NVIDIA Invests CZK 50 Billion in CoreWeave to Boost AI Data Centers

NVIDIA Invests CZK 50 Billion in CoreWeave to Boost AI Data Centers

Ondřej Barták
Ondřej Barták
Entrepreneur and Programmer
28. 1. 2026
3 minutes reading · 6 views
NVIDIA Invests CZK 50 Billion in CoreWeave to Boost AI Data Centers

Nvidia, the global leader in artificial intelligence and accelerated computing, has announced a $2 billion investment (approximately CZK 50 billion) in CoreWeave. The investment took the form of a purchase of Class A shares at $87.20 per share. On January 26, 2026, Nvidia and CoreWeave announced an expansion of their long-standing collaboration. The goal is to accelerate the construction of more than 5 gigawatts of AI factories by 2030, supporting the widespread adoption of artificial intelligence on a global scale.

What Are AI Factories?

AI factories are massive data centers specifically designed to handle demanding tasks associated with artificial intelligence. Demand for AI computing power is growing exponentially, and the need for computing capacity has never been greater. CoreWeave specializes in providing cloud services optimized specifically for these demanding AI applications.

Jensen Huang, founder and CEO of Nvidia, said: "AI is entering its next phase and driving the largest infrastructure buildout in human history. CoreWeave's deep expertise in AI factories, platform software, and unmatched speed of execution are recognized throughout the industry. Together, we aim to meet the extraordinary demand for Nvidia AI factories—the foundation of the AI industrial revolution."

Details of the Expanded Collaboration

The collaboration between the two companies covers several key areas. CoreWeave will build and operate AI factories using Nvidia's state-of-the-art accelerated computing platform technology. Nvidia's financial strength will help CoreWeave accelerate the acquisition of land, energy resources, and buildings needed to construct these AI factories.

An important part of the agreement is also the testing and validation of CoreWeave's AI-native software and reference architecture, including the SUNK and CoreWeave Mission Control systems. The goal is to achieve deeper interoperability and potentially include these offerings in Nvidia's reference architectures for cloud partners and Nvidia's enterprise customers.

Deployment of the Latest Technologies

CoreWeave will deploy several generations of Nvidia infrastructure across its platform. This includes the early adoption of Nvidia computing architectures, including the Rubin platform, Vera processors, and Bluefield storage systems. Blackwell, Nvidia's latest architecture, provides the lowest-cost architecture for inference, which is essential for efficiently operating AI systems at scale.

Michael Intrator, co-founder, chairman, and CEO of CoreWeave, added: "From the very beginning, our collaboration has been guided by a simple belief: AI succeeds when software, infrastructure, and operations are designed together. Nvidia is the leading and most sought-after computing platform at every stage of AI—from pretraining to post-training—and Blackwell provides the lowest-cost architecture for inference. This expanded collaboration underscores the strength of the demand we are seeing across our customer base and the broader market signals as AI systems move into large-scale production."

Building Robust AI Infrastructure

This collaboration builds on CoreWeave's purpose-built cloud, software, and operational expertise. It expands proven capabilities that enable customers to run the most demanding AI workloads efficiently, reliably, and at scale. Both companies are committed to working together to address the growing global demand for artificial intelligence computing power and help shape the next era of technological progress.

The plan to build more than 5 gigawatts of AI factories by 2030 represents an ambitious vision that reflects both companies' belief in the continued growth and importance of artificial intelligence in the coming years. This infrastructure will be crucial to supporting the further development of AI applications, from large language models to advanced machine learning systems used across a wide range of industries.

Sources: cnbc.com and theinformation.com

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