**Qianfan-OCR** is a **4B-parameter end-to-end document intelligence model** developed by the Baidu Qianfan Team. It unifies document parsing, layout analysis, and document understanding within a single vision-language architecture. Unlike traditional multi-stage OCR pipelines that chain separate layout detection, text recognition, and language comprehension modules, Qianfan-OCR performs **direct image-to-Markdown conversion** and supports a broad range of prompt-driven tasks — from structured document parsing and table extraction to chart understanding, document question answering, and key information extraction — all within one model. - 🏆 **#1 End-to-End Model on OmniDocBench v1.5** — Achieves **93.12** overall score, surpassing DeepSeek-OCR-v2 (91.09), Gemini-3 Pro (90.33), and all other end-to-end models - 🏆 **#1 End-to-End Model on OlmOCR Bench** — Scores **79.8** - 🏆 **#1 on Key Information Extraction** — Overall mean score of **87.9** across five public KIE benchmarks, surpassing Gemini-3.1-Pro, Gemini-3-Pro, Seed-2.0, and Qwen3-VL-235B-A22B - 🧠 **Layout-as-Thought** — An innovative optional thinking phase that recovers explicit layout analysis within the end-to-end paradigm via `⟨think⟩` tokens - 🌍 **192 Languages** — Multilingual OCR support across diverse scripts - ⚡ **Efficient Deployment** — Achieves **1.024 PPS** (pages per second) with W8A8 quantization on a single A100 GPU

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Unlimited-OCR

baidu

- [2026/07/21] 🤝 Thanks to the ms-swift community for their support, our model now supports training with ms-swift. - [2026/07/03] 🤝 Thanks to the Baidu Cloud team for their support. Our model is now available on Baidu Cloud. - [2026/06/28] 🤝 Thanks to the vLLM community and Tianyu Guo for their support, our model now supports vLLM inference. - [2026/06/24] 🤝 Thanks to AK for creating a demo for us. It is now available at Hugging Face Spaces. - [2026/06/23] 📄 Our paper is now available on arXiv. - [2026/06/23] 🤝 Thanks to the ModelScope community for their support. Our model is now available at ModelScope. - [2026/06/22] 🚀 We present Unlimited-OCR, aiming to push Deepseek-OCR one step further. Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.12.3 + CUDA12.9： **Recipe:** https://recipes.vllm.ai/baidu/Unlimited-OCR

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Unlimited-OCR-2

baidu

> Unlimited OCR 2 supports **Transformers** (native, for quick tests) and **SGLang** (recommended for serving). Tested with Python 3.10, `torch==2.13.0`, `transformers==4.52.1`, `huggingface-hub==0.36.0`, `tokenizers==0.21.4`, on an NVIDIA A800-80GB: **Multi-page inference** (`infer_multi`). All pages of a document are parsed in one request, so the model can use cross-page context. Pass the page images in page order:

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