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NVIDIA designs the computer chips and related software that power artificial intelligence, video games, and data centers.
NVIDIA makes the chips that have become the engine of the artificial intelligence boom. Its most famous products are graphics processing units, or GPUs — chips that were originally built to make video games look real by drawing millions of pixels at once. It turned out that the same math that renders a exploding spaceship is also great at training AI models, so NVIDIA found itself at the center of the biggest technology shift in decades.
Here is the simple version of why its chips matter. A normal computer processor is like a brilliant worker who does one task at a time, very fast. A GPU is like a huge room full of average workers doing thousands of small tasks at once. AI is basically mountains of small repetitive math, so the room full of workers wins. NVIDIA sells these chips, plus the networking gear and software that let thousands of them work together as one giant computer. Its customers are the big cloud companies, AI labs, and governments building data centers, and they pay premium prices because NVIDIA's chips and its software ecosystem, called CUDA, are extremely hard to replace. The money has been staggering. NVIDIA's revenue exploded from roughly $27 billion in its fiscal 2023 to about $130 billion in fiscal 2025, driven almost entirely by data center AI chips. That kind of growth made it one of the most valuable companies on earth. The business is fabless, meaning NVIDIA designs the chips but pays Taiwan's TSMC to actually manufacture them — a strength because it avoids building costly factories, and a vulnerability because it depends on a single supplier and on complex global supply chains.
In 1993, Jensen Huang and two friends, Chris Malachowsky and Curtis Priem, started a company around one big bet: that video games would move beyond flat 2D pictures into realistic 3D worlds. That idea was the seed of everything that followed, even though the market for it barely existed yet.
The bet almost ended the company before it began. Nvidia failed to deliver a graphics chip it had promised to Sega, and the business nearly collapsed, saved only by a small investment from Sega that kept the lights on. It was the first sign that this company would survive by the skin of its teeth more than once.
Six years after starting, Nvidia sold shares to the public. It was a modest company at the time, with revenue of about $158 million in its first year as a public business, but it now had the cash and the profile to keep chasing its graphics dream.
Later that same year came the product that gave the company its identity: the GeForce 256, the first chip marketed as a GPU. Instead of leaving graphics work to the computer's main brain, the CPU, the GPU took full charge of drawing the screen, which kept games from slowing down or crashing. It was the moment Nvidia stopped making graphics cards and started defining a new kind of computer part.
Nvidia then bought the graphics assets of 3dfx, its nearest rival in the gaming chip market, for cash and stock, picking up its patents and around a hundred engineers. The deal quietly cleared the field: with its toughest competitor gone, Nvidia consolidated the consumer GPU market and became the name in gaming graphics.
The 2008 financial crisis hit, and Nvidia's shares fell roughly 85 percent from their peak. Investors doubted the company's strategy while it kept pouring money into CUDA, software meant to let its chips do far more than draw games. Huang later called that stretch embarrassing and humiliating, a time when the company's only face was one everybody hated. The payoff for that stubborn bet was still years away.
In 2016, Nvidia gave the first of its DGX-1 AI supercomputers to a young research group called OpenAI. It looked like a generous gift, but it also tied OpenAI's software closely to Nvidia chips, and it set off a six-year path that would end with the launch of ChatGPT in 2022. The company that made games look real was now quietly arming the people teaching machines to think.
Nvidia bought Mellanox, a networking company, for about $7 billion in 2020. Networking was the missing piece: with chips, software, and now the connections between machines, Nvidia could control the whole data center stack and sell entire AI systems end to end instead of just parts.
Nvidia had announced a $40 billion deal to buy chip designer Arm, but regulators pushed back and the deal was terminated in 2022. Rather than give up, Nvidia built its own Arm-based Grace CPU and later the Grace Blackwell platform, reaching in a different form the combined chip-and-networking system the Arm deal was supposed to deliver.
By 2024, Nvidia had grown from a $158 million business into one worth trillions, joining Apple and Microsoft in the exclusive $3 trillion club. The engine of that rise was data centers, which overtook gaming as its biggest source of revenue a couple of years earlier. The company that nearly died over a Sega chip had become one of the most valuable on Earth.
In late 2024, Huang announced the acquisition of VinBrain, an AI startup in Vietnam, as a starting point for a future large-scale design center there. It was a small deal with a bigger purpose: planting Nvidia's flag in a new region for AI research and development.
By 2026, Nvidia was selling entire server racks built for AI, combining 72 Vera Rubin GPUs with hundreds of custom chips and Vera CPUs. The sales opportunity per gigawatt of computing power had more than doubled from the earlier Hopper generation to Vera Rubin. The chipmaker had become a seller of complete AI factories.
NVIDIA's grip is powerful but not unshakable. Competitors like AMD, custom chips from its own biggest customers, and rising Chinese players all want a piece of the AI chip market. There are also real risks: export controls restrict sales of its most advanced chips to China, and regulators around the world are watching its dominance closely. Still, NVIDIA keeps pushing forward, using its cash to fund massive share buybacks and to develop new generations of chips and software that aim to keep AI builders locked into its ecosystem.
Saved answer · last researched 19 Oct 2026