Nvidia recently reported a stellar financial performance during the third quarter of the year, with revenues surging 94 percent from a year ago to $35.1 billion. The AI chipmaker became the world’s most valuable company and the engine of the AI boom with its value soaring by $2.2 trillion this year to $3.6 trillion due to chip sales nearly doubling.
“The age of AI is in full steam, propelling a global shift to Nvidia computing. Demand for Hopper and anticipation for Blackwell — in full production — are incredible as foundation model makers scale pretraining, post-training and inference,” said Jensen Huang, founder and CEO of Nvidia.
For the quarter, GAAP earnings per diluted share was $0.78, up 16 percent from the previous quarter and up 111 percent from a year ago. Meanwhile, non-GAAP earnings per diluted share was $0.81, up 19 percent from the previous quarter and up 103 percent from a year ago.
Nvidia also reported record quarterly data center revenue of $30.8 billion, up 17 percent from Q2 and 112 percent from a year ago. The company expects revenues to rise to $37.5 billion in the fourth quarter. The chipmaker has exceeded revenue estimates by an average of $1.8 billion over the past five quarters.
“AI is transforming every industry, company, and country. Enterprises are adopting agentic AI to revolutionize workflows. Industrial robotics investments are surging with breakthroughs in physical AI. And countries have awakened to the importance of developing their national AI and infrastructure,” he added.
Market movements
In an earnings call, Huang said that the global adoption of Nvidia technology was creating a platform shift from coding to machine learning, with traditional data centers being rebuilt for machine learning to produce AI. Soaring demand for Nvidia’s Blackwell GPU chips appears to have eased anxiety that the company could be hit by a pullback in demand from tech giants sinking billions into AI processing and data centers.
Nvidia’s value has rebounded after a summer slump, rising 45 percent from an August low. The chip stock surged by almost 200 percent this year and up over 1,100 percent in the last two years, hitting record highs following the election.
Geopolitical concerns following an escalation in the Ukraine-Russia conflict earlier this week dented risk sentiment, lifting safe-haven gold and boosting oil prices. Nvidia earnings were a clear indication that momentum in AI was only growing, however, supply concerns remained the bigger headwind rather than demand.
The world’s biggest tech companies have increased the amount they invest in AI by billions in recent quarters, positioning Nvidia as a major beneficiary.
Nvidia, which many see as a leader of the tech sector and AI demand, has helped power Wall Street to multiple record highs this year. However, an escalation in the Russia-Ukraine war, the threat of global tariff hikes from Donald Trump’s incoming administration, and the likelihood that the Federal Reserve will not cut U.S. interest rates next month have also put markets on edge.
Why Nvidia?
Founded in 1993, Nvidia revolutionized computing with its graphics processing units (GPUs) which the company initially designed for gaming but are now integral to AI workloads. “Supercomputers are among humanity’s most vital instruments, driving scientific breakthroughs and expanding the frontiers of knowledge. Twenty-five years after creating the first GPU, we have reinvented computing and sparked a new industrial revolution,” Huang said.
Nvidia’s CUDA platform and tensor core GPUs, like the A100 and H100, dominate AI model training and inference, making it a cornerstone of data center infrastructure. Its software ecosystems, such as TensorRT and Nvidia AI Enterprise, also bolster its offerings in the healthcare, automotive, and robotics industries.
“Since CUDA’s inception, we’ve driven down the cost of computing by a millionfold,” Huang said. “For some, Nvidia is a computational microscope, allowing them to see the impossibly small. For others, it’s a telescope exploring the unimaginably distant. And for many, it’s a time machine, letting them do their life’s work within their lifetime,” he added.
For decades, Intel and Advanced Micro Devices dominated the U.S. chip sector. However, those companies specialized in producing central processing units (CPUs), which serve as the foundation for basic computing and software processes. Meanwhile, Nvidia specialized in GPUs. As their name suggests, GPUs are more capable of rendering images which meant that they were first associated with video and computer games.
But it turns out GPUs are also able to perform calculations concurrently in a way that regular CPUs cannot, making them more energy efficient and better able to handle sophisticated computing demands. Over time, the other big chip makers began manufacturing their own GPUs to compete but Nvidia enjoyed a first-mover advantage in the space.
