Meet EuroLLM
Large language model
made in Europe
built to support all
official 24 EU languages
Featured In
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Multimodal
Soon we will be adding vision and voice to our models so that they can interpret and understand images and speech.
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Open Source
Freely used by researchers, organisations and citizens of Europe.
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High Performance
Great on language related tasks, including question answering, summarisation, and translation.
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Multilingual
Models pretrained and finetuned on text from all languages.
EuroLLM-9B
Our current flagship model. A 9B parameter model trained on over 4 trillion tokens of multilingual data across 35 different languages, including all official EU languages. We’ve made EuroLLM 9B Base available for fine-tuning on any task. As a demonstration, we’ve also provided EuroLLM 9B Instruct, a model fine-tuned for instruction following and chat capabilities.
TRY THE MODEL AT HUGGING FACE >Euro LLM-1.7 B
A 1.7B parameter model trained on similar data to EuroLLM-9B, that is ideal to for use in edge devices.
TRY THE MODEL AT HUGGING FACE >Our Mission
Sharing a common vision, our team is committed to advancing multilingual AI technologies to empower Europe’s digital future and strengthen the EU’s commitment to AI sovereignty. The team’s goal is for EuroLLM to become a flywheel for innovation — offering anyone the opportunity to use this EU homegrown LLM and build upon it. The project is living proof that amazing things can happen when Europe comes together to push the boundaries of innovation.
The Team
Key People
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André Martins
VP of AI Research, Unbabel and Associate Professor, Instituto Superior Técnico, University of Lisbon
André Martins is an expert in machine learning and natural language processing. His research has been funded twice by the European Research Council. He is a Fellow of the ELLIS Society and a board member of the European Association for Machine Translation. He is a co-founder of the Lisbon Machine Learning School (LxMLS).
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Alexandra Birch
Co-founder and Chief Scientist, Aveni.ai
Associate Professor in Natural Language Processing at the University of Edinburgh. Her research has resulted in over 100 peer reviewed publications, focusing on translation and multilingual NLP and covering topics such as ethics, explainability and efficiency.
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Nuno Guerreiro
Senior Research Scientist, Unbabel
Nuno Guerreiro focuses on machine translation evaluation, error detection, and LLM development. He is a lead developer for Unbabel’s xCOMET and Tower models and contributes to projects like CroissantLLM and EuroLLM.
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Pierre Colombo
Associate Professor, Université Paris-Saclay
Pierre Colombo works as Chief Science Officer at Equall.AI, a legal technology startup. His work focuses on AI safety and LLM applications, with publications in ACL, EMNLP, NeurIPS, and ICML, and he received the AAAI 2022 Best Student Paper Award.
About EuroLLM
The EuroLLM project includes Unbabel, Instituto Superior Técnico, the University of Edinburgh, Instituto de Telecomunicações, Université Paris-Saclay, Aveni, Sorbonne University, Naver Labs, and the University of Amsterdam. Together they created EuroLLM-9B, a multilingual AI model supporting all 24 official EU languages. Developed with support from Horizon Europe, the European Research Council, and EuroHPC, this open-source LLM aims to enhance Europe’s digital sovereignty and foster AI innovation. Trained on the MareNostrum 5 supercomputer, EuroLLM outperforms similar-sized models. It is fully open source and available via Hugging Face.
We thank EuroHPC for the HPC resources used to support this work through grant EHPC-EXT-2023E01-042.
