Nvidia explained: software developers working at computer workstations in an open office

Tech Companies · AI

From game graphics to the engine of AI

What Nvidia sells, how it makes money and why it matters to your business.

$215.9Brevenue in fiscal 2026
$96.2Brevenue in one quarter, May to July 2026
65%revenue growth in fiscal 2026

Nvidia is the Santa Clara, California, chip company whose graphics processors became the workhorses of artificial intelligence, and in three years it grew from a gaming brand into a company that reported $215.9 billion in revenue for its latest fiscal year.

If you have used ChatGPT, generated an image with AI or asked a phone assistant a question, there is a good chance the answer was computed on Nvidia hardware in a data center somewhere. Yet most people still picture Nvidia as the company behind gaming graphics cards. Both are true, and the story of how one led to the other explains a great deal about where technology, and business, is heading.

This guide explains Nvidia in plain English: what it makes, how it earns its money, what its most recent financial results show and what any of it means for a small business or startup in the Sacramento region. Every number comes from Nvidia’s own releases and filings. We do not quote stock prices, because they change by the minute.

$215.9Brevenue in fiscal 2026, up 65% (year ended Jan. 25, 2026)
$120.1BGAAP net income in fiscal 2026
$89.0BData Center revenue in Q2 fiscal 2027, up 117% from a year earlier
$108BNvidia’s revenue outlook for Q3 fiscal 2027, plus or minus 2%

What Nvidia makes

Nvidia designs chips and the software that runs on them. Its signature product is the GPU, or graphics processing unit. A regular processor (CPU) handles a few complex tasks at a time, one after another. A GPU handles thousands of simple calculations at the same time. That was built for drawing millions of pixels in a video game, and it turns out to be exactly what training and running AI models requires: enormous numbers of multiplications done in parallel.

Nvidia does not own the factories that make its chips. Like many chip companies, it designs them and relies on manufacturing partners. What it sells today goes well beyond single chips: complete server racks, networking switches, CPUs, and software libraries that developers use to build AI applications.

  • Data center systems: AI computers and full racks built on platforms named Blackwell and, now, Vera Rubin, sold to cloud providers, AI labs, governments and large companies.
  • Networking: switches and data processors that connect thousands of GPUs into one system.
  • Gaming and PCs: GeForce RTX graphics cards and laptop chips, and AI features for Windows PCs.
  • Professional visualization: RTX PRO workstation GPUs for designers, engineers and video editors.
  • Automotive and robotics: the DRIVE self-driving platform and Jetson and Isaac tools for robots.
  • Software: CUDA and its libraries, which let programmers use GPUs for general computing.
Silicon wafer with a grid of chips, like the wafers Nvidia GPUs are cut from
Each square on a silicon wafer becomes a chip. Nvidia designs its chips and relies on partners to make them. Photo: Laura Ockel on Unsplash

How a graphics company became an AI company

Nvidia’s own timeline tells the story in a handful of dates. The common thread is that the company kept making its graphics chips useful for things other than graphics, and researchers noticed.

Milestones from Nvidia’s corporate timeline

  1. 1993: FoundedJensen Huang, Chris Malachowsky and Curtis Priem founded Nvidia on April 5, 1993. Huang is still founder and CEO.
  2. 1999: The GPUNvidia says it invented the GPU in 1999, setting the stage for modern computer graphics.
  3. 2006: CUDAThe CUDA architecture opened GPU parallel processing to science and research, so programmers could use graphics chips for general math.
  4. 2012: AlexNetNvidia GPUs powered the AlexNet neural network, which helped start the modern era of AI.
  5. 2018: RTXNvidia introduced RTX, which it describes as the first GPU capable of real-time ray tracing.
  6. 2022 to today: AI factoriesDemand for chips to train and run large AI models turned the data center business into the company’s main business.

The key decision was CUDA. By giving developers free tools to program its GPUs, Nvidia built an ecosystem of software, skills and code that runs best on its hardware. Competitors can build fast chips, but switching means rewriting or re-testing years of software. That software moat is one reason Nvidia’s position has been hard to challenge.

