DeepSeek OCR

Overview

DeepSeek OCR is a state-of-the-art, transformer-based document AI system designed to deliver unparalleled accuracy, efficiency, and multilingual capabilities in optical character recognition tasks. By compressing high-resolution documents into ultra-lean vision tokens and decoding them using a high-capacity mixture-of-experts language model, DeepSeek OCR achieves near-lossless understanding of text, layout, and diagrams across more than 100 languages.

Its innovative architecture scales across multiple precision profiles—from Tiny mode for rapid throughput to Gundam mode for maximum fidelity—making it suitable for a wide range of applications, including legal, financial, scientific, and multilingual document processing. The engine delivers 97% exact-match accuracy on benchmark datasets while operating at up to 200,000 pages per day on a single NVIDIA A100 GPU.

A key strength lies in the compression pipeline: reducing a 1024×1024 page to as few as 256 tokens without sacrificing layout integrity. Combined with multimodal pretraining, DeepSeek OCR retains captions, tables, formulas, and even specialized scientific notations, enabling downstream tasks like analytics integration, search indexing, and AI-driven summarization.

Key Features

• High-Precision Compression: Context Optical Compression Engine shrinks document images by up to 10× without significant accuracy loss, enabling long-document ingestion.
• Advanced Architecture:
  • Stage 1: Windowed SAM vision transformer + CLIP-Large encoder + 16× convolutional compressor.
  • Stage 2: DeepSeek-3B-MoE decoder (~570M active parameters per token) for reconstructing structured text and annotations.
• Structured Output: Generate HTML tables, Markdown charts, SMILES chemistry strings, geometry annotations—directly machine-ingestible.
• Multilingual Reach: Over 100 languages covered, including Latin, CJK, Cyrillic, and special scientific scripts.
• Performance: Capable of processing ~200k pages/day on a single A100 GPU.
• Deployment Flexibility: MIT-licensed weights allow local GPU deployment; also available via API.

Use Cases

Scanned Books & Reports

Compress text-rich pages for rapid downstream processing—ideal for search indexing, summarization, and knowledge graph building.

Technical Diagrams & Formulas

Accurately extract geometry reasoning, engineering annotations, or chemical SMILES from complex scientific documents.

Multilingual Dataset Creation

Scan and OCR global datasets spanning 100+ languages for training multilingual AI models.

Document Conversion Apps

Integrate into invoice, contract, or form-processing systems to output layout-aware JSON or HTML ready for automation workflows.

Archival and Batch Processing

Use Tiny mode for high-volume archival digitization, stretching GPU resources while keeping structured fidelity.

FAQ

Q1: How accurate is DeepSeek OCR compared to competitors? DeepSeek OCR achieves ~97% exact match accuracy at 10× compression, putting it at the forefront of layout-rich OCR solutions while maintaining a low token budget.

Q2: What hardware is required? Base mode runs on GPUs with 8–10 GB VRAM; Gundam mode benefits from 40 GB A100s for maximum fidelity.

Q3: Can it handle handwriting? DeepSeek OCR is mainly trained on printed text. For cursive-heavy work, it’s recommended to pair it with a handwriting-focused engine like Tesseract.

Q4: Is it open-source? Yes, the weights are MIT-licensed, allowing local deployments without proprietary constraints.

Q5: How does the API pricing work? API pricing is token-based, starting at ~$0.028 per million input tokens for cache hits.

Q6: What are its limitations? Accuracy declines (~60%) at extreme compression ratios (20×). Fine vector graphics may require vector-specific parsing tools.

Q7: Can it handle specialized scientific notations? Yes, DeepSeek OCR supports chemistry (SMILES strings), geometry annotations, and LaTeX-formatted scientific formulas.

DeepSeek OCR combines cutting-edge compression techniques, a powerful Mixture-of-Experts decoding architecture, and broad multilingual coverage to redefine what’s possible in structured document understanding. Whether you're processing millions of archival pages or precision-sensitive technical blueprints, it offers a flexible, open, and high-performance solution.