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TechCrunch AI更新于 10月13日 05:55

Mistral 发布 1T 参数多模态模型 Mistral Large 4,三周后开放权重

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

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法国 AI 实验室 Mistral AI 于周二发布 Mistral Large 4(ML4),这是一个 1 万亿参数的大规模多模态模型,昵称 Le Chonk,目前仅通过公开的 guardrail 端点访问,计划在安全测试完成后于三周内开放权重。Mistral 科学副总裁 Pierre Stock 表示,ML4 完全使用 Mistral 自有算力训练,仅动用 4000 张 Nvidia GPU,比中国竞争对手少两到三倍,也显著少于闭源竞争对手;其优化场景包括网络安全、金融和芯片设计,基准测试结果尚未公布。

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Mistral 用 4000 张 GPU 训练 1T 参数多模态模型,并计划三周后开放权重,可观察欧洲厂商在开源与闭源之间的第三条路线。

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当前显示原文,中文全文译文尚未就绪。

The race between open and closed AI is on, and Europe is still in the mix. On Tuesday, French AI lab Mistral AI released Mistral Large 4 (ML4), a new large multimodal model aiming to leapfrog both American and Chinese rivals — following what French president Macron described as “a third way in AI.”

Amid a growing divide between closed models that can be unplugged 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 1 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 — 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 , and Samsung, which led its Series D last month at a €21 billion valuation (about $24.39 billion).

At the time, the company tried to convey that its decision to host Chinese models wasn’t a pivot into becoming a mere inference provider . With Le Chonk in its corner, the company believes it should still be considered a frontier lab as well.

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