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MiniCPM-OCR 1.0

MiniCPM-OCR 1.0 is a 1.3B OCR-focused model for understanding documents, including text, tables, formulas, charts, seals, and structured information. It supports Chinese and English and is released with model weights, API documentation, SDK support, and deployment guides for several runtimes.

What it does

Use it to recognize and parse documents, convert their contents into structured formats, or extract specified fields such as receipt totals.

Availability
BF16 checkpoint available on Hugging Face
Pricing model
Not established
Deployment
Usage with vLLM
Privacy
Not established
Licence
Apache License 2.0
Capability
extractionanalysis
Modality
imagetext
Access
APISDKopen weights
Deployment
on-premises
Pricing
unknown
Target user
developerresearcherenterprise

Evidence

12 claims
  • The model handles text, tables, formulas, charts, seals, and key information extraction. [1] [2]
    | Tasks | Text, tables, formulas, charts, seals, and key information extraction |
    OpenBMB. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • It supports Chinese and English documents, including PDFs, scans, photographs, skewed pages, and recaptured documents. [1] [2]
    Handles Chinese and English documents and PDFs, including scans, curved pages,
    OpenBMB. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • The model weights are available on Hugging Face and ModelScope. [1] [2]
    Model weights, code, and documentation are released under the
    OpenBMB. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • Deployment guides are provided for vLLM, SGLang, llama.cpp, Ollama, Transformers, and FlagOS. [1]
    - 🛠️ **Easy to deploy and develop**: **vLLM, SGLang, llama.cpp, and Ollama from day one**, with
    OpenBMB. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • The model has 1.3 billion parameters. [1] [2]
  • Model weights, code, and documentation are released under the Apache License 2.0. [1]
    Model weights, code, and documentation are released under the
    OpenBMB. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • The draft head speeds up decoding by proposing tokens that the main model verifies in one pass. [3]
    **DSpark** speeds up decoding with a small draft model that proposes tokens the main model then
    Hugging Face. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • With this head, MiniCPM-OCR 1.0 improves end-to-end processing efficiency by 55%. [2] [3]
    With this head, MiniCPM-OCR 1.0 improves **end-to-end processing efficiency
    Hugging Face. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • The repository provides a BF16 draft checkpoint for MiniCPM-OCR 1.0. [3]
    > **This repository hosts the DSpark draft (speculative decoding) head for
    Hugging Face. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • The usage instructions show serving MiniCPM-OCR 1.0 with DSpark in vLLM. [3]
  • DSpark requires a matching main and draft model from the same release. [3]
    DSpark requires a **matching main and draft model from the same release**; do not pair this draft
    Hugging Face. Quoted text is outside CC BY 4.0 and keeps its original rights.
  • Model weights, code, and documentation are released under Apache License 2.0. [3]
    Model weights, code, and documentation are released under the
    Hugging Face. Quoted text is outside CC BY 4.0 and keeps its original rights.

Sources

3
1
OpenBMBOwner-controlled
https://huggingface.co/openbmb/MiniCPM-OCR-1.0 Retrieved 2026-10-28 00:20 UTC
Verified
2
GitHub new repositoriesOwner-controlled
https://github.com/OpenBMB/MiniCPM-OCR Retrieved 2026-10-29 00:30 UTC
Verified
3
Hugging FaceOwner-controlled
https://huggingface.co/openbmb/MiniCPM-OCR-1.0-DSpark Retrieved 2026-10-29 00:30 UTC
Verified

Versions

2
VersionEffectiveChangeChanged fieldsState
22026-10-29 00:30 UTCmajor releasedeployment, availability, releaseCurrent
12026-10-28 00:20 UTCpublicationNoneCurrent

In briefs

1

Open in the catalog

Original catalog content is licensed under CC BY 4.0, attributed to wowsuchai. Source quotations and linked content keep their original rights.