NVIDIA is set to start taking a cut of cloud providers' revenue
- Key Point: NVIDIA is evolving from a chip seller to the "central bank" of the AI computing ecosystem. By providing financial guarantees for new cloud service providers through a GPU capacity repurchase model, it secures a share of their revenue, thereby lowering customer financing barriers and expanding market control.
- Key Elements:
- NVIDIA has launched the "AI Computing Partnership Program," promising to repurchase unsold GPU capacity from emerging cloud service providers at agreed-upon prices, serving as a credit endorsement.
- In exchange, NVIDIA receives a gradually decreasing revenue share from these cloud service providers, creating recurring income tied to usage.
- Initial participants include cloud service provider Sharon AI (planning to deploy 40,000 GB300 GPUs) and Firmus (building a 360 MW AI factory in Indonesia).
- This model aims to solve the core challenge for emerging AI companies, which struggle to obtain GPU financing due to low credit ratings, accelerating their infrastructure construction.
- This move is a continuation of NVIDIA's strategy to reduce dependence on major customers like Amazon and Microsoft, who are developing competing AI chips.
- NVIDIA has already invested tens of billions of dollars in companies like CoreWeave through equity investments and capacity repurchase, for example, once committing $6.3 billion to buy CoreWeave's unsold capacity.
- NVIDIA added $3.5 billion to guarantee customer data center leases in exchange for stock purchase rights, building a multi-layered interest-binding mechanism.
Original Author: Dong Jing
Original Source: Wall Street Insights
Nvidia is leveraging its powerful balance sheet as a market lever, 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 a report from tech media outlet The Information, Nvidia is offering financial guarantees to young cloud service providers that lease its GPUs—if these companies cannot find enough AI developers to rent their computing power, Nvidia will repurchase their unsold GPU capacity at a predetermined price.
In exchange, Nvidia will receive a percentage of these cloud service providers' revenue, with the share gradually decreasing over the contract period. GPU cloud service providers Firmus and Sharon AI have already joined the program, and three other 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 with credit support, allowing AI cloud providers to acquire Nvidia infrastructure without fully bearing upfront capital expenditures, and to offer computing services to downstream AI-native enterprises, model developers, and corporate clients.
According to the report, this program is internally referred to by some at Nvidia as the "AI Compute Partnership." An Nvidia spokesperson also confirmed the program's existence. This move marks a significant strategic shift for Nvidia:
On one hand, it expands the customer base by lowering the financing barriers for emerging cloud service providers; on the other hand, through revenue sharing, it directly participates in the profit distribution of the downstream computing power market, extending its control over the AI industry chain further downstream.
Model Shift: From Selling Chips to Sharing Cloud Revenue
According to Nvidia's official press release, in addition to standard product revenue, Nvidia will receive an extra share of cloud service revenue, creating a recurring income stream tied to usage. The core intention of this model is to break down the financing barriers that have historically constrained startups from accessing large-scale computing power.
Nvidia positions this framework as the "DSX AI Factory" model, targeting AI service scenarios that require cross-regional continuous operation, high utilization rates, 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 building a DSX AI Factory campus on Batam Island, Indonesia, expected to expand to 360 megawatts and house up to 170,000 Nvidia GPUs. These two deployments directly demonstrate Nvidia's latest progress in turning computing demand into fundable, deployable infrastructure.
Nvidia points out that emerging AI companies have historically faced severe constraints in accessing capital-intensive infrastructure—even signing long-term commitment contracts often fails to secure financing for computing procurement. This means many AI-native companies, model developers, and inference service providers must endure long waits to scale their computing capabilities: site selection, power procurement, construction, hardware debugging—each step can take months or even longer.
The new model promises: by realigning the economic structure, these groups can access full-stack accelerated computing capabilities more quickly, without waiting for traditional infrastructure construction cycles to complete.
The Guarantee Logic: Solving the Core Problem 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 loans is a major hurdle in itself.
One data center executive commented that Nvidia's deals are "killing two birds with one stone." He explained that if Nvidia merely backs data center facility leases, "you'd still face the problem of 'how to finance the GPUs'"; but if Nvidia commits to paying for unsold computing capacity within the facility, "the GPU financing problem is solved, and the data center financing problem is solved too."
In other words, Nvidia's guarantee effectively acts as a credit enhancement tool, enabling emerging cloud providers that previously struggled to secure bank loans to leverage larger amounts of capital and accelerate data center construction.
Strategic Intent: Breaking the Oligopoly of Major Clients
Nvidia's rollout of these initiatives has a clear strategic backdrop. Currently, a small number of large cloud service providers—including Amazon, Microsoft, SpaceX, Oracle, Meta, and Google—purchase the majority of Nvidia's chip production. However, several of these companies are developing their own competing AI chips, posing a potential threat to Nvidia.
To reduce its dependence on these giant clients, Nvidia has been fostering a group of emerging GPU cloud service providers, led by CoreWeave, over the past few years. The "AI Compute Partnership" is a continuation and deepening of this strategy.
According to a previous report by The Information, Nvidia has recently been negotiating to provide financial guarantees for OpenAI to lease a large data center in Ohio. If fully built under current chip, labor, power, and material costs, the data center could cost up to $500 billion.
Financial Commitment: From Equity Investments to Capacity Guarantees
Nvidia's financial commitment in this direction is already substantial.
To date, Nvidia has invested billions of dollars in several emerging cloud service providers in exchange for equity and, in some cases, has agreed to lease back chips from these companies. This involves firms like CoreWeave and Lambda, with total transaction values reaching tens of billions of dollars. According to a previous report by The Information, Nvidia's own researchers have used GPU servers leased back from Lambda.
Regarding capacity guarantees, Nvidia began advancing related deals last fall. In September 2024, Nvidia committed to purchasing all of CoreWeave's unsold capacity through 2032 if CoreWeave could not find tenants, a contract then valued at $6.3 billion. This move effectively alleviated investor concerns about CoreWeave's highly leveraged business model, boosting its stock price by nearly 30% in the following week.
According to a regulatory filing Nvidia submitted in May (covering the quarter through April), Nvidia subsequently added another $3.5 billion to guarantee client data center leases in exchange for the right to purchase their stock.
Overall, Nvidia is constructing a multi-layered benefit-binding mechanism: equity investments, capacity leasebacks, lease guarantees, and now revenue sharing. Each layer deepens the financial ties between Nvidia and downstream cloud providers, allowing Nvidia to directly share in the incremental gains from AI computing commercialization beyond just chip sales.
