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LatestBaidu1.0
BaiduVision-Language

Baidu Releases Qianfan-OCR for Document Intelligence

The new vision-language model from the Chinese tech giant is designed for complex, multilingual optical character recognition and layout analysis.

Mar 18, 2026
NotableOther
Qianfan-OCR

Chinese technology company Baidu has released Qianfan-OCR, a new vision-language model specialized for optical character recognition and document understanding. The model is aimed at developers who need to extract text and structural information from complex documents across multiple languages.

As a document intelligence model, Qianfan-OCR is designed to go beyond simple text transcription. Its capabilities include recognizing tables, analyzing page layouts, and handling a wide variety of languages. This makes it suitable for digitizing complex materials like invoices, structured forms, and academic papers that mix text with other elements.

A New Tool for Digitization

The release adds a powerful new option to the growing ecosystem of open models for document processing. Baidu's entry provides a strong multilingual solution for enterprise and archival applications where documents often contain complex formatting. This is a critical task for businesses looking to automate data entry and researchers digitizing large volumes of text.

The model weights and usage instructions are available on the Hugging Face Hub. Potential users should note that it is released under a custom End User License Agreement, which may place restrictions on certain use cases compared to more permissive open-source licenses.

Sources

  • baidu/Qianfan-OCR

    Hugging Face

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Get the model

Hugging Face

Specs

Context window33K tokens
Size9.5 GB
PrecisionBF16
ArchitectureQianfanOCRForConditionalGeneration
LicenseOTHER
Downloads35.1K
Likes1.2K

Can you run it?

Runs on a laptop — about 5.1 GB at 4-bit.

  • BF16 (as published)

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

    11.7 GB
  • 8-bit

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

    7.2 GB
  • 4-bit

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

    5.1 GB
Your machine
GGUF builds
  • 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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