GOT-OCR 2.0 or PaddleOCR-VL: choosing an OCR model
Both models are small, both are Apache 2.0 with no commercial strings attached, and both run on an ordinary computer without a powerful GPU. GOT-OCR 2.0 from StepFun is 580M and reads text, formulas, tables, sheet music and diagrams, but its last release was 2024-11 and the catalog states plainly that it now lags behind newer models. PaddleOCR-VL from Baidu is 0.9B, was updated through 2026-05, and per its model card supports 109 languages including Russian, recognises tables, formulas and stamps, and outputs Markdown and JSON. For Russian invoices and contracts the choice is close to obvious.
Comparison based on catalog data
| Parameter | GOT-OCR 2.0 | PaddleOCR-VL |
|---|---|---|
| Category | Documents and OCR | Documents and OCR |
| Developer | StepFun, China | Baidu (PaddlePaddle), China |
| Releases | Sep 2024 – Nov 2024 | Oct 2025 – May 2026 |
| Sizes | 580M | 0.9B |
| Hardware | Laptop | Laptop |
| Commercial use | Commercial use allowed | Commercial use allowed |
| License | Apache 2.0 | Apache 2.0 |
| Russian | Not stated | Supported |
| Ollama | No | No |
| Without GPU | Yes | Yes |
| Tasks |
|
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Choose GOT-OCR 2.0 if
- You need the smallest model: 580M against 0.9B
- Your documents contain sheet music or unusual diagrams
- It is a one-off job with no Russian-language requirement
Choose PaddleOCR-VL if
- Your documents are in Russian: the catalog marks PaddleOCR-VL as supporting it
- You need tables, formulas and stamps with Markdown or JSON output
- You want something current: version 1.6 shipped in 2026-05
Other comparisons
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- Whisper or Parakeet: which to choose for business
Need a model for your task?
An open model can run on your own server: data stays in-house, there is no per-request fee, and the model can be fine-tuned on your documents.
- SelectThe model and size for your task and hardware budget
- DeployOn your server or in a closed network, with an API
- Fine-tuneOn your data, or connect a knowledge base
- IntegrateInto your CRM, ERP, bot, website or team chat


