Documents and OCR

Nanonets-OCR

A model that converts documents to Markdown with tables, stamps, signatures, checkboxes and watermarks. The OCR2 model card lists Russian among its languages.

Developer
Nanonets, USA / India
First release
Jun 2025
Latest release
Oct 2025
Sizes
1.5B – 3B
License
Commercial use with conditionsNanonets-OCR2-1.5B-exp: Apache 2.0; the 3B versions have no license stated on the card and are based on Qwen2.5-VL-3B with its own license
Russian
Supported
Ready-made builds
GGUF
Running
On your own serverAlso runs without a GPU
Industries
Documents and accounting, Finance, Legal
Deploy on your server Hugging Face

What it does

  • Recognising invoices, contracts and delivery notes, including in Russian
  • Recognising stamps, signatures and marks
  • Handwriting recognition
  • Table recognition

Where it is used

Document workflowAccountingLegal departments

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
no versions
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. Nanonets-OCR2 1.5B и 3B
  2. Nanonets-OCR-s

How to run it

On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.

Frequently asked questions

Can Nanonets-OCR be used in a commercial project?

With conditions. License: Nanonets-OCR2-1.5B-exp: Apache 2.0; the 3B versions have no license stated on the card and are based on Qwen2.5-VL-3B with its own license. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does Nanonets-OCR need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does Nanonets-OCR support Russian?

Yes, Russian is listed on the model card.

Where can I download Nanonets-OCR and what does it cost?

The Nanonets-OCR weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

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Details

Source: huggingface.co/nanonets/Nanonets-OCR2-3B. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.