ByteDance and other Chinese tech firms dominate local consumer AI market: report

A new report shows major Chinese tech firms dominating the consumer AI market. ByteDance-owned Doubao remains the top consumer AI app in the country, with DeepSeek's namesake chatbot in second place.

A report from QuestMobile underscores the dominance of Chinese Big Tech firms in the domestic consumer AI app market, thanks to their large user bases and robust AI ecosystems. ByteDance-owned Doubao holds the top spot as the country's leading consumer AI app, with DeepSeek's chatbot securing second place.

The rankings highlight advantages for giants like Alibaba, Ant Group, Tencent, and ByteDance. Other notable apps include Qwen, Kimi, Moonshot AI's Yuanbao, and AI features tied to Douyin and TikTok. While international products like ChatGPT are referenced in keywords, local apps lead the market.

Published on December 24, 2025, the report covers terms such as Ant A-Fu, Alibaba Cloud, WeChat, and Weixin, illustrating the rapid growth of China's AI sector.

Mga Kaugnay na Artikulo

In 2025, artificial intelligence is quietly transforming daily life in China, from smart homes to wearable devices and voice shopping. Executives from JD.com and Alibaba highlight surging consumer demand, with AI features now essential for many products. Experts view this as smart living moving from concept to mainstream adoption.

Iniulat ng AI

China captured nearly 90% of global humanoid robot sales in 2025, with domestic firms Unitree and Agibot topping the charts. American companies, including Tesla, sold far fewer units despite ambitious targets. This early dominance mirrors China's strategy in electric vehicles, bolstered by state support and supply chains.

Despite concerns over an AI investment bubble, investors in Taiwan remain committed to the technology. The island nation shows no signs of worry about potential overvaluation in the sector.

Iniulat ng AI

Hangzhou-based startup DeepSeek has not announced plans for its next major AI model release, but its technical papers suggest potential advances. The papers highlight how AI infrastructure innovations could drive efficiency and scale up model performance.

 

 

 

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