DeepSeek-OCR
DeepSeek-OCR reimagines optical character recognition as a context compression problem — treating visual documents not as images to scan, but as information to compress and decode through an LLM-centric vision encoder. It converts documents, PDFs, and images to clean markdown, extracts text with layout awareness, parses figures, and localizes specific elements by reference — all at ~2500 tokens per second on a single A100 with vLLM. Multiple resolution modes from 64 to 400+ vision tokens let you tune the quality-speed tradeoff for your use case.
MIT
Image-Text-to-Text
PyTorch
Transformers
Safetensors
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