#1313th of 49 in Open modelsFor data and documents, documents and ocr
unlimited-ocr
OCR model that parses long documents and multi-page PDFs in one pass
- Stars
- 28.3k
- License
- MIT
- Last commit
- Oct 2026
- Language
- Python
0 on 19 Jun 202628,306 on 23 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Unlimited-OCR is a Baidu document-parsing vision-language model, building on DeepSeek-OCR, with weights on Hugging Face. The repo ships inference code for Transformers, vLLM and SGLang, the last exposing an OpenAI-compatible chat API. It handles single images and multi-page input, with PDFs converted to images first.
Who it is for: Engineers self-hosting OCR for scanned documents and PDFs on NVIDIA GPUs
Strengths
- Multi-page parsing in one request, with 32768 max context length in the examples
- Three inference paths: Transformers, vLLM (Docker images), and SGLang with OpenAI-compatible API
- infer.py batch script launches SGLang and sends concurrent requests for image dirs or PDFs
- MIT license; training supported through ms-swift
Weaknesses
- Requires an NVIDIA GPU; examples tested only on CUDA 12.9 with Python 3.12
- PDFs must be rasterized to images with PyMuPDF before parsing
- SGLang setup needs a bundled dev wheel and custom logit processor flags
- VRAM requirement is not stated in the README
What it needs
- GPU required
- Needs PyTorch 2.10.0, transformers 4.57.1, PyMuPDF, vLLM or SGLang (optional)
- Models: baidu/Unlimited-OCR (safetensors)
- port 10000
Quick answers
Is unlimited-ocr open source?
Yes. Its code is on GitHub under the MIT license.
Can you run unlimited-ocr with Docker?
Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.
Does unlimited-ocr need a GPU?
Yes, it needs a GPU.
Also in Open models
See all 49| Rank | Project | Score |
|---|---|---|
| 1 | llmfitRust tool that checks which LLMs fit your RAM, CPU and GPU | 87 out of 100 |
| 2 | layaSingle-pass multilingual classifier for typed choice, score and yes/no decisions | 86 out of 100 |
| 3 | timesfmPretrained time-series foundation model for zero-shot forecasting from Google Research | 77 out of 100 |
| #4 | yolov5PyTorch YOLOv5 object detection, segmentation and classification models with training code | 76 out of 100 |
| #5 | speechPyTorch toolkit for training and deploying ASR, TTS and speech LLM models | 74 out of 100 |