NVIDIA has launched the "AI Computing Partnership Program," quietly evolving from a chip seller into the "central bank" of the AI computing ecosystem by offering financial guarantees to emerging cloud service providers in exchange for revenue sharing. Under the agreement, if a cloud provider cannot find enough AI developers to rent its computing capacity, NVIDIA will repurchase its unsold GPU capacity at a predetermined price and take a share of the revenue. Companies such as Sharon AI and Firmus have already joined the program. This move lowers the financing barrier for emerging cloud providers, expanding NVIDIA’s customer base, while also enabling direct participation in downstream profit distribution through revenue sharing. The strategy also aims to reduce reliance on major clients like Amazon, Microsoft, and Google. NVIDIA has invested billions of dollars in equity stakes and capacity guarantees to build a multi-layered system of aligned incentives.Article author and source: Wall Street Journal
NVIDIA is transforming its strong balance sheet into market leverage by providing financial backing to emerging cloud service providers in exchange for revenue sharing, quietly evolving from a chip seller into the "central bank" of the AI computing ecosystem.
On July 1, according to tech media The Information, NVIDIA is providing financial guarantees to young cloud service providers that rent out their GPUs—should these companies fail to secure enough AI developers to lease the computing power, NVIDIA will repurchase the unused GPU capacity at an agreed-upon price.
In exchange, NVIDIA will receive a percentage of revenue from these cloud providers, with the share rate gradually decreasing over the term of the agreement. GPU cloud providers Firmus and Sharon AI have both joined the project, and three executives with business ties to NVIDIA have confirmed the arrangement.
On July 1, NVIDIA announced on its official website a new business model combining revenue sharing and credit support, enabling AI cloud providers to purchase NVIDIA infrastructure without bearing the full upfront capital expenditure, and then offer computing power services to downstream AI-native enterprises, model developers, and enterprise customers.
Reports indicate that, internally at NVIDIA, this project is referred to by some as the AI Compute Partnership. A NVIDIA spokesperson has also confirmed the project's existence. This move marks a significant strategic shift for NVIDIA:
On one hand, it expands its customer base by lowering the financing barriers for emerging cloud service providers; on the other hand, it directly participates in profit sharing from the downstream computing power market through revenue sharing, further extending its control down the AI industry chain.Model shift: From selling chips to sharing cloud revenue. According to NVIDIA’s official press release, NVIDIA will additionally share in cloud service revenues beyond standard product sales, creating a usage-based recurring revenue stream. The core intent of this model is to break down the financing barriers that have long restricted startups from accessing large-scale computing power.
NVIDIA positions this framework as the "DSX AI Factory" model, targeting AI service scenarios that require continuous cross-regional operations, high utilization, and multi-tenant accelerated computing.
Sharon AI and Firmus are the first cloud providers to participate in this model. Sharon AI plans to deploy up to 40,000 NVIDIA Grace Blackwell GB300 GPUs; Firmus is constructing a DSX AI factory campus in Batam, Indonesia, with an expected scale of up to 360 megawatts and up to 170,000 NVIDIA GPUs. These deployments directly reflect NVIDIA’s latest progress in transforming compute demand into tangible, financiable infrastructure.
NVIDIA noted that emerging AI companies have historically faced severe constraints in accessing capital-intensive infrastructure—even with long-term commitment contracts, securing financing for compute procurement has often been insufficient. This means that a large number of AI-native companies, model developers, and inference service providers must endure lengthy delays when scaling their computing capabilities: each step—site selection, power procurement, construction, and hardware deployment—can take months or longer.
The promise of the new model is to enable the aforementioned groups to access full-stack accelerated computing capabilities more quickly, without waiting for the traditional infrastructure development cycle to complete.
Guarantee Logic: Addressing the Core Challenge of GPU Financing According to reports, GPUs are typically the most expensive component in AI data centers. For chip buyers with lower credit ratings, securing sufficient financing is already a significant challenge.
A data center executive commented that NVIDIA’s such deals “kill two birds with one stone.” He explained that if NVIDIA merely provides backing for the data center lease, “you still face the question of how to finance the GPUs”; but if NVIDIA commits to paying for unsold computing power within the facility, “the financing issue for the GPUs is solved, and the financing issue for the data center is solved too.”
In other words, NVIDIA’s guarantee effectively serves as a credit enhancement tool, enabling emerging cloud service providers, who would otherwise struggle to secure bank loans, to access larger amounts of capital and accelerate data center construction.
Strategic intent: Breaking the monopoly of major clients NVIDIA’s series of initiatives are driven by a clear strategic backdrop. Currently, a small number of large cloud providers—including Amazon, Microsoft, SpaceX, Oracle, Meta, and Google—have purchased the majority of NVIDIA’s chip production capacity. However, several of these companies are developing their own competitive AI chips, posing a potential threat to NVIDIA.
To reduce dependence on these major clients, NVIDIA has spent the past several years supporting a group of emerging GPU cloud service providers, including CoreWeave. This "AI Computing Partnership Program" is a continuation and deepening of that strategy.
According to prior reports from The Information, NVIDIA has recently been negotiating to provide financial guarantees for OpenAI’s lease of a large data center in Ohio, which, if fully built out at current prices for chips, labor, electricity, and other materials, could cost up to $500 billion.
Capital investment: From equity investment to production capacity guarantees, NVIDIA's capital investment in this area has already become substantial.
To date, NVIDIA has invested billions of dollars in equity stakes in several emerging cloud service providers and, in some cases, agreed to lease back the companies’ chips, involving firms such as CoreWeave and Lambda, with total transaction values reaching billions of dollars. According to prior reporting by The Information, NVIDIA’s own researchers have also used GPU servers leased back from Lambda.
Regarding capacity guarantees, NVIDIA began advancing related transactions in the fall of last year. In September 2024, NVIDIA committed to purchasing all of CoreWeave’s unsold capacity through 2032 if CoreWeave failed to find tenants—at which point the contract was valued at $6.3 billion. This move effectively alleviated investor concerns about CoreWeave’s highly leveraged business model, driving its stock price up nearly 30% in the following week.
According to a regulatory filing submitted by NVIDIA in May of this year (covering the quarter ended in April), NVIDIA subsequently added $3.5 billion to guarantee customer data center leases in exchange for the right to purchase its shares.
Overall, NVIDIA is building a multi-layered alignment mechanism: equity investment, capacity leaseback, lease guarantees, and now revenue sharing. Each layer deepens NVIDIA’s financial ties with downstream cloud service providers and enables NVIDIA to directly share in the incremental profits from AI computing commercialization, beyond just chip sales.