content. At 1.2B parameters it's lightweight enough to run locally without a GPU farm, and the Apache 2.0 license means it integrates cleanly into commercial document pipelines. For anyone building RAG applications, AI research assistants, or document intelligence products, this is the preprocessing layer that removes a persistent pain point.
Share this verdict
MinerU2.5 verdict: SHIP 🚀 3 ships · 1 skip from the expert panel Full review: shiporskip.io/tool/mineru25-document-parsing-vlm-opendatalab-2026
Weekly AI Tool Verdicts
Get the next verdict in your inbox
7 critics review a new AI tool every day. Weekly digest — free.
Compare MinerU2.5 with Others
Embed this verdict
Tool makers can add a live ShipOrSkip badge to their site. Badge loads track impressions; clicks route back to this review.
<a href="https://shiporskip.io/api/badge-click/mineru25-document-parsing-vlm-opendatalab-2026" target="_blank" rel="noopener"><img src="https://shiporskip.io/api/badge/mineru25-document-parsing-vlm-opendatalab-2026" alt="MinerU2.5 Ship verdict on ShipOrSkip" width="360" height="90" /></a>[](https://shiporskip.io/api/badge-click/mineru25-document-parsing-vlm-opendatalab-2026)<iframe src="https://shiporskip.io/embed/mineru25-document-parsing-vlm-opendatalab-2026" title="MinerU2.5 ShipOrSkip verdict" width="360" height="260" style="border:0;border-radius:16px;max-width:100%;" loading="lazy"></iframe>The reviews
“I've tried six document parsing libraries and MinerU has the best table extraction accuracy I've seen at any price point. The Markdown output is clean enough to feed directly into embedding pipelines without post-processing. 61K stars isn't hype — it's earned.”
“It's good, but 'state-of-the-art' in document parsing has a long history of being true until you hit your company's specific document formats. Complex form PDFs with non-standard layouts will still break it. And at 1.2B parameters, it's not actually that lightweight on CPU-only hardware.”
“Document parsing is the unsexy infrastructure that every enterprise AI project depends on. A high-accuracy open-source model at this scale removes one more reason for organizations to stay locked into expensive cloud document APIs. This is how AI democratization actually happens.”
“Research assistants and knowledge bases live or die on document ingestion quality. MinerU2.5 handling formulas, multi-column layouts, and mixed media means I can finally build reliable pipelines from academic PDFs without babysitting the output.”