The global artificial intelligence industry has taken another historic leap forward as Nvidia announced plans to invest up to $100 billion in OpenAI, the creator of ChatGPT. This unprecedented partnership represents a powerful alignment between the world’s leading AI hardware provider and one of the most innovative AI research and development companies.

At the heart of the deal lies a dual commitment: Nvidia will supply OpenAI with its state-of-the-art data center GPUs and systems, while also taking a non-controlling equity stake in OpenAI. Unlike a traditional acquisition, this arrangement ensures OpenAI maintains its governance and mission-driven structure, while benefiting from Nvidia’s unmatched hardware capabilities. The collaboration is designed to supercharge OpenAI’s infrastructure, allowing it to build and train larger, more advanced models at scale.

According to reports, the partnership will deploy at least 10 gigawatts of AI computing power under Nvidia’s Vera Rubin platform. The first gigawatt of capacity is expected to be operational by the second half of 2026. This massive increase in computing resources will enable OpenAI to accelerate its research, improve existing products like ChatGPT and DALL-E, and potentially unlock new AI capabilities.

For Nvidia, the deal secures its role at the very center of the AI revolution. Already valued as one of the world’s most influential chipmakers, Nvidia gains not only revenue from hardware sales but also a strategic foothold in the software and model development side of AI. This hybrid approach strengthens its dominance against rivals while cementing its influence in shaping the future of artificial intelligence.

The implications of this deal are far-reaching. First, it accelerates the race toward ever-more powerful AI models, raising the bar for competitors such as Google DeepMind, Amazon, and Anthropic. Second, it intensifies debates around regulation and governance—with critics warning that such massive consolidation of compute power could pose risks to fairness, accessibility, and competition in the AI ecosystem. Additionally, the environmental footprint of deploying tens of gigawatts of compute capacity will bring fresh scrutiny to energy use, sustainability, and carbon impact.