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Mistral AI, the Paris-based artificial intelligence start-up, has raised €600mn in new funding at a valuation of almost €6bn, just a year after the Microsoft- and Nvidia-backed company was launched as an unlikely challenger to OpenAI.
The investment, which has tripled the company’s price tag since December, is led by General Catalyst, alongside several of Mistral’s existing investors, including Lightspeed, Andreessen Horowitz, Factorial Funds, Bpifrance and BNP Paribas. Corporate backers include Nvidia, Salesforce, Samsung and IBM.
“We were told when we started . . . that this is a market that is never going to be disrupted,” Arthur Mensch, Mistral’s chief executive, told the Financial Times. “We showed that this wasn’t the case and we effectively disrupted the OpenAI business model.”
Yuri Milner’s DST Global joined Mistral’s latest round as a new investor, according to people involved with the deal. DST did not immediately respond to a request for comment.
Microsoft, which invested €15mn in February as part of a commercial partnership to offer Mistral’s products through its Azure cloud computing platform, did not participate in the new round.
The latest deal is the biggest yet for a start-up building large general-purpose AI models that is based outside Silicon Valley, as Mistral aims to grow from a European champion to a global contender with more than €1bn in financial firepower raised.
Investors are pouring huge sums into AI start-ups that are building large language models, which are sophisticated systems capable of producing high-quality text and imagery in seconds. Big Tech companies including Microsoft, Google, Meta and Amazon, meanwhile, are ploughing tens of billions of dollars into computing infrastructure to build their own competing systems.
Mistral’s latest funding is made up of €468mn in equity and €132mn in debt and values the company, which was founded in mid-2023, at €5.8bn including the new capital raised, according to people close to the company.
Its co-founders, Timothée Lacroix, Guillaume Lample and Mensch — a trio of French AI researchers who previously worked at Google’s DeepMind and Meta — remain majority shareholders.
Mensch said that Mistral had used a “little more than 1,000” of the high-powered graphics processing units chips needed to train AI systems and spent “just a couple of dozen millions” of euros to build products that can rival those built using much bigger budgets by some of the richest companies in the world, including OpenAI, Google and Meta.
“We seem to be doing very different calculations” of the costs needed to build large AI models to the likes of OpenAI chief Sam Altman, said Mensch.
The French company’s latest round comes two weeks after Elon Musk raised $6bn for his start-up xAI, as rivals take aim at ChatGPT developer OpenAI’s head start, which is fuelled by $13bn in backing from Microsoft.
Mistral, which has been lauded by French President Emmanuel Macron as an example of how a new generation of European start-ups can compete with the biggest US tech companies, raised €105mn in one of Europe’s largest-ever seed rounds when it was just a few weeks old in June last year. Its value jumped to €2bn in December.
“The capital efficiency of the company is really outstanding,” said Jeannette zu Fürstenberg, who leads General Catalyst’s European business, adding that Mistral had spent “the smallest possible fraction” of what its rivals had to build competitive AI models.
“It really is very, very impressive how nimbly this team has operated from a financial standpoint and what they have achieved,” she added.
Mensch said that Mistral had opted to raise more capital now after receiving inbound interest from investors to scale up its commercialisation efforts as well as to buy more computing resources. “It remains a capital-intensive market,” he said. “The more [computing] capacity we have, the more people we can get into our team . . . to break the barriers of artificial intelligence.”
The AI start-up has about 60 staff, including 45 in France, 10 in the US and five in the UK, with about three-quarters of those working on product development and research.
Its technology differs from OpenAI because many of its AI systems are available as “open source” software, meaning its source code is available for anybody to examine or customise.
Mensch argues that this makes it more appealing to large corporate customers who do not want to share their data or be dependent on a large US provider for a technology that proponents claim could be as transformational as the internet or the smartphone.
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