Mistral revenue tops $400 million as Europe contests U.S. AI rules

  • Mistral’s annualized revenue run rate exceeded $400 million, roughly 20 times the approximately $20 million recorded a year earlier.
  • The company raised €3 billion in a Samsung-led Series D round at a valuation of approximately €21 billion.
  • Mistral and other European AI companies opposed U.S. proposals for voluntary frontier-AI safety coordination and an antitrust waiver for joint safety work.

French AI startup Mistral has lifted its annualized revenue run rate above $400 million, roughly 20 times the approximately $20 million recorded a year earlier, according to the Financial Times. CEO Arthur Mensch has said the company aims to exceed $1 billion in recurring annual revenue by the end of 2026. Mistral raised €3 billion, or roughly $3.5 billion, in a Samsung-led Series D round earlier this month at a valuation above or approximately €21 billion; the transaction was Europe’s largest private technology fundraising and is intended to expand computing capacity and support larger AI models. Mistral is also building more of its own infrastructure, following an earlier $830 million data-center financing, while serving customers including Airbus, ASML and HSBC and more than 125 major clients, according to the company. The company’s commercial expansion is part of Europe’s effort to reduce reliance on U.S. companies including OpenAI, Microsoft, Google and Anthropic. Mistral and other European AI companies have challenged calls from Anthropic CEO Dario Amodei and other U.S. AI leaders for voluntary coordination to slow or manage frontier AI development, arguing that safety proposals and a proposed antitrust waiver for joint safety work could entrench established firms. Mistral instead promotes open-weight models that governments and enterprises can run, inspect and modify on their own infrastructure. The EU AI Act is already in effect with obligations tiered by system risk, but Europe remains constrained by scale: the EU controls less than 5% of global AI computing capacity, compared with roughly 75% for the U.S., according to a recent analysis.

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