A Blog post by Hugging Face on Hugging Face

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China's open-source AI ecosystem has shifted toward Mixture-of-Experts (MoE) architectures as the default choice, prioritizing cost-performance balance over maximum capability. Leading organizations expanded beyond text models into multimodal domains (video, audio, 3D), with growing emphasis on small models (0.5B-30B parameters) for practical deployment. Apache 2.0 became the standard license, reducing friction for production use. A significant strategic shift emerged toward hardware-first development, with models increasingly optimized for domestic Chinese chips (Huawei Ascend, Cambricon, Baidu Kunlun) in both inference and training. Companies are open-sourcing production-grade serving systems and infrastructure, moving competition from isolated model performance to full-stack ecosystem design.

Architectural Choices in China's Open-Source AI Ecosystem: Building Beyond DeepSeek

Mixture of Experts (MoE) as the Default Choice

<p>Perfect example of the flexibility – shift from the model oriented to the architecture and HW oriented approach to optimise costs and model availability for training on the domestic chips and even on the local systems.</p>
<p>I’m excited about the times, when a relatively small models will be trained by every SE for the company specific needs and used in the AI-enabled software. And this is in times when we must pay a lot of fee to be a members of the elite “AI golf club” of OpenAI, Anthropic, Google, and Co.</p>
