Nvidia’s market cap just made history. The AI chip behemoth broke records on July 9, 2025, crossing the $4 trillion valuation barrier, temporarily becoming the world’s most valuable publicly traded company, surpassing tech giants Microsoft and Apple. Marking a defining moment, Nvidia cements its position at the forefront of AI innovation with its groundbreaking chipsets and high-performance GPUs.
While Nvidia is now a household name in AI, there’s more to the company’s story than meteoric stock gains and powerful GPUs. Here are some lesser-known, fascinating facts about Nvidia’s journey from a struggling graphics card maker to the beating heart of modern AI infrastructure.
7 Lesser-Known Facts About Nvidia’s Rise to AI Superpower
Nvidia Didn’t Start in AI or Gaming
Founded in 1993, Nvidia initially aimed to increase multimedia functionality for personal computers. Its initial offering — the NV1 multimedia card — failed in the marketplace. At the time, AI applications or data centers weren’t even on the horizon for the young firm.
It Was Once Known as “Project X“
Before embracing the globally known name, Nvidia co-founders Jensen Huang, Chris Malachowsky, and Curtis Priem worked under the project code name Project X. The ‘Nvidia’ name is derived from the Latin term ‘invidia’, which means envy — a fitting name for a company now causing mass GPU envy throughout the AI sector.
By the end of the 1990s, Nvidia was staring down the barrel of bankruptcy
Early failures nearly closed the company. Several product failures put Nvidia on the financial ropes until the launch of the RIVA 128 GPU in 1997 and the GeForce 256, the first commercially branded GPU in the world. These chips saved Nvidia from the brink and revolutionized gaming and graphics computing forever.
Apple, Not Microsoft, Spurred Nvidia’s Early Success
Unexpectedly, it wasn’t Microsoft, but Apple that turned into one of Nvidia’s first high-profile customers. MacBook Pros were powered by Nvidia’s GPUs in the mid-2000s, and Nvidia solidified its place in high-performance computing years ahead of AI becoming a mass craze.
Nvidia’s Failed $40 Billion Bid to Acquire ARM
Back in 2020, Nvidia set its sights on acquiring ARM Holdings, a major British firm specializing in chip design, for a proposed $40 billion. Regulatory hurdles by the US, UK, and Chinese authorities stopped the deal, which would have transformed the mobile and IoT chip market and solidified Nvidia’s leadership beyond AI and graphics.
Nvidia Powers AI Applications You Use Daily
Behind the scenes of well-known AI applications such as ChatGPT, Midjourney, Google Gemini, and others, Nvidia’s H100 and A100 GPUs quietly bear the computational burden. Such AI-dedicated GPUs are the horsepower behind the world’s fastest-growing AI models, supporting sophisticated training and inference processes across the globe.
AI Is Now Nvidia’s Largest Revenue Driver
Though established to serve graphics and gaming, AI-related companies currently generate the bulk of Nvidia’s revenue. According to Nvidia’s recent earnings report, AI data center solutions generate more than 60% of its total revenue, a percentage bound to grow with the growing adoption of AI in cloud computing, healthcare, automotive, and enterprise solutions.
Why Nvidia’s $4 Trillion Milestone Matters
This is not only a financial milestone — it’s a tipping point in the way markets are valuing AI infrastructure stocks versus legacy software and consumer electronics companies. Nvidia’s unmatched dominance in the AI chip segment is driving it past traditional tech leaders.
Nvidia CEO Jensen Huang pointed out recently in an investor call, “AI is transforming every industry, and Nvidia is at the center of this transformation.”
FAQs
Q1: What drove Nvidia’s valuation past the $4 trillion mark?
Nvidia’s market cap boom is fueled by record-breaking demand for AI chips such as the H100 and A100 GPUs, which drive top AI models and data centers around the world.
Q2: What AI apps do Nvidia GPUs support?
Top AI applications like ChatGPT, Midjourney, Google Gemini, and corporate AI software depend upon Nvidia’s H100 and A100 GPUs to perform training and inference operations.
Q3: What was the initial business of Nvidia before AI?
Nvidia started in 1993 on the business of graphics acceleration for multimedia PCs. Its initial product, the NV1, was a failure, but the company successfully shifted to GPU business in gaming and AI.
Q4: Why did Nvidia’s ARM acquisition attempt fail?
US, UK, and Chinese regulatory authorities expressed fears of competition and market dominance, finally stopping Nvidia’s $40 billion takeover bid for ARM Holdings in 2022.
Q5: How does Nvidia stand compared to other AI chipmakers today?
Nvidia has a dominant position in the AI hardware space, with its H100 GPU taking the lead over competitors such as AMD’s Instinct MI300X and Intel’s Gaudi2 in AI model training benchmarks.
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