China’s rapid advancements in artificial intelligence (AI), led by tech giants such as Alibaba, Baidu, Tencent, and iFlytek, are increasingly being driven by a strong emphasis on open-source collaboration. Models like Alibaba’s Qwen 3 series and Qwen 2.5, which are competitive against GPT-4 Turbo, are built on open frameworks that encourage developer contributions and integration across platforms. Qwen, termed as the open-source king, is also among the top three contributors to the global open-source AI ecosystem.
Baidu’s ERNIE series, including the widely adopted ERNIE Bot, and Tencent’s Hunyuan model similarly benefit from China’s broader AI ecosystem, where research institutions, startups, and industry players openly share tools, datasets, and model architectures. Likewise, iFlytek’s Spark 4.0 Turbo, which has also demonstrated exceptional benchmarks, reflects the success of this multistakeholder, open innovation strategy.
Unlike the more closed and proprietary model prevalent in the United States, China’s approach leverages state support and open-source infrastructure to accelerate collective progress, allowing these companies to build, iterate, and deploy foundation models at scale while fostering a uniquely domestic AI ecosystem. Such progress not only signals that China is scaling its AI capabilities by bypassing the reliance on Western supply chains, but also highlights Beijing’s ambition to carve out a unique role in shaping the future of global AI governance.
Instead of responding to U.S. attempts to block its access to critical technologies with retaliatory export control measures, China aims to adopt a decentralized approach that will secure its industrial base in the long term. In this context, China’s strategic shift toward open-source AI development resonates with the guerrilla economic strategy. This strategy is characterized by China’s efforts to find weaknesses in the global supply chains, deepen its ties with the Global South, and showcase its domestic innovation as a better alternative to Western technology – one that is more collaborative, decentralized, democratic, and accessible.
China’s framing of AI as a critical national priority is not only about boosting national competitiveness but also about showcasing its private sector, which appears to be thriving under state control. The evolving nature of China-U.S. AI competition is now centered around how the private sector is leading this innovation game, which approach countries will leverage to lead the next wave of AI innovation, and how global powers – even middle and emerging AI powers – will respond.
What strengthens this evolving policy position is China’s greater advocacy for its open-source model as an ideological tool to surpass the importance of Western technology. China is rapidly positioning itself as a leader in shaping international norms and frameworks of AI governance that align with the needs of small and emerging AI powers. President Xi Jinping, at last year’s G-20 summit, stated that AI development “should not be a game of rich countries.” China has repeatedly raised the issue of inclusive AI governance at global platforms like the United Nations through its AI Capacity-Building Action Plan and U.N. AI resolution. This approach helps China to strengthen its influence in the growing race to shape AI standards and frameworks.
China’s growing emphasis on open-source AI has enabled it to scale alternatives that are less reliant on Western supply chains and licensing regimes. This strategy not only enhances China’s technological resilience amid export controls but also positions it as a credible actor in promoting alternative norms and frameworks for global AI governance.
China’s AI diplomacy is aligned with its homegrown technology development model, and it may harm the existing influence of Western norms. The United States’ reliance on closed-source AI models, despite its liberal democratic ethos, may limit its ability to lead global conversations on inclusive and collaborative AI development.
However, this divergence in models reflects deeper structural differences. As AI governance debates intensify, China’s open-source exports could expand its normative influence, but questions remain about transparency, data integrity, and trust in these models. Additionally, while China’s larger claims about AI progress look promising, the DeepSeek story itself is not a true testament to China’s success. While the key details and data for model training remain hidden, the company’s compliance with national laws demands global scrutiny. Some European countries have already prohibited the platform for their users, citing privacy and data transfer risks.
Meanwhile, the United States’ challenge lies in balancing commercial interests with the need for global cooperation on open and responsible AI standards. Although Western technology conventionally claims to be a harbinger of liberal democratic principles, its export model is largely driven by corporate imperialist practices, often sucking resources and human labor from the Global South.
This evolving contest reveals that neither the China nor the U.S. model is absolute, and future leadership in AI governance may depend on each country’s ability to adapt and bridge these competing approaches. As both seem to reinforce their existing power structures and seek to preserve their ideological principles, a truly global AI development framework needs to be based on shared governance, responsible and equitable access, multilateral cooperation, and a balance between security and progress.