OpenAI signs record Ohio data center lease with Nvidia backing up to $105 billion
OpenAI signed a 20-year lease with SoftBank subsidiary SB Energy for the "PORTS-Pike" campus in Ohio, securing approximately 8 gigawatts of IT capacity (10 gigawatts gross including cooling and infrastructure) Nvidia is backing the project with up to $105 billion in residual value guarantees for the first construction phase (4.25 gigawatts), becoming the exclusive chip supplier in return Jensen Huang introduced the "LPS" framework (land, power, shell), identifying these physical infrastructure e
Analysis
TL;DR
- OpenAI signed a 20-year lease with SoftBank subsidiary SB Energy for the "PORTS-Pike" campus in Ohio, securing approximately 8 gigawatts of IT capacity (10 gigawatts gross including cooling and infrastructure)
- Nvidia is backing the project with up to $105 billion in residual value guarantees for the first construction phase (4.25 gigawatts), becoming the exclusive chip supplier in return
- Jensen Huang introduced the "LPS" framework (land, power, shell), identifying these physical infrastructure elements—not chips—as the new primary bottleneck in AI buildout
- Nine major tech companies collectively hold around $3 trillion in off-balance-sheet AI commitments, with non-cancelable leases quadrupling to $1.2 trillion year-over-year
- The first 800 megawatts are scheduled to come online in 2028, with OpenAI's total commitments through 2030 estimated at roughly 12 gigawatts of Nvidia compute
Why It Matters
This deal marks a fundamental shift in how AI infrastructure is financed and built, with chipmakers like Nvidia moving beyond hardware supply into financial backstopping of data center real estate—a role previously reserved for cloud providers or sovereign wealth funds. The $3 trillion in off-balance-sheet commitments across the industry raises serious questions about financial transparency and risk assessment for investors, as traditional balance sheet metrics become increasingly unreliable indicators of corporate leverage and exposure.
Technical Details
- PORTS-Pike campus in Ohio sits partly on a former US Department of Energy uranium enrichment facility, drawing power from a 9.2-gigawatt gas plant owned by the US government and financed by Japan under a trade agreement
- Nvidia's guarantee structure: $105 billion covers residual asset value (not rent payments) for the first phase of 4.25 gigawatts; SB Energy must first find a replacement tenant and attempt to sell facilities before Nvidia covers any value shortfall
- GPU scale projections: Huang estimates ~1.5 million GPUs per system generation, generating $150–200 billion in revenue per generation; total OpenAI commitments through 2030 reach
12 gigawatts, potentially expanding to 16 gigawatts ($600 billion) if Nvidia exercises options on remaining capacity - Accounting treatment: Leases are only recorded once payments begin, and purchase commitments only when goods are delivered, meaning the $1.2 trillion in unstarted leases and $811 billion in Alphabet's purchase commitments (up from $332 billion in three months) remain invisible on balance sheets
- Nvidia originally sought a $250 billion guarantee but scaled back to $105 billion following investor pressure and a 5% stock drop
Industry Insight
- The rise of "LPS" as the critical bottleneck signals that AI competition is increasingly won or lost on energy access, land acquisition, and construction capacity—not just chip design—making energy infrastructure strategy a core competitive moat for AI labs
- The $3 trillion off-balance-sheet commitment problem suggests a coming reckoning in financial analysis; investors and analysts will need new frameworks to assess true leverage, as negative free cash flow (already reported by Alphabet and Amazon) becomes the norm rather than the exception
- Nvidia's evolution from chip vendor to infrastructure financier represents a strategic deepening of its moat—by underwriting data centers, it locks in exclusive supply relationships and captures value across the entire AI stack, from silicon to real estate
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