Why Europe’s AI champion is turning everything you think you know about privacy, security, and control on its head

Why Mistral is so efficient

The technology behind Mistral is fundamentally different. And that difference delivers tangible benefits: faster, more cost-effective, and more sustainable.

From a jack-of-all-trades to a team of specialists

Traditional AI models function like one giant jack-of-all-trades. Every query activates the entire model, even if you only need a tiny fraction of that knowledge. This wastes unnecessary computing power, time, and energy.

Imagine a library with a single librarian who has to know literally every book by heart. Ask for an apple pie recipe? He searches his entire brain. Ask about quantum physics right after that? His entire brain is at work again. Inefficient.

For some of their models, Mistral chose a different approach: Mixture of Experts (MoE). Instead of a single jack-of-all-trades, you work with a team of specialists. Each specialist (an “expert” in AI terms) is trained on specific patterns and structures. A smart receptionist (the “router”) analyzes each question and automatically forwards it to the right experts.

If you ask something about financial analysis, only the experts who are good with numbers and logic are activated. The rest remain inactive. They consume no computing power, no energy, and no money. The model determines this itself, in real time, for each question.

The numbers: 6% active, 100% knowledge available

So you have access to 100% of the knowledge and capacity, but you only use and pay for the 6% that’s actually needed for that specific question. This isn’t just marketing talk, it’s how the architecture fundamentally works.

What are the benefits?

• Speed: Answers come faster because there’s less to process. What takes 2 seconds in traditional models, Mistral delivers in less than a second.
• Lower costs: By activating only 6%, costs are 60–80% lower than with comparable traditional models. With large volumes, this literally saves thousands of euros per month.
• Scalability: Because the models are more efficient, you can deploy more capacity without needing proportionally more infrastructure.
• Sustainability: Less computing power directly translates to lower energy consumption and reduced cooling requirements. For organizations that conduct CSRD reporting, this is no mere afterthought, it’s a measurable, reportable impact.

The latest breakthrough: 10x more efficient

In late 2025, Mistral launched the Mistral 3 family. Running on NVIDIA’s new GB200 hardware, Mistral Large 3 performs a full 10x better than on previous-generation chips. The same quality, but at a fraction of the energy and cost.

This is due to the combination of smart software architecture (MoE) and new hardware specifically optimized for these types of workloads. It’s comparable to the shift from gasoline to electric: not just more efficient, but fundamentally different in design.

What makes MoE so unique

The Mixture of Experts approach isn’t a gimmick, it’s a different philosophy:

• Dynamic resource allocation: Only what’s needed is activated
• Specialization without losing breadth: Experts develop in-depth knowledge in their domain, but together they cover the full spectrum
• Linear scalability: You can add more experts without slowing down the entire architecture
• Future-proof: new experts can be added for new domains without disrupting the existing system

Other AI labs are also experimenting with MoE, but Mistral is the first to put it into production at this scale, with this level of performance, and to make it fully open-source.

Sustainability: a smart choice

Technology consumes energy, and that goes for AI as well. When you ask an AI model a question, servers in a data center are running to provide computing power. Those servers use electricity and generate heat, which means they also need to be cooled. The larger and more complex the model, the more energy it requires.

Right now, there are a lot of figures circulating online about AI’s energy consumption, some are accurate, others are wildly exaggerated. We’ll be writing a separate article about that soon. But regardless of the exact numbers, when you use technology, you naturally want to consider how to do so as sustainably as possible, and that’s where choosing efficient AI becomes relevant.

Smarter computing makes an immediate difference

Thanks to its Mixture of Experts architecture, Mistral uses 60–80% less computing power per query than traditional models. Less computing power directly translates to lower power consumption and less heat (meaning less cooling is needed).

This isn’t a theoretical saving. It’s a measurable difference that impacts your Scope 3 emissions, the emissions from the services you purchase. Under the CSRD, you have to report this. With a more efficient AI solution, you can immediately reduce your impact and show it in your reporting.

European infrastructure, shorter distances

Mistral runs on European servers with an energy mix that is, on average, greener than that of many data centers elsewhere in the world. On top of that, shorter distances also mean less energy loss during transmission over the network. Every data packet traveling from Amsterdam to Paris uses less energy than a packet heading to the West Coast of the United States.

