- Co-founder and CEO, Mistral AI1
Arthur Mensch is a co-founder and the CEO of Mistral AI, according to the company's about page. Before Mistral, Mensch was one of four equal-contribution authors of Training Compute-Optimal Large Language Models (2022), the DeepMind paper that introduced Chinchilla and studied how model size and the number of training tokens should grow together under a fixed compute budget; the paper lists Mensch among its corresponding authors at DeepMind. Mensch was also an equal-contribution author of the retrieval-enhanced RETRO paper (2021), whose authors are all listed as from DeepMind. Mensch co-authored the Mistral 7B (2023) and Mixtral of Experts (2024) papers, whose abstracts say the models are released under the Apache 2.0 license.12345
At a glance
- Current role
- Co-founder and CEO
- Company
- Mistral AI
- Sector
- Company
- Fields
- Language models, Training systems
- Work listed
- 2
- Sources cited
- 5
- Profile reviewed
Career
Before co-founding Mistral AI, Arthur Mensch worked at DeepMind, where Mensch was an equal-contribution author of the RETRO and Chinchilla papers and was listed among the Chinchilla paper's corresponding authors. Mistral AI's about page names Mensch as co-founder and CEO, alongside co-founder and Chief Science Officer Guillaume Lample, and dates the company's first employee to June 2023.321
Research
The 2021 RETRO paper, Improving language models by retrieving from trillions of tokens, describes a language model that conditions on document chunks retrieved from a large text database. The 2022 Chinchilla paper trained more than 400 language models to study how parameter count and training tokens should grow together for a fixed compute budget, and tested the result with the 70-billion-parameter Chinchilla model.32
Mistral AI models
Mensch co-authored the Mistral 7B paper in October 2023 and the Mixtral of Experts paper in January 2024, and both abstracts state that the models are released under the Apache 2.0 license. Mistral's about page lists later company milestones including Mistral Large in February 2024, Small 3 in January 2025, Voxtral in July 2025 and Mistral Studio in October 2025.451
Work and contributions
Chinchilla (Training Compute-Optimal Large Language Models) Published research
One of four equal-contribution authors of the 2022 DeepMind paper, which trains over 400 language models to find that model size and training tokens should be scaled equally for compute-optimal training, and tests this with the 70B-parameter Chinchilla model.2
Mistral 7B and Mixtral 8x7B Open weights
Co-author of the Mistral 7B (2023) and Mixtral of Experts (2024) papers; both abstracts say the models are released under the Apache 2.0 license.45
Timeline
- Released the RETRO retrieval-enhanced language model paper as an equal-contribution author at DeepMind.3
- Released the Chinchilla compute-optimal training paper as an equal-contribution author at DeepMind.2
- Mistral AI, which Mensch co-founded and leads as CEO, hired its first employee.1
- Co-authored the Mistral 7B paper describing an Apache 2.0 licensed model.4
- Co-authored the Mixtral of Experts paper describing the Mixtral 8x7B model.5
- Mistral AI released Mistral Large.1
Other documented roles
Roles the sources document that are not confirmed as current.
- Equal-contribution author of the RETRO (2021) and Chinchilla (2022) papers, written at DeepMind, DeepMind (now Google DeepMind)23
Where they work
- Mistral AI 4 people in the wiki
Related people
- Albert JiangAlso at Mistral AI
- Timothée LacroixAlso at Mistral AI
- Guillaume LampleAlso at Mistral AI
- Liliang RenLanguage models · Training systems
- Lucas AtkinsLanguage models · Training systems
- Jakub PachockiLanguage models · Training systems
- Stas BekmanTraining systems · Language models
- Bryan CatanzaroLanguage models · Training systems
- Susan ZhangTraining systems · Language models
- Ruoming PangTraining systems · Language models
Suggest a correction or removal
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References
5 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026
- Mistral AI — About (founders)
- Training Compute-Optimal Large Language Models (arXiv 2203.15556), author list, equal-contribution note and DeepMind corresponding authors
- Improving language models by retrieving from trillions of tokens (arXiv 2112.04426), author list, DeepMind affiliation and equal-contribution note
- Mistral 7B (arXiv 2310.06825)
- Mixtral of Experts (arXiv 2401.04088)