Kimi K3与DeepSeek V4路线之争:原生多模态成中国前沿模型分水岭

Between Kimi K3 and DeepSeek V4: Why Native Multimodal Capability Defines the Next Phase of Chinese Frontier Models

精选理由

Kimi K3和DeepSeek V4现在走了两条路:一个搞原生多模态,一个纯文本硬扛。长任务里能不能看懂画面,差距会越来越大。

AI 摘要

Moonshot AI的Kimi K3、阿里Qwen3.8-Max和字节Doubao-Seed-2.1均采用原生多模态训练,而DeepSeek、智谱和腾讯混元仍坚持纯文本路线。在长程智能体任务中,视觉信息的实时参与成为决定性因素。这一差异将影响下一代模型在复杂环境中的表现。

原文 · pandaily

Between Kimi K3 and DeepSeek V4: Why Native Multimodal Capability Defines the Next Phase of Chinese Frontier Models

Moonshot AI Kimi K3, Alibaba Qwen3.8-Max, and ByteDance Doubao-Seed-2.1 commit to native multimodal training while DeepSeek, Zhipu, and Tencent Hunyuan stay text-only as vision-in-the-loop becomes decisive for long agent tasks.

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