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China's open-source AI models surpass 10 billion downloads worldwide

China's open-source AI models have surpassed 10 billion downloads worldwide, with Chinese models making up 41% of downloads on Hugging Face. The country holds 60% of global AI patents and has over 6,200 AI companies.

1 min read
IT and development

China's open-source AI models hit 10 billion downloads worldwide

Chinese developers have released open-source large language models that have been downloaded more than 10 billion times globally, according to recent data. The country now holds 60% of worldwide AI-related patents, the largest share of any nation.

The domestic AI sector has grown substantially. China has more than 6,200 AI companies, with the core industry valued at over 1.2 trillion yuan ($165 billion) in 2025.

Recent model releases target practical applications

DeepSeek released its V4 model last week. Alibaba's Qwen, Moonshot's Kimi, and Tencent's Hunyuan also received updates in the same period.

Development priorities have shifted. Companies now focus on reducing computing costs, scaling industrial applications, improving specialized capabilities, and optimizing models for edge devices.

Open-source models reshape the global AI ecosystem

Chinese models accounted for 41% of large language model downloads on Hugging Face, the world's largest open-source AI platform, over the past year. China has become one of the fastest-growing regions for open-source model development.

Open-source models reduce barriers for developers. Businesses, startups, and independent programmers can build customized applications without creating AI systems from scratch, cutting both development costs and adoption hurdles.

Previously, advanced models were controlled by a small number of closed platforms where companies purchased access. Now, with mature open-source options, organizations can build secondary applications using their own data and industry expertise.

Practical use cases expand beyond chatbots

The open development approach is moving AI adoption beyond conversational interfaces. Manufacturing, energy, transportation, and finance sectors now deploy these models as productivity tools rather than experimental technology.

This shift reflects how generative AI and LLM development has matured. Developers can now tailor models to solve specific business problems instead of adapting workflows to fit general-purpose systems.

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