Scans and complex layouts leave you no choice but to infer structure with a model. But the technical gap between MinerU, Marker, and Docling is far smaller than the licensing gap — MinerU needs a separate license past $20M monthly revenue, Marker's model weights need payment past a funding threshold, and only Docling is cleanly MIT. Read the LICENSE before the benchmark.
An MIT-licensed open-source UI automation framework from ByteDance (~13k GitHub stars). UI actions rely solely on feeding screenshots to vision-language models (Qwen3-VL / Doubao / Gemini-3 / UI-TARS), with no DOM parsing. A single JS API works across Web / Android / iOS / desktop, and starting from v1.0, the DOM action mode was removed entirely. The trade-off: each step is slower and more token-expensive.
DeepSeek-OCR's paper is titled Contexts Optical Compression -- OCR is just the means; what it actually validates is that 'rendering text as images and feeding them to a VLM' achieves 10x compression at 97% accuracy. This is a qualitative shift for long-context LLM and RAG token costs.