Artificial intelligence Venture

OpenAI Competitor Mistral AI Nabs $415M Round, Hitting $2B Valuation

Illustration of robot drawing in the air. (Generative AI)

AI startups apparently are going to end the year the same way they began it — raising huge amounts of cash.

Paris-based Mistral AI, an OpenAI and Anthropic competitor, is putting the final touches on a massive round of approximately $415 million that would value the company at $2 billion, per a Bloomberg report.

The round was first reported in October, with the round being around $300 million.

Per the new report, the round will include an equity investment from investors led by Andreessen Horowitz — which is expected to invest more than $200 million. Other investors in the round include General Catalyst, Lightspeed Venture Partners and Bpifrance.

In addition, both Nvidia and Salesforce 1agreed to contribute  convertible debt to the deal.

The raise comes just about six months after the startup — which is developing an open-source large language model — raised a seed round worth approximately $111 million led by Lightspeed Venture Partners.

More big money

The round is just the latest massive one raised by a competitor of OpenAI, who itself raised the largest U.S.-based startup funding round this year — a $10 billion deal from Microsoft.

San Francisco-based Anthropic raised several rounds throughout the year, totaling more than $2.6 billion, from investors including Amazon and Google.

In June, Palo Alto, California-based Inflection AI locked up a huge $1.3 billion round led by Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt and new investor Nvidia, which valued Inflection AI at $4 billion, according to Forbes. The startup is building what it says will be the “largest AI cluster in the world.”

In November, another European startup raised a big sum as Germany-based Aleph Alpha raised a $500 million Series B led by Innovation Park Artificial Intelligence, Bosch Ventures and the companies of Schwarz Group. Founded in 2019, Aleph Alpha allows companies to develop and deploy large language and multimodal models.

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Illustration: Dom Guzman

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