Mistral’s new 1T model aims to leapfrog closed and open rivals

Mistral AI released Mistral Large 4, a one-trillion-parameter multimodal model nicknamed Le Chonk, on Tuesday, positioning it as an alternative to both closed American models and open Chinese rivals. Mistral VP Science Pierre Stock said the model was trained on Mistral's own compute using only 4,000 NVIDIA GPUs, "two to three times less than our Chinese competitors," and that weights will be published in three weeks after safety testing; for now it is available only through a public guardrail endpoint. Mistral, which raised a Series D led by Samsung last month at a €21 billion ($24.39 billion) valuation, says ML4's optimized use cases include cybersecurity, finance, and chip design, with benchmark results still pending.

The race between open and closed AI is on, and Europe is still in the mix. On Tuesday, French AI lab Mistral AI https://mistral.ai/ has released Mistral Large 4 https://mistral.ai/news/mistral-large-4/ , a new large multimodal model aiming to leapfrog https://x.com/arthurmensch/status/2107196159181639904 both American and Chinese rivals — following what French president Macron has described https://x.com/emmanuelmacron/status/2097254072441045256 as “a third way in AI.” Amid a growing divide between closed models that can be unplugged https://techcrunch.com/2026/06/15/cybersecurity-vets-protest-dangerous-us-government-ban-on-anthropics-most-powerful-models/ and open models that are often made in China, Mistral is positioning ML4 as an alternative to both. Nicknamed Le Chonk in reference to its one trillion parameters, ML4 is definitely not small; but is not an open-weight model yet. For the time being, it can only be accessed via a public guardrail endpoint, but Mistral plans to make its weights available in just three weeks, after safety testing is complete. “In the meantime, we’ll work with trusted partners and governments to make sure that the open-source weights can be used to defend, but not to perform malicious attacks,” Mistral VP Science Pierre Stock told TechCrunch. Security concerns have been mounting in recent months, particularly among Mistral’s core audience https://techcrunch.com/2026/07/04/what-is-mistral-ai-everything-to-know-about-the-openai-competitor/ — enterprises and institutions. At the same time, an open-weight model is easier to audit, Stock said. Another important behind-the-scenes aspect is that ML4 was trained entirely on Mistral’s compute; using only 4,000 NVIDIA GPUs “which is two to three times less than our Chinese competitors, and significantly less than the closed source competitors,” Stock said. With benchmark results still pending, Mistral hopes ML4 will be best in class among open-weight models, especially outside of China, but not only, Stock said. Thanks to focused training, it could also outperform closed models in specific areas that are key to its customers, and where multimodal capabilities can add value. According to Stock, ML4’s optimized use cases include cybersecurity and finance, but also chip design, which is core to two of Mistral’s main backers — Dutch giant ASML, which led its Series C https://www.asml.com/en/news/press-releases/2025/ASML-Mistral-AI-enter-strategic-partnership , and Samsung, which led its Series D https://techcrunch.com/2026/09/08/mistral-raises-e3b-as-sovereign-ai-becomes-big-business/ last month at a €21 billion valuation about $24.39 billion . At the time, the company tried to convey https://mistral.ai/news/mistral-makes-sovereign-open-weight-ai-to-frontier/ that its decision to host Chinese models wasn’t a pivot into becoming a mere inference provider https://x.com/plbiojout/status/2088020438412824756 . With Le Chonk in its corner, the company believes it should still be considered a frontier lab as well.