France-based Mistral Raises $830 Million Debt For AI Data Centre
Mar 30, 2026 | By Kailee Rainse

France-based AI startup Mistral has raised $830 million in debt funding to acquire 13,800 Nvidia chips for a large data centre project near Paris, according to a Reuters report.
The financing, which is expected to be announced on Monday, marks Mistral’s first entry into the debt market and reflects rising investor confidence in European AI firms competing with US tech giants like Microsoft, Google, and Amazon in cloud and AI services.
SUMMARY
- France-based AI startup Mistral has raised $830 million in debt funding to acquire 13,800 Nvidia chips for a large data centre project near Paris, according to a Reuters report.
The funding was arranged by a group of seven banks, including BNP Paribas, Crédit Agricole CIB, HSBC, and MUFG, according to the company.
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The data centre is located in Bruyères-le-Châtel near Paris and is expected to become operational in Q2 2026. Mistral selected the site in February 2025 for its first facility.
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Last month, the Paris-based company also announced plans for a second data centre in Sweden and aims to secure 200 megawatts of capacity across Europe by the end of 2027.
“Scaling our infrastructure in Europe is critical to empower our customers and to ensure AI innovation and autonomy remain at the heart of Europe,” Chief Executive Officer Arthur Mensch said in a statement shared with Reuters.
Mistral, which provides AI models to the French armed forces, has established itself as a European alternative to major US AI companies. It offers AI models and infrastructure services to governments and enterprises that want greater technological independence.
About Mistral AI
Mistral AI is a leading artificial intelligence company focused on building advanced and accessible AI systems. It aims to make frontier AI widely available so that individuals and businesses can innovate easily. The company’s mission is to empower the world to create and benefit from powerful AI technology in a simple, open, and scalable way.
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