Tiny Aya: Bridging Scale and Multilingual Depth
Tiny Aya redefines what a small multilingual language model can achieve. Trained on 70 languages and refined through region-aware posttraining, it delivers state-of-the-art in translation quality, strong multilingual understanding, and high-quality target-language generation, all with just 3.35B parameters. The release includes a pretrained foundation model, a globally balanced instruction-tuned variant, and three region-specialized models targeting languages from Africa, South Asia, Europe, Asia-Pacific, and West Asia. This report details the training strategy, data composition, and comprehensive evaluation framework behind Tiny Aya, and presents an alternative scaling path for multilingual AI: one centered on efficiency, balanced performance across languages, and practical deployment.
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Alejandro R. Salamanca
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Diana Abagyan
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Daniel D'souza
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Ammar Khairi
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David Mora
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Saurabh Dash
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Viraat Aryabumi
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Sara Rajaee
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Mehrnaz Mofakhami
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Ananya Sahu
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Thomas Euyang
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Brittawnya Prince
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Madeline Smith
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Hangyu Lin
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Acyr Locatelli
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Sara Hooker
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Tom Kocmi
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Aidan Gomez
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Ivan Zhang
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Phil Blunsom
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Nick Frosst
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Joelle Pineau
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Beyza Ermis
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Ahmet Üstün
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Julia Kreutzer
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Marzieh Fadaee
Tiny Aya: Bridging Scale and Multilingual Depth
Tiny Aya redefines what a small multilingual language model can achieve. Trained on 70 languages and refined through region-aware posttraining, it delivers state-of-the-art in translation quality, strong multilingual understanding, and high-quality target-language generation, all with just 3.35B parameters. The release includes a pretrained foundation model, a globally balanced instruction-tuned variant, and three region-specialized models targeting languages from Africa, South Asia, Europe, Asia-Pacific, and West Asia. This report details the training strategy, data composition, and comprehensive evaluation framework behind Tiny Aya, and presents an alternative scaling path for multilingual AI: one centered on efficiency, balanced performance across languages, and practical deployment.
Tiny Aya demonstrates high-quality multilingual capabilities with 3.35 billion parameters through region-aware posttraining and balanced language performance.
multilingual language model region-aware posttraining instruction-tuned variant region-specialized models multilingual understanding translation quality target-language generation