About This Site
Next-gen document intelligence with context optical compression and multilingual support. DeepSeek OCR is a two-stage transformer-based document AI system that utilizes context optical compression to deliver state-of-the-art document intelligence. It compresses high-resolution documents into lean vision tokens, then decodes them with a 3B-parameter mixture-of-experts model to achieve near-lossless text, layout, and diagram understanding across 100+ languages. It supports GPU-efficient throughput for complex layouts and is trained on 30 million real PDF pages plus synthetic data, preserving layout structure, tables, chemistry (SMILES strings), and geometry tasks.
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Key Features AI
Core Features
Context Optical Compression Engine
Multilingual Support (100+ languages)
Structured Output (HTML, Markdown, SMILES, JSON)
GPU-efficient throughput (200k pages/day on A100)
High precision (97% exact-match accuracy)
MIT-licensed weights for on-premises deployment
Advantages
State-of-the-art accuracy (97% exact match at 10x compression).
High throughput (~200k pages/day per NVIDIA A100 GPU).
Extensive multilingual coverage (100+ languages).
Generates structured output (HTML, Markdown, SMILES, JSON).
Context optical compression reduces compute requirements for long documents.
Open-source (MIT license) for local deployment and compliance control.
Preserves layout structure, tables, chemistry, and multimodal competence.
缺点：Accuracy drops significantly at higher compression ratios (~60% at 20x).
缺点：Challenges with fine vector graphics; may require vector-native parsers.
缺点：Limited performance on handwriting compared to specialized tools.
缺点：Requires modern GPUs for real-time throughput.
缺点：API usage may involve regulatory scrutiny tied to DeepSeek’s Chinese infrastructure.
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