Soofi Announces Model for Industrial AI in Europe

The Soofi consortium presents initial performance results for “Soofi S”, the first building block of a European AI model family. The project, funded by the Federal Ministry for Economic Affairs and Energy as part of the IPCEI-CIS / 8ra initiative, aims to develop high-performance foundation models on European infrastructure, offering businesses, public administration, research institutions and start-ups a transparent alternative to non-European models.

Soofi S marks the beginning of the project’s first release phase. The model is designed for organisations that need to run AI applications transparently, adaptably and on their own or sovereign infrastructure — for example in industrial processes, the analysis of extensive technical and regulatory documents, code generation or agentic AI systems. Trained from scratch on 27 trillion (27T) tokens, Soofi S is a 30 billion parameter (30B-A3B) mixture-of-experts model whose hybrid Mamba-Transformer architecture combines high throughput with low energy consumption. Soofi S has been trained primarily on English and German text and achieves top-tier results among open models in its size class in English; in German, it leads the peer group. Soofi S is initially released as a base model, which can already be fine-tuned for specific domains; post-trained variants for dialogue and agentic applications will follow.

“Whoever controls the foundation models controls a central part of future digital value creation and strengthens their sovereignty and resilience. With Soofi, we are building an open foundation on which businesses, SMEs and the public sector can develop transparent AI applications based on their own data, without becoming permanently dependent on individual non-European
models,” says Jörg Bienert, Managing Director of the Center for Sovereign AI, German AI Association.

A particular focus lies on transparency: the consortium will not only release model weights but also publish technical documentation on training methodology, data preparation and the data pipelines used. This makes Soofi S more auditable for businesses, public authorities and researchers, and more readily adaptable to specific use cases. Soofi S and subsequent models are trained on Deutsche Telekom’s Industrial AI Cloud in Munich, using NVIDIA’s open-source AI framework. Initial results show that the Soofi S base model matches or outperforms international models of comparable size across German and English benchmarks.

“Soofi S is not intended as yet another general-purpose chatbot, but as a technical foundation for industrial AI. What matters is that Soofi S performs not only well in benchmarks, but can be deployed reliably, efficiently and transparently in production,” says Nicolas Flores-Herr, Technical Project Lead for Soofi and Team Lead at Fraunhofer IAIS.

The Soofi consortium brings together research institutions, universities and AI companies from across Germany. The project is coordinated by the German AI Association.

The partners are:

● Fraunhofer IAIS: Dr. Nicolas Flores Herr, Dr. Mehdi Ali, Dr. Michel Fromm, Dr. Max Lübbering
● Fraunhofer IIS: Jan Plogsties, Dr. Viktor Hangya, Dr. Lucas Weber
● German Research Center for Artificial Intelligence: Prof. Dr. Antonio Krüger, Prof. Dr. Philipp Slusallek, Dr. Daniel Porta, Dr. Simon Ostermann
● Julius-Maximilians-Universität Würzburg / CAIDAS: Prof. Dr. Andreas Hotho, Jan Pfister, Julia Wunderle
● Leibniz University Hannover / L3S Research Center: Prof. Dr. Wolfgang Nejdl, Simon Gottschalk
● Technical University of Darmstadt / hessian.AI: Prof. Dr. Kristian Kersting
● Berlin University of Applied Sciences: Prof. Dr. Alexander Löser, Tom Röhr
● Ellamind: Dr. Jan Philipp Harries, Björn Plüster, Maximilian Idahl
● Merantix Momentum: Dr. Stefan Dietzel, Dr. Patrick Putzky, Dr. Martin Genzel

The model is being tested in collaboration with industry partners in real-world application scenarios. The goal is to gather insights from real-world use cases at an early stage and to tailor the model’s further development closely to the specific requirements of the
business community, so that companies can integrate the model into their processes and products. If you are interested in testing the model or collaborating, please contact us at .

Press Contact:
Lara Lawniczak

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