Mistral AI nears $2B valuation — less than 12 months after founding

  • 16:21 - 06/12/2023
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Mistral AI nears $2B valuation — less than 12 months after founding



European contributions might have been a little late to join the generative AI investment party, but that does not mean they will not end up rivalling some of the earlier North American frontrunners. According to people familiar with the matter, Mistral AI, the French genAI seed-funding sensation, is just about to conclude the raising of about €450mn from investors.


Unlike Germany’s Aleph Alpha who just raised a similar sum, most investors come from beyond the confines of the continent. The round is led by Silicon Valley VC firm Andreessen Horowitz, and also includes backing from Nvidia and Salesforce.


Sources close to the deal told Bloomberg that Andreessen Horowitz would invest €200mn in funding, whereas Nvidia and Salesforce would be down for €120mn in convertible debt, although this was still subject to change. If it goes through, this would value the Paris-based startup at nearly $2bn — less than a year after it was founded.


Mistral AI was one of the few European AI companies to participate in the UK’s AI Safety Summit held at Bletchley Park last month. The generative AI startup released its first large language model (LLM), Mistral 7B, under the open source Apache 2.0 licence in September.


Targeting dev space with smaller size LLMs


The key thing that sets Mistral apart is that it is specifically building smaller models that target the developer space. Speaking at the SLUSH conference in Helsinki last week, co-founder and CEO Arthur Mensch said this was exactly what separates the philosophy of the company from its competitors.


“You can start with a very big model with hundreds of billions of parameters — maybe it’s going to solve your task. But you could actually have something which is a hundred times smaller,” Mensch stated. “And when you make a production application that targets a lot of users, you want to make choices that lower the latency, lower the costs, and leverage the actual populated data that you may have. And this is something that I think is not the topic of our competitors — they’re really targeting multi-usage, very large models.”


Mensch, who previously worked for Google DeepMind, added that this approach would also allow for strong differentiation through proprietary data, a key factor for actors to survive in the mature application market space.


Mistral AI and the reported investors have all declined to comment on the potential proceedings.

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