Tools/baidu/Unlimited-OCR

Unlimited-OCR

Unlimited OCR Works: Welcome the Era of One-shot Long-horizon Parsing.

22.7k+1.2k/wkgrowthPythonMIT Licensenew this week

The Lens

By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.

Updated Jun 2026

Unlimited-OCR is Baidu's open model for turning images and PDFs into text. Point it at a scanned contract, a multi-page report, or a screenshot full of text and it reads the whole thing in one pass, even very long documents. It handles single images, batches, and full PDFs, with streaming output so you see results as they parse. The weights are on Hugging Face and ModelScope under the MIT license, which means free to use, including commercially, with no strings.

Running it yourself is where the cost shows up. This needs an NVIDIA GPU, CUDA 12.9, Python 3.12, and a recent PyTorch and transformers stack. You can run it through plain transformers or through SGLang for faster batch serving. It builds on DeepSeek-OCR, so the lineage is solid, but you are still standing up GPU infrastructure and a model server. There is no hosted API here, no dashboard, no support line. You bring the hardware.

For solo work, the Hugging Face demo is free to try and you can run it on a rented GPU when you have a real job. Small teams that already process documents will want a dedicated GPU box or a cloud GPU. Larger teams treating OCR as a pipeline should put SGLang behind a queue. If you need OCR as a managed service with an SLA, look at a cloud vendor instead.

The catch: MIT covers the code and weights, but accuracy on messy real-world scans is the thing you have to test on your own documents before trusting it. No benchmark replaces running it on your actual files.

Free vs Self-Hosted vs Paid

fully free

Free: The model weights are published on Hugging Face and ModelScope under the MIT license. Free to download, run, and use commercially with no restrictions. A live demo runs on Hugging Face Spaces for testing without any setup.

Self-hosted: This is the only real way to run it in production. You supply the hardware: an NVIDIA GPU, CUDA 12.9, Python 3.12, and a recent PyTorch and transformers stack. Inference runs through plain transformers or through SGLang for faster batch serving. No license fee, but you pay for the GPU, whether that is a box you own or a rented cloud instance.

Paid: There is no hosted API, paid tier, or commercial offering from Baidu here. If you want managed OCR with an SLA, that means a different vendor, not this project.

Free and MIT licensed, including for commercial use. Your only cost is the GPU you run it on.

Self-hosting ops:significant

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Organization account (125 public repos)Notable author: 2,610 followersAuthor also built: baidu/nettools (157 stars)

License: MIT License

Use freely, including commercial. Just keep the license.

Commercial use: ✓ Yes

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