Kimi K3: Open-Weight Trillion-Scale MoE for Agentic Intelligence

作者： Moonshot AI (2026)

领域

混合专家多模态应用

TLDR（中文）

约 2.8T 总参数、百亿级激活参数的 MoE 模型，开放权重后成为当时规模最大的开源权重模型，原生支持视觉与约 1M token 上下文，主打 Agentic 与多模态能力，是 2026 年开源权重追平闭源前沿的标志性工程之一。

TLDR (English)

A MoE model with ~2.8T total parameters and ~100B activated, at release the largest open-weight model ever. Natively multimodal with ~1M-token context, focused on agentic capability—one of the landmark 2026 engineering efforts in which open weights caught up with the closed frontier.

出现在这些文章里

• 预训练与 Scaling Law：模型怎么学
• Pretraining and Scaling Law: How Models Learn

同被引用

这些论文与本文出现在同一篇文章中

• Language Models are Few-Shot Learners Tom Brown et al. (2020)
• PaLM: Scaling Language Modeling with Pathways Aakanksha Chowdhery et al. (2022)
• DeepSeek-V4 Technical Report DeepSeek-AI (2026)
• Training Compute-Optimal Large Language Models Jordan Hoffmann et al. (2022)

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