The deal that started as a $250 billion rumor in late July has now been officially closed. On August 17, Nvidia confirmed it will back up to $105 billion in financing to support a massive new AI data center campus in Ohio that OpenAI will lease for the next 20 years. It is the largest AI infrastructure commitment in history.

What Was Announced

The campus is located at the PORTS-Pike Technology Campus in Pike City, Ohio. SB Energy, the SoftBank-backed developer, will build and manage the facility. OpenAI has secured rights to up to 8 gigawatts of computing capacity, with the first 800 megawatts expected to come online in 2028.

Nvidia’s role goes beyond the guarantee. The chipmaker is also investing $1.5 billion directly in SB Energy, the company responsible for construction and operations. SB Energy and SoftBank together will invest at least $4.2 billion in regional grid infrastructure to support the site’s power needs, which will scale to 10 gigawatts at full build-out.

OpenAI says the project will support 35,000 construction jobs through 2032 and create 2,500 long-term positions once operational.

From Talks to Closure

When Bloomberg first reported in late July that Nvidia was in discussions to provide a $250 billion guarantee for this campus, the scale seemed almost implausible. The final figure of $105 billion is still the largest guarantee of its type ever arranged by a chip company. Analysts note the reduction from $250 billion reflects a restructured deal where SB Energy’s own balance sheet absorbs more of the lease obligation and where the campus build-out has been phased more conservatively.

The deal structure is a conditional lease and power payment guarantee. Nvidia is not spending $105 billion outright. Rather, it is providing credit support that allows SB Energy to secure the financing to build and operate the campus at the scale OpenAI requires. Without a guarantor of Nvidia’s standing, a project of this magnitude would not be financeable in a normal commercial real estate market.

Why This Matters for Business

The implications extend well beyond OpenAI and Nvidia.

Compute supply is being locked in at decade-long horizons. With 800 megawatts arriving in 2028 and the campus scaling to 8 gigawatts over time, a significant portion of the world’s most powerful AI compute will sit on one campus in Ohio. Businesses that rely on OpenAI’s API products and cloud-delivered AI capabilities are, in effect, building their operations on top of infrastructure being planned right now.

The infrastructure gap is real. One of the consistent constraints on AI deployment for enterprise teams has been capacity. Long queue times, model throttling, and pricing volatility all trace back to compute scarcity. Projects of this scale are how the industry closes that gap, though the timeline of 2028 for the first phase means near-term constraints remain.

Nvidia has become infrastructure, not just hardware. By providing financing guarantees alongside chips, Nvidia is moving into a role that looks more like a bank or a utility than a component supplier. That shift in the company’s risk profile and its relationship with customers is something enterprise buyers and the industry at large are still working out. AMD is following a similar trajectory: its recent $5B partnership with Anthropic includes 2GW of Instinct GPU commitments alongside an equity stake — another sign that compute suppliers are becoming long-term co-investors in AI deployments, not just chip vendors. Ohio is becoming an AI hub. The concentration of this facility, alongside existing hyperscaler investments in the Midwest, is reshaping the geography of AI infrastructure. Data sovereignty, latency, and energy access will drive more of these decisions in the coming years.

What’s Next

The first 800 megawatts of capacity is not arriving until 2028. Between now and then, the practical question for enterprise teams is how current AI capacity constraints affect their own roadmaps. The pipeline being built in Ohio is part of the long-term answer. Planning for AI-dependent workflows over a multi-year horizon requires accounting for the fact that compute availability and pricing will look materially different by the end of the decade.

For context on where AI infrastructure is heading and what it means for how businesses access and budget for AI capability, this deal is worth watching closely.

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