OpenAI vs. Google: The AI Hardware Battle
OpenAI relies on Nvidia’s GPUs, facing the “Nvidia tax,” which results in gross profit margins around 80%. This steep markup pressures OpenAI’s profitability. In contrast, Google, which began developing its own tensor processing units (TPUs) in 2015, operates these more cost-effectively, estimating costs 20% lower than those reliant on Nvidia technology. In April 2025, OpenAI shifted to Google’s TPUs for efficiency, reducing dependency on Nvidia.
While Google’s TPUs outperform Nvidia’s GPUs in deep learning applications, offering superior speed and energy efficiency, GPUs remain versatile for tasks like speech and image recognition. OpenAI seeks to mitigate costs through partnerships and potential chip designs, but Google’s vertical integration allows it to avoid external supplier costs effectively. Despite current disadvantages, OpenAI aims for significant growth, projecting $125 billion by 2029, hinting at a competitive AI landscape.
