The Risks in Customers’ Business Models: What Investors Need to Know
One of the biggest risks lies in the business models of Nvidia’s customers, especially large cloud providers and hyperscalers like Amazon Web Services (AWS), Google Cloud, and Microsoft Azure, as well as AI-specialized companies that rent out GPU capacity “on-demand.”
An example of an AI-specialized company is Coreweave. They offer powerful GPU infrastructure to support various AI and machine learning applications, allowing businesses to rent GPU capacity without investing in their own hardware.
Coreweave has quickly grown to become one of the largest players in this space.
Many of these providers build their business models on the assumption that end customers will demand enough computing power to rent these expensive GPUs on a continuous basis.
The problem is that customers do not always have guaranteed revenues. This means that cloud providers, especially the smaller AI-specialized companies, are left with a large number of GPUs with uncertain future rental income.
If end customers’ demand for AI capacity does not reach the levels forecasted, this could create a significant surplus of unused GPUs, which in turn would reduce future orders to Nvidia.
VC Risk
Another risk factor is that many of these end users, apart from tech giants like Google and Amazon, are venture capital-funded startups. These companies face a challenging future where they are likely to start generating significant revenues to cover the increasing costs of computing power.
GPU costs have risen dramatically. Between the A100 and Hopper (H100) generations, prices have increased by around 250 percent. The next generation GPU, the Blackwell series, is expected to be another 20–30 percent more expensive.
These price increases reflect improved performance, lower energy consumption, and higher demand for AI capacity.
If these startups fail to capitalize on their AI projects and increase their revenues, they may struggle to finance their computing power in the long run. This could create a risk that they can no longer afford Nvidia’s products, leading to reduced demand and impacting Nvidia’s future growth.
To further complicate the situation, Nvidia, with its price hikes, expects continued strong demand.
Overcapacity
Another potential issue is overcapacity. If the market becomes saturated with GPUs and AI-specialized cloud providers cannot rent out the capacity they have invested in, this could lead to an excess of available GPUs in the market. This surplus could, in turn, result in downward pressure on prices or reduced orders for Nvidia.
Nvidia’s future revenue streams depend on their customers’ business models continuing to generate revenue and on end customers’ demand for AI capacity remaining strong.
## Analysis:
The article highlights the risks associated with Nvidia’s customers’ business models, especially in the context of cloud providers and AI-specialized companies. These risks include uncertainties in revenue generation, potential overcapacity issues, and the need for startups to increase revenues to cover rising GPU costs. Investors need to be aware of these factors as they could impact Nvidia’s future growth and demand for its products.