What is DeepSeek OCR's core technology for document processing?
DeepSeek OCR utilizes a two-stage transformer system with context optical compression. It compresses high-resolution pages into compact vision tokens using a DeepEncoder, then decodes them with a 3B-parameter mixture-of-experts model to reconstruct text, layout, and diagrams with high fidelity.
Does DeepSeek OCR support multiple languages?
Yes, DeepSeek OCR offers extensive multilingual support, covering over 100 languages. This includes Latin, CJK, Cyrillic, and specialized scientific scripts, making it suitable for global digitization and data generation projects across diverse linguistic contexts.
Can DeepSeek OCR handle complex document structures like tables and charts?
Absolutely. DeepSeek OCR is specifically designed to deliver near-lossless document understanding for complex layouts, including tables, charts, formulas, and diagrams. It can output structured HTML tables, Markdown charts, and geometry annotations, enabling direct ingestion into analytics pipelines.
What are the deployment options for DeepSeek OCR?
DeepSeek OCR can be deployed locally on-premises using GPUs, as its weights are MIT-licensed. Alternatively, users can access its capabilities via an OpenAI-compatible API, which follows DeepSeek's token pricing model. This offers flexibility for various operational and compliance needs.
How does DeepSeek OCR compare to other cloud OCR services?
DeepSeek OCR matches or exceeds cloud competitors in accuracy for complex documents while using significantly fewer vision tokens. This efficiency makes it particularly advantageous for GPU-constrained operations, offering a powerful alternative for specialized document intelligence tasks.