French AI startup Mistral launched its new Mistral 3 family of open-weight models on Tuesday – a 10-model release that includes a large frontier model with multimodal and multilingual capabilities, and nine smaller offline-capable, fully customizable models.
The launch comes as Mistral, which develops open-weight language models and a Europe-focused AI chatbot Le Chat, has appeared to be playing catch up with some of Silicon Valley’s closed source frontier models. The two-year-old startup, founded by former DeepMind and Meta researchers, has raised roughly $2.7 billion to date at a $13.7 billion valuation – peanuts compared to the numbers competitors like OpenAI ($57 billion raised at a $500 billion valuation) and Anthropic ($45 billion raised at a $350 billion valuation) are pulling.
But Mistral is trying to prove that bigger isn’t always better – especially for enterprise use cases.
“Our customers are sometimes happy to start with a very large [closed] model that they don’t have to fine-tune…but when they deploy it, they realize it’s expensive, it’s slow,” Guillaume Lample, co-founder and chief scientist at Mistral, told TechCrunch. “Then they come to us to fine-tune small models to handle the use case [more efficiently].”
“In practice, the huge majority of enterprise use cases are things that can be tackled by small models, especially if you fine tune them,” Lample continued.
Initial benchmark comparisons, which place Mistral’s smaller models well behind its closed-source competitors, can be misleading, Lample said. Large closed-source models may perform better out-of-the-box, but the real gains happen when you customize.
“In many cases, you can actually match or even out-perform closed source models,” he said.
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