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Mistral 开源万亿参数模型 Mistral Large 4 权重,主打网络安全

原标题:Mistral releases weights for its trillion-parameter AI model, targeting cybersecurity

Mistral 发布万亿参数开源模型 Mistral Large 4(ML4,昵称 Le Chonk)的权重,企业和政府可自行下载部署,权重已上线 Hugging Face 并提供 API。公司称其性能可比肩开源模型 GLM-5.3,且每任务少用 47% 的 token,并宣称在 Artificial Analysis 的 Coding Agent Index 上超过所有开源模型;Mistral 高管称开源权重可让机构本地部署、自主掌控网络安全防御能力。

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原文给出 ML4 权重开放的具体卖点和与 GLM-5.3 的对比数据,读者可据此权衡开源自部署的性价比。

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原文

French AI company Mistral has released the weights for its trillion-parameter open source AI model Mistral Large 4 (ML4), allowing businesses and governments to download and deploy the system themselves. Nicknamed “Le Chonk,” the model was first introduced earlier this month.

The release comes as competition between open-weight AI developers like Mistral and closed-model providers like OpenAI and Anthropic heats up, with the former arguing that businesses and governments shouldn’t have to rely on outside AI companies for access to advanced capabilities. That argument may hold more weight in cybersecurity, where organizations want more control over their data and systems.

Or, as Mistral’s CEO, Arthur Mensch, explained, AI should “be a tool for empowerment, not dominance.” With Chonk, Mistral doubles down on that position, arguing that it’s able to achieve “state-of-the-art performance” at a “fraction of the compute and capital committed by closed labs.”

The release of the model’s weights — the numerical training that animates the system — ensures that other companies and government agencies will now be able to deploy ML4 for their own purposes.

Mistral says that its model is comparable in terms of performance with a Chinese open-weight competitor, GLM-5.3, which was previously considered one of the best open-weight models in the world — particularly when it comes to cyber work. However, Mistral’s model uses 47 percent fewer tokens per task, making it significantly more economical than GLM-5.3.

The company also claims that the model outranks all other open models when it comes to agentic coding tasks on Artificial Analysis’ Coding Agent Index, an AI benchmarking site.

“Amid growing cyber threats, ML4 brings state-of-the-art sovereign cyber defense capabilities to enterprises and governments globally,” the company said Thursday. “Enterprise and public sector institutions can now download, deploy, and own frontier AI to detect, analyze, and respond to threats across code and IT infrastructure.”

The weights for ML4 are being made available on Hugging Face and via its API.

Pierre Stock, Vice President of Science at Mistral, told TechCrunch that the release of the model’s weights meant that organizations will have more control over how they use AI to defend themselves.

“Concretely, it means that, for instance, as a business company or as a government, you’re able to have access to frontier intelligence to defend yourselves against cyberattacks. Access that can’t be cut off by definition because the model is open-weighted,” he said.

Stock added that the model could be used to “identify, coordinate, and respond in real time to major security incidents, and that the open sourcing means that companies can deploy this model on-prem in their own ecosystem.

While advances in AI cybersecurity are helping security professionals to find bugs at a much higher rate than before, Stock continued, he believes it’s important for companies to “provide [this same] capability to everyone…as soon as possible to ramp up and to strengthen the ecosystem,” given that “some malicious actors might try to actually leverage their own technology to attack.”

Separately, Stock addressed concerns about recent incidents involving rogue AI agents, acknowledging the risks but cautioning against overreacting.

“We don’t want to fearmonger people. We think it’s a problem that is solvable. It’s a hard problem to have good security,” he said.

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Lucas is a senior writer at TechCrunch, where he covers artificial intelligence, consumer tech, and startups. He previously covered AI and cybersecurity at Gizmodo. You can contact Lucas by emailing [email protected].

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事件综述

Mistral 发布开源万亿参数多模态模型 Mistral Large 4(Le Chonk)

2026 年 10 月 29 日,Mistral 发布开源权重多模态大模型 Mistral Large 4(昵称 Le Chonk),权重上线 Hugging Face。模型为总参数约 1 万亿(激活参数约 49B–52B)的 MoE 架构,支持 1M token 上下文、文本与图像输入及 160+ 种语言,在 Mistral 位于欧洲的自有数据中心用 3,800 块 NVIDIA Grace Blackwell GPU 训练,采用修改版 MIT 许可(Mistral Ecosystem Open-Weight License),商用需另行授权。定价为输入 $0.70/M、输出 $2.10/M token,支持 Low/Medium/High 三档推理模式,可通过 Hugging Face、Microsoft Foundry、OpenRouter、NVIDIA NIM 获取;Hugging Face 提供 transformers 和 llama.cpp 的 day-0 支持及量化版本。官方称其在 FrontierCode 开放模型中排名第一、Terminal-Bench 4.0 得分 41%(此前预览版为 28%)、Coding Agent Index 得分约 48–49.8%,与 GLM-5.3 基本持平且少用 47% token,但整体智能指数(26 分)仍低于 DeepSeek V4.1 Flash 和 GLM-5.3(均 32 分)。网络安全方向上,官方称恶意请求平均拒绝率 96.6%,并经 CrowdStrike、Cloudflare 等厂商测试;早先报道称 Artificial Analysis Cyber Index 得分 82%(该指数已报告最高分),Mistral 官方博客则称该指数得分为 51%,两者不一致。10 月 30 日,Mistral 宣布完成三周集中训练的更新版本,第三方评测称其编码能力位居开源模型第二。

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