• Nvidia reported strong earnings, driven by demand for chips with “AI reasoning.”
• The company’s relies on its data center division, exposing it risks if spending in this area slows.
• The bull case appears intact, but its stock is likely to track the broader market instead of leading it. 

Nvidia (NVDA) is riding the AI wave, and yesterday’s quarterly earnings report provides a powerful reminder of why it’s the go-to player in AI chips. With revenue soaring and demand climbing, the company continues to solidify its position as a market leader. But with that dominance comes a critical question: Can it keep the momentum going, or is it in danger because it relies on just one rapidly evolving sector?

Two takeaways emerged from Nvidia’s earnings release. The first is an opportunity in AI reasoning, which could provide a foundation for growth in the near term. The second, however, is a growing risk—its dependence on the data center sector, which could prove problematic if it experiences a slowdown. But first, let’s review its Q4 performance and the factors driving its bottom line.

Nvidia’s Q4 earnings

Nvidia’s earnings report for the fourth quarter of fiscal 2025, released yesterday, reinforced the company’s commanding position in the tech industry, particularly in AI and data centers. Revenue reached an impressive $39.3 billion, a 78% increase year-over-year and a 12% rise from the previous quarter. Earnings per share (EPS) came in at $0.89, a 14% quarterly increase and an 82% jump from the same period last year. For the full fiscal year, its revenue surged 114%, reaching $130.5 billion, while net income more than doubled to $72.9 billion. These results reflect consistent growth and market dominance, fueled by robust demand for AI-focused chips. 

The company’s forward guidance of $43 billion in revenue for the first quarter of fiscal 2026 was well above analysts’ anticipated $41.8 billion. While the numbers showcase Nvidia’s market-leading position, they also point to a more nuanced future. Its Q1 guidance suggests a year-over-year growth rate of 65%—still impressive—but a sharp slowdown from the previous year’s eye-popping 262%. It appears the breakneck pace of the AI boom is decelerating. 

Nvidia’s data center division, which now comprises a remarkable 91% of total revenue—up from just 60% two years ago—has become the bedrock of the company’s financial performance. As demand for AI and cloud computing continues to surge, it has positioned itself as the go-to supplier of hardware for these technologies. Its graphics processing units (GPUs) are indispensable for AI training, inference and high-performance computing (HPC). They power everything from cutting-edge supercomputers to enterprise cloud services. 

Nvidia’s dominance in this area is undeniable, with many of the world’s largest cloud service providers—including AWS, Google Cloud and Microsoft Azure—turning to the company for AI acceleration. Analysts maintain its AI chips are several years ahead of its competitors, underscoring the company’s pivotal role in shaping the future. 

Advances in “AI reasoning”

During the earnings call, management emphasized the growing importance of “AI reasoning” to call centers. It captured the world’s attention after the release of DeepSeek’s model and presents an opportunity and a challenge. In a CNBC interview following the earnings call, Nvidia CEO Jensen Huang addressed the market’s reaction to the reasoning capabilities of DeepSeek-R1. Initially, investors feared the increased efficiency of DeepSeek’s model, which reportedly requires fewer computational resources than its competitors. That could signal a decline in demand for Nvidia’s chips, but Huang argued the opposite is true, asserting that reasoning is a “compute intensive” process and will likely increase, not decrease, the demand for hardware.

As AI models evolve, they are expected to require even more computational power to handle increasingly complex problem-solving. That could increase sales of Nvidia’s new Blackwell chips. Huang made this point clear in a previous interview with DDN CEO Alex Bouzari, CEO of privately held DirectData Networks, or DDN. He said this: “Reasoning is a fairly compute-intensive part. The market responded to [DeepSeek] R1 as in ‘Oh my gosh, AI is finished. It dropped out of the sky, we don’t need to do any computing anymore.’ It’s exactly the opposite.” As the models grow in sophistication, the computational demands will only rise, creating a growing need for powerful GPUs like Blackwell.

