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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

Primary sourcepandaily@[email protected] (Pandaily)
Blog/Media· 7 sources
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Why we picked it

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。

Moonshot AI的Kimi K3、阿里Qwen3.8-Max和字节Doubao-Seed-2.

Body

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。

Original · 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.

Industry Coordinates & Source Verification

This report is categorized under AITOP's "Models" desk, focusing on China's AI industry and domestic foundation model ecosystem. Within our cross-regional analytical framework, it directly maps to US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Kimi K3, DeepSeek V4, 多模态, 智能体.

Primary source verification: published directly by pandaily with first-party authority. Cross-source corroboration: 7 independent sources have covered this development (including IT之家, Decoder, Nathan Lambert: Interconnects), confirming industry-wide signal strength.

#Kimi K3#DeepSeek V4#多模态#智能体

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