The numbers: how fast Nvidia has grown

Nvidia’s fiscal year ends in late January, so its fiscal 2026 ran from early 2025 to January 25, 2026. In three years, annual revenue grew roughly eightfold.

Nvidia annual revenue by fiscal year ($ billions)

Fiscal 2023Ended January 2023
27.0B
Fiscal 2024Up 126%
60.9B
Fiscal 2025Up 114%
130.5B
Fiscal 2026Up 65%
215.9B

Source: NVIDIA fourth-quarter and fiscal-year results releases for fiscal 2024 (Feb. 21, 2024) and fiscal 2026 (Feb. 25, 2026). Values in billions of U.S. dollars.

Profit grew alongside sales. For fiscal 2026, Nvidia reported GAAP net income of $120.1 billion on $215.9 billion in revenue, with a GAAP gross margin of 71.1%. During that year it returned $41.1 billion to shareholders through share buybacks and dividends.

Where the money comes from

The shift to AI shows up clearly in where Nvidia’s revenue comes from. Gaming, the business most people know, set a record in fiscal 2026 at $16.0 billion, yet it was a small slice of the whole.

Nvidia revenue by market, fiscal 2026

~90%from data centers
  • 89.7%Data Center ($193.7B)
  • 7.4%Gaming ($16.0B)
  • 1.5%Professional Visualization ($3.2B)
  • 1.1%Automotive and Robotics ($2.3B)
  • 0.3%OEM and other

Shares calculated by Inksight from the dollar figures in NVIDIA’s fiscal 2026 results release; “OEM and other” is the remainder of total revenue.

Server cooling fans in an AI data center, where most Nvidia revenue now comes from
Data centers built for AI produced about 90% of Nvidia’s revenue in fiscal 2026. Photo: Winston Chen on Unsplash

The latest quarter: May to July 2026

In its second quarter of fiscal 2027, which ended July 26, 2026, Nvidia reported revenue of $96.2 billion, up 18% from the previous quarter and up 106% from a year earlier. Data Center revenue was $89.0 billion. The company now groups its other products, including gaming, PCs, cars and robots, under Edge Computing, which brought in $7.2 billion, up 27% from a year earlier.

Q2 fiscal 2027 at a glance

Measure Result Change from a year earlier
Revenue $96.2 billion Up 106%
Data Center revenue $89.0 billion Up 117%
Edge Computing revenue $7.2 billion Up 27%
GAAP gross margin 75.0% Up 2.6 points
GAAP net income $59.7 billion Up 126%
Returned to shareholders About $26.0 billion Buybacks and dividends in the quarter

Nvidia’s outlook for the third quarter is revenue of $108.0 billion, plus or minus 2%, and the company said it is not assuming any Data Center compute revenue from China. Its next quarterly dividend, $0.25 per share, was set for payment on October 1, 2026.

In the CEO’s words

“Now, compute is revenue,” Jensen Huang said in the August 26, 2026 release, arguing that AI models doing useful work turn computing power directly into income for Nvidia’s customers. That is the company’s view; whether AI spending keeps growing at this pace is the main question investors and analysts debate.

What Nvidia is launching now

According to its August 2026 release, Nvidia’s Vera Rubin platform is in full production, with racks running at partners including CoreWeave, Google Cloud, Microsoft Azure, Oracle Cloud Infrastructure and Nebius. The company also announced Vera, a CPU it describes as built for AI agents, and, with Microsoft, RTX Spark, a chip for Windows PCs. On the robotics side, it introduced a reference design for an open humanoid robot built on its Jetson Thor computer.

What Nvidia means for small businesses

Few small businesses will ever buy a data center rack, but almost all of them now use Nvidia indirectly. Here is where it touches Main Street:

  • AI tools you already pay for. Chatbots, AI image tools and AI features in accounting, design and marketing software typically run in cloud data centers on GPUs. Their prices and limits depend partly on the cost of that computing.
  • Rent, do not buy. Major cloud providers rent GPU time by the hour, so a small team can test an AI idea without buying hardware.
  • Your next computer. Designers, video editors, architects and engineers use RTX laptops and workstations to run creative and AI software locally. Match the GPU to the software you actually use.
  • Jobs and skills. Programming with GPUs and AI tools is in demand; free courses from Nvidia and local colleges can be a low-cost way in.
Startups: Nvidia Inception is free

Nvidia’s Inception program for startups has no application or membership fees and takes no equity. Nvidia says companies must be officially incorporated and under 10 years old, have a working website, a clear use for Nvidia technology and at least one active founder. Benefits include free self-paced courses, preferred pricing on some hardware and software, cloud credits from Nvidia and partners, and possible introductions to investors. For the bigger funding picture, see our small business loans guide and SBA loans guide.

