DeBERTa-v3 и mDeBERTa-v3
A time-tested encoder behind many classifiers and NER models (including GLiNER). The multilingual mDeBERTa-v3 understands Russian.
The last open version came out in Oct 2021. The family has not been updated for a long time: the model still works, but do not expect fixes or new sizes.
- Developer
- Microsoft, USA
- First release
- Oct 2021
- Latest release
- Oct 2021
- Sizes
- 70M – 435M
- License
- Commercial use allowedMIT
- Russian
- Supported
- Running
- On your own serverAlso runs without a GPU
- Industries
- Software development, Documents and accounting, Customer support
What it does
- Classifying review sentiment
- Entity extraction after fine-tuning
- Checking whether a conclusion follows from a text
Where it is used
Hardware requirements
Versions
- mDeBERTa-v3-base (многоязычная)
- DeBERTa-v3 xsmall, small, base, large
How to run it
I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.
Frequently asked questions
Can DeBERTa-v3 и mDeBERTa-v3 be used in a commercial project?
Yes. License: MIT. It allows commercial use, but it is still worth having a lawyer review the license before launch.
What hardware does DeBERTa-v3 и mDeBERTa-v3 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 DeBERTa-v3 и mDeBERTa-v3 support Russian?
Yes, Russian is listed on the model card.
Where can I download DeBERTa-v3 и mDeBERTa-v3 and what does it cost?
The DeBERTa-v3 и mDeBERTa-v3 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
- SelectionI pick the model size for your task and hardware and test it on your examples.
- DeploymentI deploy it on your server or in a closed network and provide an API.
- Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
- IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.
Similar models
A modern replacement for classic BERT: faster, reads up to 8 thousand tokens at once. A base for your own classifiers. Trained on English and code; for Russian there is RuModernBERT.
DetailsText analysisXLM-RoBERTaMeta · USACommercial use allowedA classic multilingual encoder for 100 languages, including Russian. The base of many sentiment, NER and embedding models, including BGE-M3.
DetailsText analysisGLiNERUrchade Zaratiana and Fastino AI · France / USACommercial use allowedFinds the entities you need in text without training: just list what to look for (name, amount, date). GLiNER2 also classifies text. Multilingual versions understand Russian.
DetailsSource: huggingface.co/microsoft/deberta-v3-base. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.


