OpenAI has unveiled an audacious internal roadmap to build 250 gigawatts (GW) of data center capacity by 2033, a scale equivalent to 250 nuclear power plants and roughly 25% of the current U.S. total installed power generation (1,200 GW). Disclosed in a September 29, 2025, internal memo from CEO Sam Altman, this “astronomical” ambition aims to secure the compute power needed for artificial general intelligence (AGI), outpacing rivals like Google and Meta in the $500 billion AI infrastructure race. The plan builds on the $500 billion Stargate project, with the first site in Abilene, Texas, already operational and five more announced, but scaling to 250 GW could cost $12.5 trillion at current nuclear plant prices ($50 billion per GW).
For AI enthusiasts, energy experts, and investors in the $1 trillion data center market, OpenAI’s target—starting from 2 GW by end-2025—highlights the voracious power demands of next-gen models, potentially rivaling India’s entire electricity consumption (1,200 GW projected for 2038). Amid U.S. policy pushes for AI leadership, this blueprint could create hundreds of thousands of jobs but strain global energy grids. Let’s dissect the plan, partnerships, and feasibility.
The 250GW Roadmap: From 2GW in 2025 to AGI-Scale Compute
Altman’s memo outlines a phased buildout to maintain OpenAI’s edge: 2 GW by December 2025, scaling exponentially to 250 GW by 2033 via custom superclusters and nuclear revival. This dwarfs Microsoft’s current 5 GW cloud capacity and reflects the exponential needs of models like GPT-5, which could require 100x more compute than GPT-4.
Phased targets:
| Year/Phase | Capacity (GW) | Key Milestones | Cost Estimate ($T) |
|---|---|---|---|
| End-2025 | 2 | Abilene site online; Nvidia partnership | 0.1 |
| 2026-2028 | 10-50 | Stargate’s 5 new sites; Oracle/SoftBank builds | 0.5-2.5 |
| 2029-2033 | 250 | 250 nuclear-equivalent plants; global sites | 12.5 |
The Stargate initiative, a $500 billion collaboration with Oracle, SoftBank, and MGX, anchors this: The Abilene flagship (1 GW potential) went live in June 2025, with expansions in Texas, New Mexico, Ohio, and two SoftBank-led sites. A September 23 Nvidia partnership adds 10 GW of GPU systems starting 2026, complementing Microsoft’s Azure credits.
Drivers: AGI Ambition and the AI Power Crunch
OpenAI’s scale-up addresses the “compute bottleneck”: Training GPT-5 could demand 100x GPT-4’s energy (10 GWh), per estimates. Altman stressed: “We must maintain our lead against better-resourced companies,” amid U.S. policy incentives like the CHIPS Act’s $52 billion for domestic fabs.
Energy realities:
- Nuclear Revival: Plans revive dormant plants; one GW nuclear unit costs $50 billion, powering 750,000 homes.
- Job Creation: 25,000 onsite roles per site, totaling hundreds of thousands, aligning with Trump’s AI leadership push.
- Global Scale: Sites in Texas (Abilene, Shackelford, Milam), New Mexico (Dona Ana), Ohio (Lordstown), and Midwest undisclosed.
Challenges: Grid strain (10 GW equals 10 nuclear reactors) and $12.5 trillion costs could face regulatory hurdles.
Implications: A $12.5 Trillion Power Play for AI Dominance
OpenAI’s 250GW data center goal by 2033 could eclipse India’s 2038 power demand (129 GW) and create a U.S. AI monopoly, per Business Korea. For investors, it’s a boon for Nvidia ($500B systems) and Oracle; energy firms, a revival catalyst; policymakers, a jobs/economy windfall but emissions risk.
Critics warn of feasibility: Building 250 plants in eight years defies logistics, potentially delaying AGI timelines. Yet, with Stargate’s $400 billion over three years, OpenAI leads the charge.
Conclusion: OpenAI’s 250GW Moonshot – Powering the AGI Era
OpenAI’s plan to build 250GW of data centers by 2033 is a $12.5 trillion wager on AI supremacy, scaling from 2GW in 2025 via Stargate’s nuclear-fueled sites. If realized, it could power superintelligence but strain global grids— a bold vision where compute meets geopolitics. CNBC