And if you opt for on-premises, the model runs on your own servers within your organization’s walls, so you have complete control. Solar panels on your roof? Then your AI runs on solar energy. Green energy contracts? Then you can directly link your AI footprint to your sustainability goals.

Sustainability as a strategic advantage

CSRD reporting requires organizations to be transparent about their impact. With Mistral, you can demonstrate that you’re making conscious choices:

• An architecture that’s 60–80% more efficient than alternatives
• European infrastructure with a greener energy mix
• The option for on-premises deployment with full control over energy sources
• Measurable, reportable impact

This isn’t just good for the climate, it’s also good for your reputation, your compliance, and your credibility as an organization that takes sustainability seriously.

The Mistral 3 family

The Mistral 3 family offers a complete spectrum: from models that run on a laptop to flagship models capable of handling the most demanding analyses.

Mistral Large 3: the flagship

This is the most powerful model. With 675 billion parameters (41 billion of which are active per query), it ranks #2 among all open-source models worldwide. It processes text and images, speaks over 40 languages fluently, and has a context window of 256,000 tokens (approximately 200,000 words that it can process at once).
Suitable for complex analyses, legal documents, medical diagnostics, strategic planning, anything where you need the highest-quality AI.

Ministral 3: from data center to laptop

This is where it gets really interesting. Ministral 3 consists of nine compact models in three sizes:

• 3B (3 billion parameters): runs on a laptop or edge device
• 8B (8 billion parameters): ideal for medium-sized applications
• 14B (14 billion parameters): a balance between power and efficiency

Each size comes in three variants: Base (the foundation), Instruct (optimized for conversations), and Reasoning (for complex logic).

Open-source and open weights

A fundamental difference between Mistral and proprietary alternatives is their approach to openness and transparency. This is no minor detail; it determines what you can and cannot do with the technology.

What does open-source actually mean?

Open-source means that the source code is freely available. Anyone can view, use, modify, and distribute the code. This is the opposite of closed systems, where the code is secret and you can only use the end product.

Mistral publishes many of its models under the Apache 2.0 license, one of the most permissive open-source licenses. You may use the software for any purpose, including commercial use, and make modifications without being required to share those modifications.

Open weights: the key to true control

In addition to open-source code, Mistral also publishes the “weights,” the model’s learned parameters. This is crucial. An AI model is essentially a massive collection of numbers (the weights) that determine how the model works. Without these weights, you have the code but no working model. With open weights, you can:

• Run the model entirely on your own without relying on Mistral’s servers
• Customize and fine-tune the model for your specific situation
• Check exactly what happens to your data
• Conduct independent research into how the model works

The biggest advantage: no vendor lock-in

With closed systems, you’re completely dependent on the vendor. Does OpenAI raise prices? You pay. Do they change the terms? You accept them. With open-source Mistral models, we have more control. In addition, our Sterc.ONE platform makes it easy to switch between all models from all AI model providers, such as Gemini, OpenAI, and Anthropic, as well as all Mistral models.

Our partnership with Mistral

Mistral combines the best of both worlds. The open-source models give you complete freedom and control; we can deploy them on your own infrastructure within your own premises. At the same time, we can leverage the European infrastructure, benefiting from Mistral’s infrastructure, updates, and support.

This means you automatically have access to improvements. Updates, security patches, and new model versions are rolled out without you even noticing. You can always switch to a self-hosted version later if your needs change.
And if you choose the on-premise option, you’ll have complete autonomy. Together, we’ll decide when to implement updates, how to configure the model, and what to do with it.

Privacy you can trust

This is probably the most important difference. It’s not just about technology. It’s about legislation, jurisdiction, and who has access to your data.

The difference between server location and legislation

Many organizations think, “We use Azure with servers in the Netherlands, so our data is safe.” That’s true, but not entirely. Where the server is located isn’t the whole story. What matters is which laws govern the company that manages that server and who owns the software.

Microsoft, Google, OpenAI, all American companies with American software. Thanks to the CLOUD Act (in effect since 2018), U.S. authorities can demand access to all data that these companies manage or process using their software, even if those servers are physically located in Amsterdam, and even without your knowledge. There’s nothing you can do about it.

Incidentally, this applies to all your American software: your Microsoft 365, Salesforce, and other American cloud solutions are also subject to this legislation. For many standard business processes, such as email, CRM, and HR systems, that risk is acceptable. You make a conscious decision: the convenience and functionality outweigh the theoretical risk posed by the CLOUD Act.

