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LatestDeepSeekOCR-2
DeepSeekVision-Language

DeepSeek-OCR-2 Tackles Multilingual Document AI

The new open vision-language model is designed to extract text and understand structure from complex, multilingual documents.

Jan 27, 2026
NotableOther
DeepSeek-OCR-2

AI company DeepSeek has released DeepSeek-OCR-2, a powerful vision-language model specialized for Optical Character Recognition (OCR). The model is designed to go beyond simple text extraction, aiming to provide a deeper understanding of document structure and content across multiple languages.

Unlike traditional OCR tools that follow a rigid pipeline, DeepSeek-OCR-2 operates as a vision-language model. It processes an image of a document and a user's prompt to generate structured output, allowing it to handle complex layouts, tables, and mixed-language text found in real-world documents like invoices, forms, and academic papers.

A New Open Alternative

The release of DeepSeek-OCR-2 on Hugging Face provides developers with a strong open-source alternative to proprietary document intelligence APIs from major cloud providers. Its key capabilities include:

  • Multilingual Support: Handles a wide range of languages within the same document.
  • Layout Understanding: Recognizes and preserves the structure of tables and multi-column text.
  • Versatility: Processes both scanned and digitally-born documents effectively.

The model is available under a custom license that permits commercial use, though it includes restrictions against using the model to create competing products. This move gives developers and businesses a new, powerful tool for building applications that require sophisticated document processing without relying on closed, pay-per-use services.

Sources

  • deepseek-ai/DeepSeek-OCR-2

    Hugging Face

    Visit
OlderLingbot-World Animates Images with Camera Controlrobbyant · Image → Video · 9 months agoNewerQwen open-sources compact model for speech recognitionQwen · Alibaba · Speech → Text · 9 months ago

Get the model

Hugging Face

Specs

Context window8K tokens
Size6.8 GB
PrecisionBF16
ArchitectureDeepseekOCR2ForCausalLM
LicenseOTHER
Downloads419.3K
Likes1.2K

Can you run it?

Runs on just about anything.

  • BF16 (as published)

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

    8.3 GB
  • 8-bit

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

    5.1 GB
  • 4-bit

    Any modern laptop · 8 GB RAM

    3.5 GB
Your machine
  • 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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