English(EN) How to Run Mistral Large 4 Locally: 52B Active, Still Needs ~400GB of RAM

Mistral Large 4 发布，但权重和许可仍不明确

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-22 16:00

Mistral AI 发布了 Mistral Large 4，这是一个拥有 1.05 万亿参数的混合专家（MoE）模型，拥有 520 亿活跃参数，并被描述为开放权重。然而，截至 10 月 22 日，该模型的权重尚未提供下载，其 Hugging Face 存储库目前显示一个倒计时。本地运行 Mistral Large 4 大约需要 400GB RAM，性能估计表明由于其活跃参数数量的增加，其速度将比之前的模型慢。 AI

影响 Mistral Large 4 的发布，尽管发布延迟且许可不明确，但标志着大型 MoE 模型持续进步，并可能对现有顶级模型构成竞争。

排序理由 Mistral AI 发布了新模型 Mistral Large 4，并提供了其架构和性能的详细信息，尽管权重尚未发布。[lever_c_demoted from frontier_release: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

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AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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Signal score: 2 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Significant; Mistral AI 发布了新模型 Mistral Large 4，并提供了其架构和性能的详细信息，尽管权重尚未发布。[lever_c_demoted from frontier_release: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: model release; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 1 days old; Coverage has settled into its steady-state source set.

完整方法见我们的编辑标准。

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dev.to — LLM tag TIER_1 English(EN) · Alan West · 2026-10-22 16:00

How to Run Mistral Large 4 Locally: 52B Active, Still Needs ~400GB of RAM

<p>Mistral Large 4 is a 1.05 trillion parameter MoE with 52B active, and Mistral calls it open-weight. As of today, October 22, you can't download a single byte of it. The Hugging Face repo is a countdown page.</p> <p>So "can I run Mistral Large 4 locally?" has two answers. Today…

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How to Run Mistral Large 4 Locally: 52B Active, Still Needs ~400GB of RAM

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