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LatestBaiduv1
BaiduVision-Language

Baidu releases Unlimited-OCR under permissive MIT license

The Chinese tech giant's multilingual vision-language model targets text extraction across languages and document types.

Jun 19, 2026
NotableMIT
Unlimited-OCR

Baidu has published Unlimited-OCR on Hugging Face, a multilingual vision-language model aimed at optical character recognition. The release lands under the MIT license, one of the most permissive options available, meaning developers can use, modify, and ship the model commercially with minimal restrictions.

Unlimited-OCR is built as a vision-language system rather than a traditional OCR pipeline. That approach has become increasingly common for document understanding, where models read images and produce structured or plain text while drawing on broader language reasoning to handle layout, context, and multiple scripts.

Why it matters

OCR remains one of the most practical and widely deployed AI tasks, underpinning everything from document digitization to data entry and accessibility tools. A few points stand out about this release:

  • The MIT license lowers the barrier for commercial adoption and downstream fine-tuning.
  • A multilingual focus suggests the model is intended to work across scripts rather than English-only text.
  • Backing from Baidu, a major player in Chinese-language AI, adds weight to the multilingual claim.

Baidu has not yet detailed parameter counts, context length, or benchmark results in the available record, so independent evaluation will be the real test of how Unlimited-OCR compares to established open OCR systems. For now, the model is available to download and try directly from its Hugging Face repository.

Sources

  • baidu/Unlimited-OCR

    Hugging Face

    Visit
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Get the model

Hugging Face

Specs

Context window33K tokens
Size6.7 GB
PrecisionBF16
ArchitectureUnlimitedOCRForCausalLM
LicenseMIT
Downloads4.1M
Likes4.9K

Can you run it?

Runs on just about anything.

  • BF16 (as published)

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    8.2 GB
  • 8-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    5 GB
  • 4-bit

    Any modern laptop · 8 GB RAM

    3.5 GB
Your machine
GGUF builds
  • Mixture-of-experts: every expert must be loaded, so memory follows total parameters, not the active slice.
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Vision-Language

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