Most of our customers run our models inside their own data centers and cloud environments today. As AI becomes more deeply embedded in production, they need confidence that the underlying capacity will remain available, resilient, and under the regional controls their workloads require. For some, that means complementing infrastructure they manage themselves with capacity provided and operated by Mistral.
At the inference layer, that means two things: keeping data and processing in-region, and having dependable access to capacity when demand peaks. We are strengthening both.
Mistral Regional Endpoints , now generally available, let customers choose whether their inference runs in Europe or the US, helping them align inference location with their data-residency, regulatory, and latency requirements. Inference and the associated processing take place in the selected region, subject to limited, safeguarded transfers to sub-processors that may occur outside that region, as described in our Trust Center . Our new Mistral Priority Tier , now in public preview, provides committed service levels for mission-critical workloads, including custom rate limits, and is backed by an uptime SLA. Mistral is the only European AI lab to offer both: choice of processing region and a committed, SLA-backed service level.
Of course Mistral models will continue to be available through partners, as well - you can learn more about our close partnerships here .
Control over where AI runs, however, is only one part of AI sovereignty. Customers also need control over the intelligence they choose to run on that infrastructure. Today’s AI systems are no longer built on a single model but on an ensemble of capabilities: extended reasoning, high-volume production, or work shaped around a company's own data. Mistral builds for each, from frontier models to specialist ones like Mistral OCR and Voxtral to custom models trained on a company's own knowledge.
Our customers particularly value us for pioneering open models. Open weights give them what mission-critical work demands: the ability to see inside a model, adapt it, and retain the intelligence they build with it. This is why we are enthusiastic contributors to the Open Secure AI Alliance and NVIDIA Nemotron Coalition . We are now extending that openness beyond our own models. Mistral’s platform will support third-party open models, starting with Z.ai’s GLM-5.2 . This and future open models will run on the same infrastructure, regional controls, and service commitments as Mistral models, so customers can broaden model choice without fragmenting where their AI runs.
Open intelligence is inseparable from the compute beneath it. And without assured access to that compute, Europe cannot control the AI systems on which its industries, institutions, and future competitiveness will depend. Capacity is increasingly strategic, yet remains scarce, fragmented, and difficult to secure.
Mistral is bringing together an anchor group of enterprises whose multi-year commitments can support infrastructure in Europe at a scale no participant could secure alone. Aggregating long-term demand in this way will help determine what capacity is built, where it is located, and whom it serves. European Compute Units, or ECUs, convert those commitments into access to Mistral-built infrastructure over multiple years. Participants can use that capacity across the range of products available on Mistral Compute as their needs evolve.
Europe is the place where this framework begins, but the same challenge exists everywhere: organizations and governments need to harness the power of frontier AI for their mission-critical needs without surrendering control over the infrastructure and intelligence loop.
The path will differ by region, but the foundations are the same: operational control, choice of intelligence, and assured access to compute. Europe can show how these elements come together to create an AI ecosystem that remains open to global innovation while preserving institutional autonomy.
That is the model Mistral is building toward: one in which enterprises, public institutions, and startups can use the best AI available, shape it around their own knowledge, and retain the value it creates.