But AI is different. For two reasons:

First: with AI, you often share much more sensitive information than with standard software, such as strategic analyses, sensitive documents, confidential conversations, medical records, and R&D plans. AI actively processes your most valuable knowledge. And that’s where the fear comes in: Is my data being used to train the model? Are they learning from my trade secrets? With many AI services, this is unclear or even explicitly the case. Whether this is justified or not, let’s leave that aside for now, because:

Second: when it comes to AI, you now truly have a choice. Replacing Microsoft 365 is complex, your entire organization runs on it. But when it comes to AI, you’re still at the beginning. You can choose now: an American model or a European solution that offers transparency regarding data processing and training from day one. With existing software packages, that choice is often no longer available or isn’t even an option.

That makes the choice for European AI strategically more important than with standard cloud tools. It’s not just legally different; it also feels different because you know that AI “reads” and “understands” your data in a way that traditional software doesn’t.

Mistral is subject to European law

Mistral is a French company, based in Paris, operating under French and European law. The software was developed in Europe. The U.S. CLOUD Act has no jurisdiction here. U.S. authorities cannot demand access.

For organizations that use AI to process their most sensitive information, such as patient records in hospitals, legal files at law firms, strategic plans, business-critical data, and R&D data, this is a fundamental difference. No gray area, just clarity.

GDPR compliance from day one

Mistral was designed from the outset with European privacy legislation as its guiding principle. An independent study by Incogni in 2025 ranked Mistral number one for privacy among AI providers.

Specifically:

• Data processing in Europe: all processing takes place on European servers
• Full transparency: open-source options let you see exactly how models work
• EU AI Act ready: a compliance hub with tools and documentation

Mistral itself does not learn from your data

Crucial: Mistral itself does not learn from your data. It uses the information temporarily to provide an answer and forgets it immediately afterward. Your trade secrets stay confidential. It’s worth noting, though, that most AI model providers explicitly state that they don’t train their models using your data when you use their APIs, which is the case when you use Sterc.ONE.

However, we can make your AI system smarter by incorporating the right dataset as memory, from short-term memory for previous questions in a session to long-term memory containing your entire knowledge base. But this only happens with data that you explicitly release, within your own environment.

Mistral on the Sterc.ONE platform

Technology alone isn’t enough. You need a platform that makes technology accessible and usable for your organization.

Your AI cockpit

Sterc.ONE is an all-in-one AI platform that gives you access to the power of Mistral through a secure, European environment. Think of it as your personal AI cockpit: a central hub where you can work with AI without having to be an AI expert yourself.

We work directly with Mistral and use servers located within the European Union that offer maximum infrastructure security. Updates, security patches, and new model versions are rolled out automatically, ensuring you’re always working with the latest and most secure versions. If you choose the on-premise option, the infrastructure is located within your own facility, and you have full control.

Data Processing Agreement (DPA)

We have a Data Processing Agreement (DPA) with Mistral, a legal contract that precisely outlines how your data is handled and what Mistral is and isn’t allowed to do with that data. We also have these agreements with the other AI model providers.

The memory: your own vector database

This is where the magic happens. A vector database is a specialized database optimized for AI applications. All your documents, manuals, contracts, knowledge base, and procedures are converted into vectors and stored in a database that only you can access.

Do you have 10,000 documents? The AI finds the relevant passages in seconds and uses them to answer your question. This data never leaves your environment.

How does a question work?

1. An employee asks a question: “What is the procedure for warranty claims for product X?”
2. The system instantly searches your vector database for relevant passages
3. Those passages are sent to Mistral along with the question
4. Mistral writes a clear answer based on your own documentation
5. The answer is returned, all done.

Important: This data, your documents, your vector database, and your conversations, is also stored within the Sterc.ONE platform. We have full control over this data. No black box, no hidden processes. You know exactly where your data is stored (within Europe), how it’s processed, and who has access to it. And if you opt for on-premises deployment, literally everything stays within your own walls.

We can also integrate this as automation flows into your processes. Think of: automatic processing of emails, real-time analysis of documents in your workflow, or proactive alerts when certain situations arise. AI becomes part of how you work.

A team of AI agents ready to go

The platform offers ready-to-use AI agents: digital colleagues who can perform specific tasks. Each agent is assigned a clear role in the process and is fully equipped to fulfill it.

