Speech to text

T-one

A compact T-Bank streaming model for recognizing Russian speech in phone calls. Works in real time even without a GPU.

Developer
T-Bank, Russia
First release
Jul 2025
Latest release
Jul 2025
Sizes
72M
License
Commercial use allowedApache 2.0
Russian
Supported
Running
On your own serverAlso runs without a GPU
Industries
Customer support, Finance
Deploy on your server Hugging Face GitHub

What it does

  • Transcribing phone calls
  • Voice robots on the line
  • Call quality control
  • Searching call recordings

Where it is used

Call centersBanksDelivery servicesTelecom

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. T-one

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.

Frequently asked questions

Can T-one be used in a commercial project?

Yes. License: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does T-one 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 T-one support Russian?

Yes, Russian is listed on the model card.

Where can I download T-one and what does it cost?

The T-one 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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DetailsSpeech to textNVIDIA Parakeet / Canary / Nemotron SpeechNVIDIA · USACommercial use with conditions

Fast NVIDIA speech recognition models, including streaming ones for real-time use. Parakeet TDT v3 and Nemotron 3.5 ASR understand Russian.

Details

Source: huggingface.co/t-tech/T-one. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.