Risks worth knowing

  • Concentration: about 90% of revenue in fiscal 2026 came from one market, data centers.
  • China: Nvidia’s outlook assumes no Data Center compute revenue from China.
  • Competition: other chipmakers and large cloud companies design their own AI chips.
  • The AI spending cycle: growth depends on customers continuing to invest heavily in AI computing.

Common mistakes

  • Thinking Nvidia is mainly a gaming company. Gaming is under a tenth of revenue.
  • Buying a high-end GPU for software that does not use it. Check the software’s requirements first.
  • Treating headlines as forecasts. Use Nvidia’s own releases for figures, and date them.
  • Confusing fiscal and calendar years. Nvidia’s fiscal 2027 runs to late January 2027.
  • Ignoring cloud options. Renting GPU time is often cheaper than buying hardware for a short project.

Key terms

  • GPU: a graphics processing unit, a chip that runs thousands of calculations in parallel.
  • CUDA: Nvidia’s programming platform that lets developers use GPUs for general computing.
  • Data center: a building full of servers; Nvidia calls those built for AI “AI factories.”
  • Inference: running a trained AI model to answer questions or create content.
  • Fiscal year: a company’s 12-month accounting year; Nvidia’s ends in late January.

The bottom line: Nvidia turned a chip built for video games into the standard engine for AI, backed by software that developers rely on. Its fiscal 2026 revenue of $215.9 billion, about 90% from data centers, shows how central AI computing has become. For a small business, the practical takeaway is to use that computing power through cloud services and the right hardware, and for startups, to look at free programs such as Inception.

Free help in the Sacramento region

You do not have to work through these decisions alone. SCORE Sacramento pairs owners with volunteer mentors, many of them retired executives, bankers and accountants, at no cost. The Sacramento Valley Small Business Development Center offers free one-on-one advising on financing, budgeting and financial statements. The SBA’s Sacramento District Office can explain loan programs and connect you with lenders, and community lenders such as California Capital and Opening Doors serve owners who need smaller loans or extra support. Browse our Business Resources and the free business help guide for more.

Key takeaways

  • Nvidia designs GPUs, chips that run thousands of calculations at once, which suits AI.
  • Founded in 1993, it built CUDA in 2006 and powered the AlexNet AI breakthrough in 2012.
  • Fiscal 2026 revenue was $215.9 billion, up 65%; about 90% came from data centers.
  • Q2 fiscal 2027 revenue reached $96.2 billion, with a $108.0 billion outlook for Q3.
  • Small businesses use Nvidia mainly through cloud AI tools; startups can join Inception for free.

Frequently asked questions

What does Nvidia make?

Nvidia designs graphics processing units (GPUs), AI data center systems, networking equipment, CPUs and software such as CUDA, plus chips for gaming PCs, workstations, cars and robots.

Why are Nvidia chips used for AI?

GPUs run thousands of simple calculations in parallel, which is what training and running AI models requires, and Nvidia’s CUDA software made its GPUs easy for researchers and developers to program.

How much revenue does Nvidia make?

Nvidia reported 215.9 billion dollars in revenue for fiscal 2026, which ended January 25, 2026, and 96.2 billion dollars for the quarter that ended July 26, 2026.

Who founded Nvidia?

Jensen Huang, Chris Malachowsky and Curtis Priem founded Nvidia on April 5, 1993. Jensen Huang is founder and CEO.

Can a small business or startup use Nvidia technology?

Yes. Most small businesses use it through cloud AI services or RTX computers, and incorporated startups under 10 years old can apply to the free Nvidia Inception program.

Sources