This Is How NVIDIA Makes Money: A Breakdown of a Company That Began in Gaming and Now Dominates Data Centers in the Era of AI

  • NVIDIA has experienced exponential growth in recent times. Today, it earns more than $60 billion annually.

  • The company dominates the specialized AI chip market relying on architectures like CUDA.

  • Its main division used to be Gaming, but now, the Data Center division is far above it.

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NVIDIA’s meteoric rise in recent years has been nothing short of remarkable. From its origins in the gaming industry to its current dominance in data centers and AI technologies, the company has undergone a dramatic transformation. In this article, we’ll delve into NVIDIA’s journey, exploring how it has evolved into a powerhouse of the tech world.

The fruits of decades of work

For this article, we consulted NVIDIA’s financial results for the fiscal year 2024. Although it may sound strange to those unfamiliar with corporate finance, there’s a simple explanation: a company’s fiscal year doesn’t always coincide with the calendar year. Many companies, such as this one, choose a different fiscal year for accounting, financial, or business reasons. NVIDIA’s fiscal year 2024 has already ended, as it ran from February 1, 2023, to January 31, 2024.

That said, let’s take a look at the numbers.

NVIDIA had a spectacular 2024. The company’s revenue surpassed the $60 billion mark, more than double that of 2023. To put it in context, in 2020 it barely exceeded $10 billion.

F1i9t Nvidia S Annual Revenue

But if there is one figure that conveys the magnitude of NVIDIA’s current business, that’s its net income, which is close to $30 billion; approximately 50% of its revenue. This is a profit level that has grown at a much faster rate than the revenue. In other words, in addition to its growing turnover, the company is also earning much more money.

Edpyg Nvidia S Annual Profit

How did it get to this point?

The company has been building the current scenario for decades, and the rise of generative AI has provided an opportunity for those who were prepared for it. This isn’t about two or three particularly prolific years; it’s the result of decades of accumulated work.

NVIDIA began investing in AI and deep learning long before these technologies reached the level of popularity they have today. This forward-looking vision led them to develop hardware and software optimized for the high computational demands of AI algorithms.

From there came their star products: high-performance GPUs that are extremely efficient in executing the training and inference tasks of AI models. The GeForces, Quadros, or Teslas that were later renamed as A100, H100, and so on, have become the industry standard for graphics processing and high-performance computing (HPC).

In addition, NVIDIA has also developed specific architectures, such as CUDA, which allow developers to use GPUs for parallel processing in AI applications, making it easier to work with large amounts of data and complex machine learning algorithms.

All these different approaches have allowed the company to offer advanced hardware, but also an ecosystem that meets the needs of developers, who can create their own AI applications on NVIDIA architecture.

Another consequence of this is that the company is now practically alone. Of course, it has competitors, like AMD with its Radeons and–to a lesser extent–Intel, which is trying to regain lost ground, a Graphcore that is far from the expectations of a few years ago, and, in different contexts, Apple Silicon or Google, with its TPUs. But none compares to the scale of NVIDIA, even if the shadow of Groq is approaching... as well as that of OpenAI.

The company’s current catalog includes dedicated GPUs for gaming and data centers, AI tasks, machine learning, and autonomous cars. Additionally, NVIDIA also generates revenue from the sale of software and licenses.

Its business model, especially the corporate aspect, is similar to the bait-and-hook model: the company sells its GPUs and then continues to generate revenue with the sale of software and licenses for the use of those GPUs. This model has other examples, such as printers and ink.

These are the four divisions of NVIDIA:

  • Data Center: It supplies hardware and software to accelerate AI, deep learning, and high-performance computing applications in cloud and server environments.
  • Gaming: It develops GPUs and technologies for the gaming experience on PCs, consoles, and mobile devices.
  • Professional Visualization: It offers graphics solutions for professionals, such as workstations or rendering and simulation, in sectors such as design, architecture, or digital content creation.
  • Automotive: It provides hardware and software platforms for the automotive industry, focusing on autonomous driving, navigation systems, or in-car infotainment.

This is how the revenue is distributed: Data Center, $47.5 billion; Gaming $10.4 billion; Professional Visualization, $1.6 billion, and Automotive, $1.1 billion.

Vh3o8 Breakdown Of Nvidia S 2024 Revenue

This distribution hasn’t always looked like this. In fact, it used to be quite different: it is the materialization of NVIDIA’s progress in the Data Center division. Not long ago, the Gaming division still led the company’s sales.

Nvidia surpasses internal expectations

This is the chart that best summarizes the story. What NVIDIA was and what it is now. What has been the great engine that allowed it to reposition itself in the industry. It is no longer just an important technology company; it has climbed positions and its market capitalization is already higher than that of Amazon, Meta, or Alphabet. Quite an impressive feat.

Vgk3p The 10 Biggest Companies By Market Cap

A huge leap, especially in the last eighteen months, that has changed NVIDIA and, with it, an entire industry. Without a doubt, this is no longer the company that used to bolster its treasury by selling graphics cards for gamers.

Image | NVIDIA, Vecteezy, Xataka On

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