Audience
Researchers, developers, and organizations building multilingual AI applications who need a high-performance model that understands and generates text across many language
About Aya Expanse
Aya Expanse redefines multilingual AI as a research model mastering 101 languages through innovative instruction tuning and cross-lingual transfer techniques. By combining a curated open source dataset with compute-efficient pretraining, it achieves unparalleled performance across low- and high-resource languages while reducing infrastructure costs by up to 30%, setting a new benchmark for scalable, inclusive language modeling.
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Llama 2
The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters.
Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations.
Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests.
Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations.
We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.
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Aya Vision
Aya Vision is a research model advancing in multilingual multimodal AI through innovative synthetic data generation, cross-modal model merging, and a comprehensive benchmark suite. It achieves state-of-the-art performance across 23 languages, surpassing larger models while efficiently addressing data scarcity and catastrophic forgetting by reducing computational overhead up to 40% via optimized training techniques.
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Voxtral TTS
Voxtral TTS is a state-of-the-art, multilingual text-to-speech model designed to generate highly realistic and emotionally expressive speech from text, combining strong contextual understanding with advanced speaker modeling to produce natural, human-like audio output. Built as a lightweight model with around 4 billion parameters, it delivers efficient performance while maintaining high quality, enabling scalable deployment for enterprise voice applications. It supports nine major languages and diverse dialects, and can adapt to new voices using only a short reference audio sample, capturing not just tone but also rhythm, pauses, intonation, and emotional nuance. Its zero-shot voice cloning capabilities allow it to replicate a speaker’s style without additional training, and it can even perform cross-lingual voice adaptation, generating speech in one language while preserving the accent of another.
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Tiny Aya
Tiny Aya is a family of open-weight multilingual language models from Cohere Labs designed to deliver powerful, adaptable AI that can run efficiently on local devices, including phones and laptops, without requiring constant cloud connectivity. It focuses on enabling high-quality text understanding and generation across more than 70 languages, including many lower-resource languages that are often underserved by mainstream models. Built with lightweight architectures around 3.35 billion parameters, Tiny Aya is optimized for balanced multilingual representation and realistic compute constraints, making it suitable for edge deployment and offline use. The models support downstream adaptation and instruction tuning, allowing developers to customize behavior for specific applications while maintaining strong cross-lingual performance.
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Pricing
Starting Price:
Free
Free Version:
Free Version available.
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Company Information
Cohere
Founded: 2019
Canada
cohere.com/research/aya
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