Glossary

Mistral AI

What is Mistral AI?

Mistral AI is an AI company based in Paris, founded in 2023 by Arthur Mensch, Guillaume Lample and Timothée Lacroix. It develops large language models and offers both models with openly available weights, some under the Apache 2.0 licence, and commercial models through its own platform. For European organisations, Mistral AI is frequently mentioned in discussions about data sovereignty and running models on their own infrastructure.

Topics

  • language models
  • provider
  • Europe

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Related terms

Large language model (LLM)

A large language model (LLM) is a neural network trained on very large amounts of text, enabling it to understand and generate language. It works by calculating the most likely next token, step by step. LLMs write, summarise, translate, answer questions and generate code; well-known examples include Claude, GPT, Gemini and Llama. Without access to current sources, they only know what was in their training data.

  • Language models
  • Generative AI
  • +1

LLaMA (Meta)

LLaMA, now usually written “Llama”, is a family of large language models from Meta. Many versions were released with downloadable weights under Meta’s own licence, allowing organisations to run and adapt them on their own infrastructure. The most recent major generation is Llama 4 (2025); in 2026 Meta also introduced the Muse model series, only some of which is released openly (as of October 2026).

  • language model
  • open weights
  • +1

OpenAI

OpenAI is an AI company based in San Francisco, founded in 2015 as a non-profit organisation. Since its restructuring in October 2025, it has consisted of the non-profit OpenAI Foundation, which controls the for-profit OpenAI Group PBC (as of October 2026). OpenAI is best known for ChatGPT and the GPT language models, as well as the DALL·E image generator and the Whisper speech recognition model. Its models are offered through apps and an API.

  • provider
  • language models
  • +1

Foundation model

A foundation model is a large AI model pre-trained on very extensive, wide-ranging data that can then be used for many different tasks. The term was coined at Stanford University in 2021. Well-known examples include large language models such as Claude or GPT, as well as image models. Businesses usually build their applications on such models rather than training their own from scratch; the EU AI Act refers to general-purpose AI models.

  • Base model
  • Language models
  • +1