Since 2022, generative AI has established itself in businesses. In a few months, GPT chat, developed by OpenAI, has become an essential tool for writing texts, generating code, creating marketing materials or even automating exchanges with customers.
This rise in power has accelerated writing, coding, and automation, but it has also raised major questions: Where does the data go?, Who controls the models? and What alternatives exist to the American ecosystem?

It is in this context that was born Mistral AI in 2023, which aims to build a sovereign and open artificial intelligence, capable of competing with American giants while respecting European standards of confidentiality and transparency.

Mistral now represents a credible alternative to ChatGPT for companies looking for more control over their data and tools.

So Should we rely on the maturity of ChatGPT or on the sovereignty of Mistral?

In this article, we are going to compare both models from every angle : performances, prices, speed, confidentiality and adaptation to the professional world, with concrete examples and data from recent studies to help you choose the one that best fits your needs.

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ChatGPT or Mistral IA:

ChatGPT: the recognized model

OpenAI is a company founded in 2015 by Sam Altman, Elon Musk, Elon Musk, Greg Brockman, Ilya Sutskever, John Schulman, and Wojciech Zaremba. In 2022, she released the first version of ChatGPT, today The most used artificial intelligence model in the world. Supported by microsoft, which integrated it into its tools (Word, Outlook, Copilot), OpenAI was able to transform complex technology into an assistant accessible to all.

According to the site H.Ostinger, here is a breakdown of the number of users per LLM.

Powerful and varied functionalities

ChatGPT is based on language models that are now available in several versions: GPT-4, Gpt-4o, and more recently GPT-5, all capable of treating text, code, images, and even voice.

This allows it to perform a wide variety of tasks:

- Write professional content (articles, emails, LinkedIn posts, internal reports).

- Translate or rephrase a text in a different tone.

- Analyze computer code or propose technical solutions.

- Create images thanks to the integration of the visual model FLOOR 3.

This versatility makes ChatGPT a very comprehensive tool for businesses, freelancers, or content creators.

Strengths and limitations

The strengths of ChatGPT

• ‍High contextual understanding: ChatGPT knows how to adapt its style, language level and structure according to the target audience.‍
• Great versatility: He can also write an article, correct a text, generate code, or help with translation.‍
• Fluid interface and intuitive API: the tool is accessible to everyone, whether via the website or by integration into professional applications.
  

Benchmarks confirm these qualities. According to Prompthackers (2025), Gpt-4o gets 88.7% of success on the test MMLU (Massive Multitask Language Understanding), a score higher than most competing models, including Mistral Large which only gets 81.2%.
This score reflects Gpt-4o's ability to correctly answer questions from more than 50 domains, ranging from Computing At upright, with a level of difficulty ranging from general knowledge to a level collegiate. The MMLU test assesses the understanding, the precision And the versatility of the model in various contexts to provide a performance indicator for professional uses.

The limits you need to know

• ‍Data hosting in the United States: conversations and requests pass through OpenAI servers, which may raise questions of sovereignty and GDPR compliance for some European companies (openai.com/privacy).‍
• Subscription cost: The “ChatGPT Plus” version allowing access to GPT-4 is charged approximately €22 per month, a reasonable price for individual use, but higher on a large scale.‍
• Limited confidentiality: Although OpenAI claims that it does not use business account data to train its models, some sensitive businesses (banks, health, public sector) prefer sovereign solutions to ensure compliance.

Mistral AI: the French and open alternative

Mistral AI is a French start-up created in 2023 in Paris, by three researchers: Arthur Mensch, Guillaume Lample and Timothée Lacroix. Its ambition: to offer a “frontier” artificial intelligence that is both Efficient, transparent and respectful of data sovereigntyS.
To support its development, Mistral raised a major fundraiser in September 2025: 1.7 billion euros, which values the company at 11.7 billion euros depending LeMonde.

The Chat: the general public (and professional) interface

Among its flagship products is The Cat, a conversational assistant comparable to ChatGPT, but designed for Europe and professional needs. In February 2025, Mistral launched its Le Chat application in a mobile version, claiming that the AI could respond up to 1,000 words per second, thanks to an optimized infrastructure. 

This claimed speed places Mistral in a unique position for highly reactive interactive uses, such as customer chatbots Or the internal micro-assistants.

One of the pillars of Mistral is its orientation towardsOpen source or Open Weights. This means that some versions of its models allow companies to deploy Or of the modify. 

