en.Wedoany.com Reported - On June 10, OpenAI is reportedly in talks to lease a 10-gigawatt data center in Ohio, USA. The proposed plan involves a 20-year lease, and if the deal materializes, it would become one of OpenAI's largest AI infrastructure investments to date. Nvidia has also been in discussions to provide credit support for the project.
At the core of this potential lease arrangement is the further binding of OpenAI's rapidly growing model training and inference needs to hyperscale data centers and long-term power supply. A capacity of 10 gigawatts far exceeds the scale of traditional single data center projects, meaning the project involves not just server room leasing but also power development, transmission access, server clusters, liquid cooling systems, fiber optic networks, campus construction, and long-term capital structure. In recent years, OpenAI has continuously expanded its computing demands around ChatGPT, API services, multimodal models, and enterprise AI applications. Model scale, context length, inference call volume, and multimodal generation tasks are all driving up underlying infrastructure consumption. If the company chooses to lock in a large data center in Ohio with a 20-year lease, it indicates that AI enterprises are shifting from short-term cloud resource procurement to long-term computing power deployment more akin to energy and industrial infrastructure.
Ohio has become a key region for AI infrastructure expansion in the United States. The U.S. Department of Energy's previously announced PORTS Technology Campus plan also proposed building a 10-gigawatt-level data center and supporting power projects in the Piketon area of Ohio.
AI data center construction is reshaping the capital expenditure structure of technology companies. In the past, OpenAI primarily relied on cloud infrastructure like Microsoft Azure for computing power support. As training and inference demands continue to grow, relying solely on external cloud resources has become insufficient to fully cover cost control, delivery timelines, and architecture customization needs. Large model companies are now directly participating in data center site selection, chip procurement, energy infrastructure, and financing arrangements to gain greater computing power certainty. If Nvidia provides credit support for the project, it also reflects that AI chip suppliers are moving from hardware sales further into the infrastructure financing chain, binding top model customers through capital, GPU systems, and network solutions to ensure the deployment scale and supply rhythm of next-generation AI clusters.
Such hyperscale data centers also bring new constraints. A 10-gigawatt project requires long-term stable power, sufficient water resources or advanced cooling solutions, high-capacity fiber optic connections, local approvals, and community acceptance. The 10-gigawatt data center plan in Ohio has previously sparked discussions about natural gas power generation, transmission expansion, land use, and local load pressure. If OpenAI ultimately signs a long-term lease, it will need to address the matching issue between computing power construction and energy supply, and establish a sustainable balance among costs, energy consumption, carbon emissions, equipment depreciation, and model commercialization revenue.
These negotiations have not yet been formally confirmed, but the direction indicates that frontier AI competition is entering a comprehensive phase of "model capability + chip supply + data center + energy finance." In the coming years, competition among OpenAI, Anthropic, Google, Meta, Microsoft, and others will not only be reflected in model parameters and product experience but also in who can obtain long-term computing power faster, at lower cost, and more stably. If the 10-gigawatt project in Ohio materializes, it will serve as an important sample for observing the industrial expansion of AI infrastructure in the United States.
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