gImageReader vs Surya
gImageReader
github.comSurya
github.comSide by side
| Figure | gImageReader | Surya |
|---|---|---|
| Price from | Free | $400/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | — |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 3 |
| Spec score · OCR software | 7.8 (#29) | 8.7 (#6) |
| Supported inputs | both | both |
| License | The repository identifies its license as GPL-3.0. | The Surya code is Apache 2.0, while the model weights use a modified AI Pubs Open Rail-M license with commercial-use conditions described in the README. |
| Primary platform | desktop | desktop |
| Purpose | gImageReader is a Gtk/Qt front-end to tesseract-ocr. | Surya is a 650M-parameter OCR model for text recognition, layout analysis, reading order, and table recognition. |
| Support | The project directs users to its issue tracker, maintainer email, and FAQ for help. | Datalab lists community support on Free, email and Slack support on Team, and dedicated support on Enterprise. |
Plans
In their own words
gImageReader
gImageReader has no write-up on Specifiction yet; its figures are above.
Surya
Surya is a 650M-parameter OCR model for extracting text and analyzing document structure. It handles layout, reading order and tables, and supports OCR in 91 languages. Surya 2 returns page content as structured blocks that can include HTML, polygons, bounding boxes, confidence values and reading order. Table recognition can provide row and column geometry; full mode can also return HTML with spanning cells and header rows. Equations found in page OCR are represented as KaTeX-compatible LaTeX within math tags. Users can work with a Python package, command-line tools or an interactive Streamlit app for images and PDFs. Layout, OCR and table recognition require an inference backend: vLLM on NVIDIA GPUs or llama.cpp on CPU and Apple Silicon, or a connection to an existing server. Surya is free and open source. The code uses Apache 2.0, while the model weights have a separate modified AI Pubs Open Rail-M license with commercial-use conditions. It is specialized for documents, not photos or natural scenes.