China’s AI Acceleration Intensifies Competition with US, Sharpens Strategic Choices for South Korea
One year after DeepSeek unsettled the global AI landscape, signaling China’s narrowed gap with the US in generative artificial intelligence, the question has evolved. Now, the focus is on whether China is poised to define the very architecture of the next AI order.
“The difference between adopting AI and defining its architecture is huge,” stated Ahn Jun-mo, a professor of public administration at Korea University. “Countries that set the standards wield the power to shape entire ecosystems, while others operate within those established frameworks.”
From Symbolic Breakthrough to Sustained Momentum in AI Development
What began as a symbolic breakthrough has solidified into significant structural momentum. Over the past year, Chinese AI developers have accelerated their model release cycles, expanded open-weight ecosystems, and shifted competition from benchmark scores to factors like scale, deployment, and overall influence.
The debut of DeepSeek was widely seen as a geopolitical milestone, proving that China could forge a viable path forward despite tightening US semiconductor restrictions. By utilizing widely accessible research components – including Google’s SigLIP vision encoder, OpenAI’s Triton framework, and Stanford’s FlashAttention – Chinese teams reduced development time and conserved crucial computing resources. Reinforcement learning was also deeply integrated, improving efficiency in the face of hardware constraints.
Leading AI models are now being updated every one to two months. Moonshot AI’s Kimi K2.5 uses distributed reasoning agents. Alibaba’s Qwen3-Max-Thinking shows strength in complex reasoning benchmarks. Zhipu AI’s GLM-4.7-Flash surpassed 1 million downloads on the AI research community platform, Hugging Face, within two weeks. Baidu’s Ernie 5.0 reports over 200 million monthly active users.
The AI Performance Gap Narrows, but Leadership Differs
Even US leaders are acknowledging this shift in the AI landscape. Google DeepMind CEO Demis Hassabis recently commented that Chinese frontier models are performing much closer to US systems than previously anticipated, with performance gaps now measured in months rather than years.
Shin Jin-woo, ICT endowed chair professor at KAIST, offered a similar perspective. “Based on the time needed to absorb and reproduce publicly available technologies, the performance difference is closer to six months,” he stated. However, he emphasized that ecosystem leadership is a distinct issue. “China already possesses the technological capabilities to lead key aspects of the industry. This is a step beyond simply matching benchmark scores.”
While structural advantages still favor the US in GPU clusters, AI alignment research, and global cloud infrastructure, the competitive landscape is undoubtedly evolving.
“The competition is shifting away from isolated benchmark scores toward overall ecosystem control,” an AI industry expert noted. “Scale and capital mobilization will become more important than marginal performance gains.”
The numbers reflect this transition. Downloads of Chinese open-weight AI models on Hugging Face surged dramatically from approximately 1 million in January 2024 to over 818 million by January 2025.
A report released in November by MIT and Hugging Face revealed that Chinese-developed models accounted for 17 percent of newly generated open-model downloads on the platform over the past year, surpassing the 15.8 percent share held by US-developed models. This marked the first time that Chinese models have outpaced their American counterparts in this key metric.
China’s AI market was valued at around 900 billion yuan ($131 billion USD), with projections estimating a growth to $1.4 trillion USD by 2030. Alibaba has committed 380 billion yuan in investment towards AI and cloud infrastructure over the next three years. Furthermore, China leads in global AI patent filings, particularly in areas such as computer vision, natural language processing, and speech technologies.
These developments align with long-term strategic state planning. AI was designated as a strategic industry by China in 2016, followed by the 2017 Next Generation Artificial Intelligence Development Plan, which established a target of achieving global AI leadership by 2030.
For South Korea, China’s rapid AI acceleration goes beyond simply regional developments; it represents a significant structural shift.
While South Korea maintains strengths in semiconductors, telecommunications, and applied AI services, it currently lacks a globally dominant foundation model capable of shaping open AI ecosystems. According to International Data Corp. and Invest Korea, the South Korean domestic AI market is projected at 3.4 trillion won ($2.31 billion USD) in 2025 – a fraction of China’s market scale.
“The difference between adopting AI and defining its architecture is huge,” Ahn reiterated. “Countries that establish the standards have the power to shape entire ecosystems.”
The central question for South Korea is therefore not whether it can effectively utilize AI, but whether it intends to shape any aspect of its foundational AI architecture – or instead operate within the standards established elsewhere.
Just one year ago, DeepSeek was perceived as an unexpected challenger in the AI landscape.
Today, China’s AI expansion appears less like a series of isolated events and more like a systemic trend – anchored in scale, strategic policy alignment, and expanding ecosystem reach.
The AI race is no longer primarily defined by benchmark supremacy. It is increasingly about which AI models become embedded first, which ecosystems attract the most developers, and which AI infrastructures evolve into the default standards.
yeeun
