TLDRs;
- South Korea receives 13,000 Nvidia GPUs to expand AI infrastructure nationwide.
- Universities, startups, and public institutions will access high-performance AI resources.
- Power, cooling, and redundancy are crucial for running large GPU clusters.
- Government funding and policy support accelerate AI infrastructure development and innovation
South Korea has taken a major step toward strengthening its artificial intelligence (AI) capabilities with the arrival of its first batch of Nvidia graphics processing units (GPUs).
The shipment, totaling 13,000 GPUs, was purchased with a budget of 1.4 trillion won (approximately US$952.7 million) and includes several models, including Nvidia’s B200. This marks the opening phase of a broader initiative to build large-scale AI infrastructure across the country.
The program is part of a collaborative effort between Nvidia, the South Korean government, and leading corporate players to deploy 260,000 GPUs nationwide. The government plans to dedicate 50,000 GPUs to a sovereign national AI platform, while private companies such as Samsung Electronics, SK Group, and Hyundai Motor Group will each receive 50,000 units.
Naver, the country’s top search engine and technology platform, will acquire 60,000 GPUs to support AI research and operations.
Distribution targets research and industry
The GPUs are slated for deployment across universities, research institutes, startups, and public-sector organizations. Ministry officials emphasize that this distribution will accelerate both academic research and commercial applications of AI, enabling institutions to process complex data sets, train AI models, and innovate in various technology sectors.
By equipping these organizations with high-performance computing resources, South Korea aims to strengthen its position as a global AI leader.
Energy and cooling challenges remain
While the GPU rollout represents a significant advancement, technical hurdles remain. Operating tens of thousands of high-performance GPUs requires robust energy supply and advanced cooling systems. In September 2025, a fire at the National Information Resources Service, South Korea’s government data center operator, exposed vulnerabilities in the country’s centralized infrastructure.
Aging lithium-ion batteries burned for 22 hours, freezing 647 government services and requiring 170 firefighters to respond. The incident highlighted the critical need for redundancy and backup systems in large-scale AI operations.
Vendors positioned to support AI growth
The government’s push for AI expansion has opened opportunities for vendors specializing in data center infrastructure. Suppliers of liquid cooling systems, power distribution equipment, and battery monitoring technology are positioned to support South Korea’s AI projects.
Networking and system integration companies can bid for redundancy upgrades using N+1, 2N, and 2N+1 standards, ensuring uninterrupted operations. These investments will be crucial for preventing downtime and maximizing the efficiency of high-density GPU clusters.
Policy and funding accelerate AI deployment
South Korea’s 2026 budget strengthens AI development with a 19% increase in research and development funding and a 15% rise in support for industry, SMEs, and energy projects. The KRW 100 trillion National Growth Fund will provide public-private financing to boost AI infrastructure, backed by tax incentives, relaxed regulations, and power supply support.
The upcoming AI Framework Act, effective January 2026, along with its enforcement decrees, will guide the implementation of large-scale AI initiatives, creating a clear regulatory environment for both domestic and foreign firms.
The arrival of the first 13,000 Nvidia GPUs marks a pivotal moment in South Korea’s AI strategy. With robust infrastructure planning, strong policy support, and collaboration between government and private sectors, the nation is positioning itself as a leader in AI innovation, research, and industrial application. The successful deployment of these GPUs will serve as a foundation for future AI factories and cutting-edge computational projects.
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