Pandemic surge turns into AI revolution
During the pandemic, the shift to remote work raised demand for data centers that could enable cloud-based computing. Moreover, the rise in interest in video games while everyone was stuck indoors accelerated Nvidia’s revenues even further.
Then, Silicon Valley, led by OpenAI, began to realize the potential of AI to transform how all companies do business. With that, the Nvidia ecosystem allowed it to position itself as the go-to source for companies that needed massive computing power to handle their AI needs. Today, virtually every major tech company, including Amazon, Google, Meta, Microsoft, and Oracle, has made use of Nvidia chips.
While other chip makers continue to try to catch up to Nvidia, the company’s 30-year GPU specialization is a massive advantage. This specialization means the company is able to charge a premium for its products. In fact, its chips are so unique that companies looking to build AI capabilities are complaining that there is a shortage of them.
Global AI market
Fortune Business Insights says that the global AI market size was valued at $515.31 billion in 2023 and is projected to grow from $621.19 billion in 2024 to $2.74 trillion by 2032, exhibiting a CAGR of 20.4 percent during the forecast period. North America dominated the global AI market with a share of 41.23 percent in 2023. Mizuho Securities estimates that Nvidia controls between 70 and 95 percent of the market for AI chips used for training and deploying models like OpenAI’s GPT.
“AI will accelerate scientific discovery, transforming industries and revolutionizing every one of the world’s $100 trillion markets,” Huang said.
The global AI market is set to grow drastically with the surge in AI applications, increased number of relevant partnerships and collaborations, rise in small-scale AI providers, changing complexities of business structure, and hyper-personalized service demands. Additionally, government initiatives and investments in AI technologies for enterprises and end users create benefits.
The pandemic crisis changed the way businesses operated and increased business complexities. In order to adopt these changes, companies shifted their work processes to the cloud. This surged the adoption of advanced technologies such as AI, machine learning, and others, marking a milestone in Nvidia’s growth prospect.
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2025 AI market predictions
Nvidia has recently shared its 2025 AI market predictions. Among the most notable predictions was made by Kimberly Powell, vice president of healthcare at the company, who said that robots will assist human clinicians in a variety of ways, from understanding and responding to human commands to performing and assisting in complex surgeries.
New virtual worlds for training robots to perform complex tasks will make autonomous surgical robots a reality. These surgical robots will perform complex surgical tasks with precision, reducing patient recovery times and decreasing the cognitive workload for surgeons. In addition, the dawn of agentic AI and multi-agent systems will address the existential challenges of workforce shortages and the rising cost of care.
Patient experience will be transformed with always-on, personalized care services while healthcare staff will collaborate with agents that help them reduce clerical work, retrieve and summarize patient histories, and recommend clinical trials and state-of-the-art treatments for their patients. Just as ChatGPT can generate an email or a poem without putting a pen to paper for trial and error, generative AI models in drug discovery can also liberate scientific thinking and exploration.
Cost of humanoid robots to decline
In addition to their smarts, one big factor that has slowed the adoption of humanoid robots has been affordability. However, as agentic AI brings new intelligence to robots, volume will pick up and costs will come down sharply. The average cost of industrial robots is expected to drop to $10,800 in 2025, down sharply from $46,000 in 2010 to $27,000 in 2017. As these devices become significantly cheaper, they’ll become as commonplace across industries as mobile devices are.
Rise of small language models
Another market prediction for AI in 2025 is the rise of small language models. To improve the functionality of robots operating at the edge, expect to see the rise of small language models that are energy-efficient and avoid latency issues associated with sending data to data centers. The shift to small language models in edge computing will improve inference in a range of industries, including automotive, retail, and advanced robotics.
Autonomous vehicles
Nvidia also expects autonomous vehicles to become more performant as developers tap into advancements in generative AI. For example, harnessing foundation models, such as vision language models, provides an opportunity to use internet-scale knowledge to solve one of the hardest problems in the autonomous vehicle (AV) field, namely that of efficiently and safely reasoning through rare corner cases.
