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

China's open-source AI ecosystem has undergone significant transformation since the "DeepSeek Moment" in January 2025, with a focus on architectural and hardware choices that reflect a strategic shift toward building comprehensive AI systems. The widespread adoption of Mixture-of-Experts (MoE) architectures among Chinese models underscores the emphasis on cost-effective, flexible, and sustainable AI solutions. The ecosystem has expanded beyond text models to include multimodal and agent-based systems, fostering the development of reusable system-level capabilities. Small models have gained popularity for their ease of integration and compliance with local requirements, while large MoE models serve as "teacher models." The adoption of permissive licenses like Apache 2.0 has facilitated the utilization and deployment of open-source models. Moreover, a shift from model-first to hardware-first approaches has led to integration with domestic AI chips for training and inference, highlighting China's focus on optimizing AI performance within its hardware constraints. This evolution signifies a move from isolated model optimization to creating a robust open-source ecosystem, where system design and integration are now central to competitive advantage.