surya

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# Surya

Surya is a 689M param OCR model with these features:

- Accuracy - scores 85.9 on [OmniParseBench](https://huggingface.co/datasets/datalab-to/omni_parse_bench), the highest of the open models under 1B parameters we have scored, and 83.7% on [olmOCR-bench](https://huggingface.co/datasets/allenai/olmOCR-bench)
- Speed - throughput of 4.5 pages/s on one H100 at 192 DPI, 1.7x Surya 2 with MTP (see [Throughput](#throughput))
- Multilingual - scores 74.9% on an internal benchmark set of 91 languages (more [here](#multilingual))
- Layout analysis (table, image, header, etc.) with reading order
- Tables as HTML, with merged cells as colspan / rowspan (row and column geometry needs a Surya 2 checkpoint; see Limitations)

We also ship smaller models for line-level text detection and ocr error detection.  It works on a range of documents (see [usage](#usage) and [benchmarks](#benchmarks)).

## Try Datalab's Managed Platform

Our managed platform uses Surya, our highest accuracy model [Chandra](https://github.com/datalab-to/chandra), and other models.

The Datalab API turns documents into verifiable knowledge your agents act on. Every result traces back to its page and position, and one API can parse, extract, fill and edit documents.

Get started with **about 5,000 free convert pages every month** (work email) — [sign up](https://www.datalab.to/?utm_source=gh-surya) (takes under 30 seconds) or try our free [public playground](https://www.datalab.to/playground?utm_source=gh-surya).

## Model Information

<img src="static/images/opb_size_chart.png" width="700"/>


|                            Detection                             |                                   OCR                                   |
|:----------------------------------------------------------------:|:---------------------------------------------------------------------