Enterprise AI company Cohere has launched a new family of multilingual models called Tiny Aya. The announcement was made on the sidelines of the ongoing India AI Summit. These models are open-weight, meaning their underlying code is publicly available for anyone to use and modify. They support over 70 languages and can run on everyday devices like laptops without requiring an internet connection.
The model, launched by the company’s research arm Cohere Labs, includes support for South Asian languages such as Bengali, Hindi, Punjabi, Urdu, Gujarati, Tamil, Telugu, and Marathi. The base model contains 3.35 billion parameters, which is a measure of its size and complexity. Cohere has also launched TinyAya-Global, a version fine-tuned to better follow user commands for applications that require broad language support.
Regional variants complete the family: TinyAya-Earth for African languages; TinyAya-Fire for South Asian languages; and TinyAya-Water for Asia Pacific, West Asia, and Europe. The company stated that this approach allows each model to develop stronger linguistic grounding and cultural nuance, creating systems that feel more natural and reliable for the communities they are meant to serve. All Tiny Aya models retain broad multilingual coverage, making them flexible starting points for further adaptation and research.
Cohere noted that these models were trained on a single cluster of 64 H100 GPUs, a type of high-powered chip by Nvidia, using relatively modest computing resources. They are ideal for researchers and developers building apps for audiences that speak native languages. The models are capable of running directly on devices, allowing developers to power offline translation. The company built its underlying software to suit on-device usage, requiring less computing power than most comparable models.
In linguistically diverse countries like India, this offline-friendly capability can open up a diverse set of applications and use cases without the need for constant internet access.
The models are available on HuggingFace, the popular platform for sharing and testing AI models, and the Cohere Platform. Developers can download them on HuggingFace, Kaggle, and Ollama for local deployment. The company is also releasing training and evaluation datasets on HuggingFace and plans to release a technical report detailing its training methodology.
The startup’s CEO, Aidan Gomez, said last year that the company plans to go public soon. Reports indicate the company ended 2025 on a high note, posting $240 million in annual recurring revenue, with 50 percent growth quarter-over-quarter throughout the year.