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Nougat

Visual transformer that turns scientific PDF pages into markup, math intact.

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About

Nougat (Neural Optical Understanding for Academic Documents) is a visual transformer from Meta AI that performs end-to-end OCR on scientific documents. Instead of relying on embedded PDF text, it reads the rasterized page image and generates a lightweight markup language, which lets it recover semantic structure that conventional extraction loses, especially mathematical expressions and tables.

The model pairs a Swin Transformer vision encoder with an mBART text decoder and was trained on millions of academic papers from arXiv and PubMed via an automated PDF-to-source matching pipeline. It outperformed GROBID and raw PDF text extraction in the paper's evaluations and can handle scanned documents. Meta released the models and code (arXiv 2308.13418, August 2023); check the Hugging Face model card for current license terms before commercial use.

Specs

Context window

Pricing

Free quota

API access

Weights

Open weights

Released

August 30, 2023

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

document-parsingacademic-pdfsocrmath-extraction

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 79; Trending score 72/100 from researcher assessment.

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