OpenAI: 100 Billion-Dollar Supercomputer for
OpenAI and NVIDIA have announced a strategic partnership via a Letter of Intent to build at least 10 gigawatts of NVIDIA systems for the next generation of OpenAI models. NVIDIA intends to gradually invest up to 100 billion US dollars. The first gigawatt is expected to come online in the second half of 2026 on the Vera Rubin platform. This article examines the operational, energy-economic, and strategic implications of this alliance.
Quelle: Own depiction
OpenAI & NVIDIA Alliance Overview
On September 22, 2025, OpenAI and NVIDIA announced a strategic partnership. The goal is to build at least 10 gigawatts (GW) of NVIDIA systems. NVIDIA intends to invest up to 100 billion US dollars gradually, depending on the progress of the gigawatt buildout phases. This announcement was made via a Letter of Intent (LOI), a declaration of intent that outlines the scope and direction of the venture but is not yet a final contract.
The Vera-Rubin platform refers to NVIDIA's next data-center generation, designed specifically for training and inference of large AI models. The first gigawatt of these systems is planned to be deployed in the second half of 2026. The 10 gigawatts refer to the electrical connection capacity of the data centers, which will be equipped with millions of GPUs, and not to the computing power of individual end devices.
Agency reports describe the investment structure as two streams: OpenAI buys hardware, while NVIDIA acquires non-controlling stakes. The first 10 billion US dollars are expected to flow after finalization, as Reuters reports. The alliance complements existing infrastructure partnerships of OpenAI, including collaborations with Microsoft and Oracle, as AP notes. Previously, OpenAI had already announced a 4.5 GW expansion with Oracle as part of the “Stargate” program.
Operational & Strategic Implications
The alliance between OpenAI and NVIDIA is strategically motivated. OpenAI secures predictable, massive compute capacity for the development of its next-generation models. NVIDIA, in turn, secures demand for its systems and networks over the long term, creating a stable sales base for its advanced hardware. This shift toward "AI factories" – data centers planned, financed, and operated like industrial facilities – is a central aspect of this partnership.
Quelle: cdotrends.com
A schematic representation of a large server room illustrating the massive infrastructure for a 10 GW GPU cluster.
The COMPUTEX keynote recording by Jensen Huang provides further background on “AI factories” and NVIDIA's roadmap.
Fact Check & Clarifications
Evidence: There is a Letter of Intent in place. The goal is at least 10 GW of NVIDIA systems, and NVIDIA intends to invest up to 100 billion US dollars gradually. The first operation of a 1 GW package on the Vera-Rubin platform is planned for the second half of 2026, confirmed by NVIDIA News.
Evidence: Agency reports, such as Reuters, indicate hardware purchases by OpenAI and non-controlling NVIDIA stakes. The first 10 billion US dollars are to flow after finalization.
Unclear: Final contract terms, exact site distribution, precise GPU counts, and the energy mix remain open. The companies point to ongoing finalization (OpenAI, NVIDIA).
False / Misleading: The claim “The deal is signed and starts immediately” is incorrect. It is a LOI, with final contracts in preparation and a start of the first expansion phase from H2 2026 (NVIDIA News).
False / Misleading: “OpenAI replaces existing partners” is also incorrect. The alliance complements existing collaborations, including with Microsoft and Oracle (OpenAI).
Industry Reactions & Perspectives
Quelle: whileint.com
The exploded view of the NVIDIA GB200 Blackwell superchips, which form the technological basis for the next generation of AI infrastructures.
Reuters highlights potential antitrust scrutiny and the structure of cash-and-hardware purchases plus minority stake. AP links to ongoing OpenAI initiatives and mentions legal disputes shaping the environment. The Guardian summarizes the two transaction paths and the financial magnitude. The Verge highlights the status as the “preferred strategic compute and networking partner” and the 10-GW expansion.
Quelle: hardwareluxx.de
A data center corridor with tall server racks illustrating the physical infrastructure and density of computing power for future AI projects.
For businesses, this could ease GPU capacity constraints in the medium term, but only once ramp-up begins in 2026. It is prudent to plan realistically and monitor energy, cooling, and footprint requirements for your workloads (NVIDIA News). Operators and municipalities should coordinate gigawatt projects early with grid operators, heat-utilization concepts, and permitting authorities (DatacenterDynamics). Teams should evaluate providers not only by raw compute but also by energy efficiency, network topologies, and orchestration. Following primary sources for roadmaps and contract progress is essential (OpenAI, NVIDIA News).
Quelle: YouTube
The GTC keynote stream provides more technical background on the platform generation and the factory concept.
Future Outlook & Recommendations
The alliance lays out a clear roadmap: OpenAI gains predictable, very large compute access, and NVIDIA actively shapes the next infrastructure wave by anchoring demand. It is a LOI with an ambitious roadmap, slated to begin in 2026, and accompanied by energy and regulatory considerations.
Open questions concern the concrete sites of the 10 GW, the energy mix, and the use of waste heat. The companies have not yet named a final site plan; details are to follow with contract signing and project announcements. The response of regulatory authorities to the investment structure and potential conditions that could alter timelines remain to be seen. Reuters anticipates review steps. It is also unclear how parallel initiatives like “Stargate” will align in cadence and site selection. The 4.5 GW Oracle cooperation provides initial hints but is not replaced by this alliance (OpenAI).
Decision-makers today should follow primary sources, plan scenarios through 2027+, and tailor their own architecture early for efficiency, site conditions, and cost control (OpenAI, NVIDIA News).