The staggering innovations of generative AI models are reconfiguring professional dynamics. Mistral AI, a major player in the technology scene, is deploying an impressive range of models tailored to each sector. The proposed solutions range from a small specialized model to advanced
multilingual architectures. Finding the right model for your needs can be crucial to optimizing your processes. Be attentive to the technical specifics, as each model has its distinct characteristics to meet the diverse demands of the industry.
A varied range of models at Mistral AI
Mistral AI offers a wide range of generative AI models adapted for various use cases in business. Based in Paris, this French company provides both open-source and proprietary models, ensuring flexibility for developers and businesses. With a vast selection of models, it becomes essential to understand their differences to choose the one that best meets specific needs.
Understanding Mistral AI licenses
Mistral AI takes a dual approach to distributing its models. Some are available under an Apache 2.0 license, offering considerable freedom of use. This open-source license allows users to modify, distribute, and use the models without restriction. Additionally, some advanced models are offered under a dual-license system: the research license, which allows for non-commercial use, and the commercial license, required for deployment for profit.
Models under the Apache 2.0 license are showcased on platforms like Hugging Face, from where they can be downloaded freely. For models under a commercial license, Mistral AI ensures private management of weights, limiting access to authorized users.
Deployment methods
Mistral AI offers various deployment solutions. This includes access through its developer API “The Platform,” hosted in Europe, which is designed for all available models. Models under the Apache 2.0 license can also be deployed through major cloud providers such as GCP, AWS, Azure, and others. Moreover, Mistral Large 2 is accessible via tools like Azure AI Studio, AWS Bedrock, Google Cloud Model Garden, and IBM Watsonx.
Models under the Apache 2.0 license
| Model | Use | Size | Context (in tokens) | Modality |
|---|---|---|---|---|
| Pixtral 12B | Analysis / understanding of images | 12B | 128k | Text, Image |
| MathΣtral | Advanced mathematics | 7B | 32K | Text |
| Codestral Mamba | Programming | 7.3B | 256K | Text |
| Mistral NeMo | Generalist and multilingual | 12B | 128K | Text |
| Mistral 7B | Generalist | 7B | 4k | Text |
| Mixtral 8x7B | Generalist and multilingual | 45B (12.9B active) | 32k | Text |
| Mixtral 8x22B | Generalist and multilingual | 141B (39B active) | 64k | Text |
For applications in generalist chatbots, the model Mixtral 8x7B emerges as the best choice, with its multilingual capability and a context of 32,000 tokens. While Mistral 7B launched the company, its limited contextual dimension has now been surpassed by more advanced models.
Models under the commercial license
| Model | Use | Size | Context (in tokens) | Modality |
|---|---|---|---|---|
| Mistral Small | Generalist | 22B | 32k | Text |
| Mistral Large 2 | Advanced generalist, multilingual, code | 123B | 128K | Text |
| Codestral | Programming (80+ languages) | 22B | 32K | Text |
| Mistral Embed | Embeddings (English only) | NC | 8k | Text |
| Ministral 3B | Edge computing | 3B | 128K | Text |
| Ministral 8B | Advanced edge computing, reasoning | 8B | 128K | Text |
The model Mistral Large 2 is praised for versatile professional use, with its 123 billion parameters and a large context window, allowing for complex tasks. The model Mistral Small is designated for fundamental tasks such as translation or summarization while remaining economical.
Finally, the models Ministral 3B and 8B show respectable performance, especially when integrated into a well-defined RAG architecture. The 128,000 token context window makes them suitable tools for analyzing long documents. For semantic search systems, Mistral Embed proves optimized for English.
Challenges and opportunities
Mistral AI covers a wide range of business needs, but the presence of Pixtral in its open-source range highlights a certain lag in the multimodal field. Generative AI stands out as a major issue for companies wishing to stand out in artificial intelligence technologies. The integration of these models into various systems is central to maximizing their yield within organizations.
Partnerships with giants like OpenAI and Apple may also influence market dynamics. Confronted with growing competition in the sector, continuous innovation will emerge as a determining factor for players like Mistral AI wishing to maintain their leadership.
The orientation towards smaller, purpose-adapted models proves to be an opportunity, especially with the emergence of solutions like a new AI JetPack, which can stimulate asynchronous creation and significantly improve business process efficiency.
The availability of a complete range of generative AI models from Mistral AI demonstrates a strong commitment to meeting the demands of the contemporary market. Although the path to excellence in generative AI promises to be complex, Mistral AI positions itself as one of the key players to watch.
Frequently asked questions
What are the different types of generative AI models offered by Mistral AI?
Mistral AI offers several language models, including open-source models, proprietary models, and specialized models, suited for various business applications.
How do I choose the generative AI model that best suits my business?
To choose the right model, evaluate your specific needs, such as language processing capability, the type of tasks (analysis, programming, etc.), and the level of complexity you wish to achieve.
Which Mistral models are available under the Apache 2.0 license?
The models available under the Apache 2.0 license include Pixtral 12B, MathΣtral, Codestral Mamba, Mistral NeMo, Mistral 7B, Mixtral 8x7B, and Mixtral 8x22B, allowing for free usage by the community.
What are the differences between Mistral AI’s commercial and open-source models?
Models under an open-source license are freely accessible and can be used without restriction, while commercially licensed models require a specific agreement for professional use and are often more advanced.
Is the Mistral Large 2 model the best choice for general use?
Yes, the Mistral Large 2 is widely recognized for its versatility, offering advanced multilingual capabilities and complex reasoning, making it an excellent choice for various tasks, including chatbots.
What are the specificities of the Mixtral 8x22B model?
The Mixtral 8x22B is an extremely powerful model with 141 billion parameters, designed for advanced reasoning tasks and complex applications requiring high processing and contextual capacity.
Is it possible to deploy Mistral models on a private cloud?
Yes, Mistral AI allows self-deployment of all its models on private or on-premises clouds, providing additional flexibility for companies with specific security requirements.
Which Mistral AI models are best suited for code processing?
Codestral and Mistral Large 2 are particularly suited for code processing, with capabilities supporting over 80 different languages.
How can I gain access to Mistral AI models for non-commercial projects?
For non-commercial projects, you can use the open-source licensed models available or request access to the Mistral research license for advanced models.
Which model is recommended for image analysis?
The Pixtral 12B model is specifically designed for the analysis and understanding of images, making it the optimal choice for multimodal applications combining text and image.