How does an agent work?

Each agent can:

• Usetools: access specific functionalities needed for the task (search documents, perform calculations, interact with external systems)
• Have its own memory: remember context within a conversation or even across multiple sessions
• Deploy the right AI model: we choose the Mistral model that best suits the task, a lightweight model for quick queries, a more powerful model for complex analyses, or even a specialized model like Codestral for technical tasks

For example, we can build an agent that handles emails using Mistral Small (fast and cost-effective), while another agent analyzes legal contracts using Mistral Large 3 (maximum quality). Each agent gets exactly the capacity it needs, no more, no less.

You’ll also get access to handy AI tools, such as your own prompt library where you can save and reuse your best prompts.

You don’t have to start from scratch. You’ll get an AI team that’s already up and running, which we can fully customize to your specific needs and processes.

Why this matters now

The question isn’t whether you’ll use AI, but which AI and under what conditions.

Shadow IT is the real risk

Many organizations ban ChatGPT in the workplace. But research shows that employees who know its benefits use it anyway, on their personal phones, with personal accounts, out of sight of IT and compliance.

And it doesn’t stop with ChatGPT. There are hundreds of AI tools that employees use spontaneously: free text generators, AI chatbots for customer service, tools for creating presentations, and AI assistants that write code. Many employees don’t even realize they’re using AI. It’s built into all kinds of handy online tools they find through Google.

The problem with this uncontrolled proliferation:

• You have no idea where the data is going
• Every tool has its own privacy terms (which nobody reads)
• Some tools explicitly train on your input
• You can’t control who has access to what
• Compliance and IT have no visibility into what’s happening
• Different tools mean varying levels of quality and reliability

This is shadow IT at its worst: all the risks, no control, and you only find out about it after the fact. It often comes to light when something goes wrong, a data breach, a compliance question you can’t answer, or sensitive business information that suddenly pops up somewhere it doesn’t belong.

A better solution

Instead of banning it, you can offer a secure, compliant AI platform that employees are allowed to use. When you offer Mistral through Sterc.ONE, you give them the tools they need within the parameters you set.

Employees gain access to powerful AI that truly makes their work easier. But with:

• Full control over where data goes
• One platform instead of dozens of separate tools
• clear terms and governance
• Visibility for IT and compliance
• European legislation and GDPR compliance
• Quality and reliability you can guarantee

The paradox is this: by offering a good alternative, you increase control and productivity. Employees no longer need to secretly use random tools because they now have an official, secure alternative that works just as well, or even better.

The competition isn’t waiting

While some organizations hesitate, competitors are adopting AI at breakneck speed. Companies that use AI effectively can work faster, make better decisions, and provide better service.

The question isn’t whether AI will change your industry, it’s bound to happen anyway. The question is whether you’ll lead the way or fall behind.

The strategic choice

European compliance from day one. GDPR-compliant with no gray areas. Ready for the EU AI Act. And 60–80% lower costs with comparable performance. For large volumes, this saves thousands of euros per month.

Data that stays within Europe, or even within your own walls. Sustainability you can measure and report on. And technological independence from American or Chinese tech.

Sterc.ONE + Mistral: a winning team

Why organizations choose Mistral through Sterc.ONE:

Privacy & legislation

• European jurisdiction, no CLOUD Act risks
• Fully GDPR-compliant from day one
• EU AI Act-ready with a compliance hub
• Data Processing Agreement (DPA) with Mistral

Data & infrastructure

• Servers located within the European Union
• Data processing stays within Europe
• Option for on-premises deployment
• Option to run the system on your own premises
• Maximum security and control

Sustainability

• 60–80% lower energy consumption per query
• Measurable impact for CSRD reporting
• European data centers with a greener energy mix
• Full control over energy sources for on-premises operations

Freedom & transparency

• Open-source models available (Apache 2.0)
• Open weights for full control
• No vendor lock-in
• Flexibility in deployment (API, own server, on-premise)
• Full transparency thanks to open source

Efficiency & costs

• 60–80% lower costs than U.S. alternatives
• Mixture of Experts for maximum efficiency
• Automatic updates and security patches
• Scalable from laptop to data center

Ready for the next step?

Want to experience for yourself how Mistral works on the Sterc.ONE platform? Schedule a demo, test with a secure subset of your own data, and go live immediately with full support.

Request a demo