This approach contrasts with that of fully proprietary models, where the user depends on the provider for any evolution or hosting. We will come back to this distinction between open and closed models in more detail in the second part of the article, in order to explore the concrete implications for businesses.

Strengths and limitations

Mistral forces

• ‍Speed : the promise of 1,000 words per second (via Le Chat) gives it a competitive advantage for instant interactions.‍
• Reduced cost and efficiency : by optimizing inference and distributing models, Mistral promises a lower cost per use than very heavy proprietary models.‍
• Compliance with the RGPD and European hosting : the ability to deploy models locally or in European data centers reinforces confidence in the protection of sensitive data.‍
• Innovation and openness : the choice of open source (or open weight) models encourages adoption, experimentation and customization by users.
  

Mistral limits

• ‍Less extensive “general public” functions : some services that are already mature at ChatGPT (plugins, various integrations) are still under development at Mistral.‍
• Fewer resources and infrastructures than American giants: OpenAI has massive support from Microsoft,). Mistral, despite a recent fundraiser, is still evolving with more limited resources, which sometimes slows down scaling.

Understand the difference: closed model vs open model

The real distinction between ChatGPT and Mistral is not only in their performance, but in how they are designed and used.

ChatGPT: a closed and centralized model

ChatGPT works as a “closed” platform: everything goes through the servers ofOpenAI.
The data you send (your requests, documents, messages) passes through an infrastructure located mainly In the United States, managed directly by OpenAI.
Businesses cannot see or change how the model was trained, or adapt it to their own technical environment.

That's what we call a proprietary model :
OpenAI keeps control of everything, performance, updates, security, and even possible usage limits.

Pros

It's stable, reliable, and ready to use. ChatGPT is still great for businesses that want a tool powerful and immediately operational, without technical configuration.

Cons

‍This dependence on external infrastructure means that Data is bound to leave the company.
Even though OpenAI claims that it does not use data from subscribers to the professional version to train its models (Source: openai.com/privacy), this can be a problem for structures subject to strict rules (banks, health, public sector, etc.).

Mistral: an open and adaptable model for each company

The approach of Mistral AI is the opposite: its model is designed to be integrated and personalized within business systems.
Some of its models are distributed under Apache 2.0 license (help.mistral.ai), which allows an organization to download, deploy, and modify them according to its specific needs.

Clearly, with Mistral, a company does not just “use” an AI, it can host it internally, personalize it, and keep control of all its data.

Mistral can be installed:

1. ‍on your internal servers, if you want total control;‍
2. in a European cloud, for a compromise between security and performance;
3. or via a private API, hosted on a RGPD certified cloud.
   

This makes it possible to process sensitive data (medical reports, financial documents, customer calls...) without them ever leaving the perimeter of the company.

The other strength of the open model is that it can be adjusted to your job.

For example :‍

- One bank can teach him the terminology of its financial products for more relevant answers.
- One industrial company can link it to its internal documentary base to assist technicians in real time.
- One public organization can create an internal assistant without depending on a foreign actor.

For example, the manufacturer Stellantis is already working with Mistral to integrate AI models directly into its internal infrastructures, avoiding any transfer of data outside Europe (Reuters, 2025).
This allows them to use artificial intelligence to optimize production and R&D, while respecting their industrial confidentiality requirements.

Comparative performances: a clear summary

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Towards model orchestration: using the right engine at the right time

Today, it is no longer necessary to choose a single AI.
The trend is heading towards platforms that are capable oforchestrate multiple models at the same time, automatically selecting the one that best suits each task.

For example:

- GPT chat excels in long and creative writing, where nuance and structure are essential.
- Mistral stands out on the quick and confidential answers, particularly useful in sensitive professional environments.
- Claude (Anthropic) shines for the encoding, synthesis, logic and complex summaries.
- Perplexity combines AI and search in real time, ideal for strategic intelligence.

Some solutions combine these different models in a single interface. The user no longer has to choose, the platform automatically identifies The most suitable model on demand, while guaranteeing data security and sovereignty thanks to accommodation in France.

Conclusion

GPT chat and Mistral AI do not oppose each other: they complement each other.

- The first bet on the maturity, precision and global power.
- The second on the speed, adaptability and European sovereignty.

The real challenge in 2025 is no longer to choose between them, but to know How to make them collaborate intelligently.
Thanks to hybrid tools like Delos, businesses can now use each AI for what it does best, while keeping total control of their data.

Try Delos for free and discover how to combine ChatGPT, Mistral, Claude or Perplexity to boost your performance.