From the model card
Fields below are copied from the tags and counters on the HuggingFace repository deepseek-ai/DeepSeek-OCR at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.
- Publisher (HF namespace)
- deepseek-ai
- Pipeline tag
- image-text-to-text
- Library
- Transformers
- Weight formats
- safetensors
- License tag
mit— read the license file in the repo before relying on it- Language tags
- multilingual
- Papers cited
- arXiv:2510.18234
- Downloads (HF counter at last fetch)
- 2,382,527
- Likes (HF counter at last fetch)
- 3,351
- Model card
- https://huggingface.co/deepseek-ai/DeepSeek-OCR
Use cases
- Extracting text from photographed documents, receipts, and signs
- Mixed-language OCR in bilingual Chinese-English documents
- Processing handwritten forms and low-quality scanned pages
- Building document digitization pipelines
Pros
- Tailored specifically for OCR rather than general VLM tasks
- Handles Chinese and English text in the same image
- DeepSeek's release includes evaluation on real-world OCR benchmarks
- Can process complex layouts that generic VLMs struggle with
Cons
- Specialized OCR models may outperform on narrow domains
- Model card lacks detailed comparison against established OCR tools (Tesseract, PaddleOCR, Google Vision)
- DeepSeek license terms require review before commercial deployment
- Large model size vs dedicated lightweight OCR solutions
Tags
transformerssafetensorsdeepseek_vl_v2feature-extractiondeepseekvision-languageocrcustom_codeimage-text-to-textmultilingualarxiv:2510.18234license:miteval-resultsdeploy:sagemakerregion:us