DeepSeek-OCR
Read documents like an image
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DeepSeek-OCR is a model that reads documents by treating long text as an image and compressing it optically. Representing a page visually uses far fewer tokens than encoding the same text directly, which makes long-context document tasks much more efficient while still delivering strong optical character recognition.
The technique is aimed at cases where large volumes of text have to be fed into a model, archives, books, records, and token cost or context limits become the bottleneck.
It is aimed at developers and researchers building document-processing and long-context systems who want to cut the cost of handling large text corpora without losing OCR accuracy.
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Why we picked it
DeepSeek-OCR earns its spot for the token-efficiency angle specifically — representing a page visually instead of encoding its text directly cuts the token cost of long-document tasks dramatically, worth naming for anyone processing large volumes of scanned or dense documents.
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