Nvidia has become the first company in the world to reach a market capitalization of $4 trillion, after its shares rose 2.4% on Wednesday to $164 per share, continuing to benefit from the sustained surge in demand for AI-related technology.
The U.S. company had first crossed the $1 trillion mark in June 2023, and has maintained rapid growth ever since.
Dan Ives, tech analyst at Wedbush Securities, described the milestone as “a historic moment for Nvidia,” adding: “They’re the only game in town — their chips are the new gold and oil.”
Nvidia shares had plunged in April when global markets were shaken by the escalating trade war led by U.S. President Donald Trump. Despite ongoing concerns about Trump’s trade policies, Nvidia’s stock has continued to rise since spring, reaching this latest milestone.
Eight years ago, Nvidia stock was worth less than 1% of its current value, driven at the time by competition with AMD over graphics card dominance. Today, its meteoric rise is tied to surging demand for the chips that power generative AI models such as ChatGPT.
Nvidia’s dramatic ascent has also elevated its CEO and co-founder, Jensen Huang, whom Mark Zuckerberg recently dubbed “the Taylor Swift of tech” — a reference to his rockstar-like status, particularly in Taiwan.
The company’s rising market value reflects Wall Street’s confidence in the AI sector, despite the turbulence caused by broader U.S. economic policies.
Nvidia reported revenues of $44.1 billion in the first quarter, up 69% year-over-year, with earnings per share reaching $0.81.
What makes Nvidia so special?
Origins:
Nvidia was founded in 1993 — during a now-famous meeting at a Denny’s restaurant — with a focus on designing a specific type of programmable chip.
For years, the U.S. chip market was dominated by Intel and AMD, who produced CPUs (central processing units) for general computing tasks.
Nvidia, by contrast, specialized in GPUs (graphics processing units), which had stronger image-rendering capabilities — initially useful for video games and graphics applications.
Eventually, it became clear that GPUs could execute parallel calculations more efficiently than CPUs, making them more energy-efficient and better suited for complex computational tasks.
Over time, major chipmakers began manufacturing their own GPUs, but they were late to the game. Nvidia had first-mover advantage, along with a suite of developer-friendly software, and a streamlined supply chain that enabled large-scale GPU production with unmatched speed and efficiency.
For example, carmakers began using Nvidia chips in driver-assistance programs that process visual data from sensors. All Tesla vehicles now include Nvidia hardware. Still, up until 2020, Intel’s market cap was larger than Nvidia’s.
COVID-19 and the AI explosion
During the pandemic, the shift to remote work, demand for data centers and cloud services, and booming interest in video games accelerated Nvidia’s revenues.
Then, Silicon Valley — led by OpenAI — began to recognize AI’s potential to transform business operations.
Thanks to its software ecosystem and efficient supply chain, Nvidia was ideally positioned to provide the computing power needed for AI adoption.
Nvidia’s fortunes took off like a rocket. At its current share price, the company is valued at nearly $3 trillion, rivaling Apple.
In a past CNBC interview, CEO Jensen Huang said the company’s success was a mix of “skill and luck,” noting: “We believed something new would happen someday, and the rest just required a little luck. It wasn’t foresight — it was accelerated computing.”
Today, virtually every major tech firm — including Amazon, Google, Meta, Microsoft, and Oracle — uses Nvidia chips.
Bloomberg has described Nvidia’s chips as “the backbone of AI model training,” while PNC analyst Amanda Agati called its dominance “near-total monopoly.”
Raj Joshi, senior VP at Moody’s, said Nvidia is “the dominant player in AI infrastructure,” and while other companies are racing to catch up, Nvidia’s 30-year experience designing GPUs gives it a major advantage.
Joshi added that Nvidia also leads in sectors like healthcare, saying: “They have a strong foothold in those markets too.”
The race to catch up
Thanks to its unique position, Nvidia can charge a premium for its chips — manufactured in Taiwan and so scarce that AI startups often complain about supply shortages.
The CHIPS and Science Act, passed under the Biden administration in 2022, aims to boost domestic GPU production, but doubts remain over whether the U.S. can meet demand.
Commerce Secretary Gina Raimondo said this week: “The volume of chips AI companies need is staggering,” and hinted that more federal support may be needed to keep up.
The new market anchor
Nvidia’s financial performance now holds major weight across U.S. stock indexes, according to Amanda Agati. “Nvidia has become a market anchor,” she said. “If data is the new oil, Nvidia is leading the pack.”
Originally known for gaming GPUs, Nvidia now provides the foundation for most AI applications.
Alan Priestley at Gartner called Nvidia “the technological leader in AI enablement,” while Dan Hutcheson of TechInsights said: “What Intel was to the PC, Nvidia is to AI.”
ChatGPT, for instance, was trained on 10,000 Nvidia GPUs within a Microsoft supercomputer — one of several such AI-focused systems, some public, others not.
According to CB Insights, Nvidia commands about 95% of the market for AI-focused GPUs. Its chips, used in data centers, cost around $10,000 each, with newer, more powerful versions priced even higher.
How did Nvidia gain this dominance?
The answer lies in a bold bet on its own tech — and good timing.
In 1999, Nvidia began developing GPUs for better image rendering. In 2006, Stanford researchers discovered the chips could accelerate mathematical computations, prompting Huang to invest in making GPUs programmable — expanding their use beyond graphics.
This became the foundation of modern AI.
In 2012, the AI model AlexNet was unveiled, trained on just two Nvidia chips. It completed training in days, not months — and researchers took notice.
Word spread quickly, and demand for Nvidia GPUs surged as researchers began building new AI tools.
Dominance and competition
Nvidia doubled down, developing AI-specific chips and easy-to-use software, pulling further ahead of rivals.
Startups like Metaphysic use Nvidia chips to train models that generate lifelike video — such as the viral Tom Cruise deepfake in 2021.
“There’s no substitute for Nvidia,” said co-founder Tom Graham. “They’re too far ahead.”
Still, Nvidia’s dominance is not unshakable. Rivals like AMD, Intel, and startups like Graphcore are developing custom AI chips.
Graphcore CEO Nigel Toon said: “We’ve built a processor tailored to AI as it exists today and will evolve in the future,” but admitted that competing with Nvidia is a steep challenge.
Ian Buck of Nvidia responded: “Everyone needs AI now — and others will need to find their role in supporting it.”