AI reasoning occurs when models don’t simply provide answers but instead reflect on their analysis step-by-step, breaking down complex problems into smaller, more manageable tasks. This “chain-of-thought reasoning” enables AI to generate more accurate responses by performing multiple computations before arriving at a conclusion. However, some skeptics argue what is being labeled as “reasoning” might, in fact, be an advanced form of pattern recognition, where the AI mimics human-like thought without truly understanding or “thinking.” Either way the so-called reasoning models will demand greater computational power. That makes Nvidia’s next-generation chips, like the Blackwell series, well-positioned to benefit from the increasing complexity of AI tasks.

DeepSeek’s success in demonstrating smaller models can perform advanced reasoning more efficiently has raised questions about the cost-effectiveness of traditional AI chip technology. But Huang remains steadfast in the belief that as AI capabilities advance, the demand for increasingly powerful chips will only rise—and in greater quantities. The theory known as the Jevons Paradox supports his view. It posits that “increased efficiency in a resource often leads to higher consumption of that resource.” If that holds true, Nvidia is clearly poised to capitalize. 

Risky reliance on data centers

Nvidia’s earnings release revealed the growing concentration of the company’s revenue in its data center division, which now accounts for 91% of total revenue—up from around 60% from two years ago. While this sector has been a major driver of the company’s remarkable growth, it also presents a risk to the company’s stability. A slowdown in cloud spending or AI adoption could have a disproportionate effect on Nvidia’s financial performance. Additionally, regulatory risks, such as new restrictions on the sale of advanced chips to countries like China, could also disrupt its growth trajectory. 

The turbulence caused by DeepSeek’s AI model—using fewer chips more efficiently—underscores this potential risk for Nvidia. DeepSeek’s approach demonstrated that advanced reasoning tasks can be handled with less computational power. It also raised concern about the demand for Nvidia’s high-performance chips. If more efficient AI models continue to emerge, requiring fewer chips to achieve the same or better results, it could dampen demand for Nvidia’s products and services. This shift, where efficiency begins to outweigh raw processing power, could therefore threaten the company’s dominant position, stiffle its potential for growth and call its market valuation into question. 

While Nvidia is diversifying its business, particularly in its automotive and robotics divisions, these areas still represent a small portion of total revenue. The automotive division, for example, posted 103% year-over-year growth last quarter, but sales only amounted to $570 million—not nearly enough to offset a slowdown in the data center division. Similarly, while gaming and professional visualization are strategically important, their growth (or lack thereof) is also insufficient. In the most recent quarter, revenue in the gaming division fell 11% year-over-year, while sales in the professional visualization division grew by just 10%. It’s clear Nvidia would struggle to navigate a downturn in its largest division.

Nvidia’s growing dependence on its data center business underscores the risks of a highly concentrated model. Recent reports that Microsoft (MSFT) has scaled back some of its data center investments heighten this concern. If other tech giants follow suit, it could dampen demand for Nvidia’s chips, exposing the company to greater volatility. To mitigate this risk, Nvidia should strike a balance between maintaining its AI leadership and expanding into new, less-concentrated markets. The next few quarters will be critical in determining how well it navigates this concentration risk while continuing to fortify its core business.

Final takeaways

No matter how you cut it, Nvidia posted an impressive Q4 earnings report. The company continues to grow at an extraordinary pace, with revenue surging 78% year-over-year, and gross margins above 70%. The strong demand for its cutting-edge chips, particularly in AI and cloud computing, bolster its dominant position in the market. Moreover, advances in AI reasoning present a promising opportunity, likely driving sustained growth in sales as the need for more powerful GPUs increases. Coupled with the company’s strong moat, created by its CUDA software platform, Nvidia can maintain its competitive edge—making it tough for competitors like Advanced Micro Devices (AMD) to make inroads.

However, risks remain because of Nvidia’s growing concentration in data centers. A downturn in cloud spending or AI adoption could have a disproportionate effect on Nvidia’s financial performance. The recent news of Microsoft scaling back data center investments increases the uncertainty, and other major tech players may follow suit. Until Nvidia can diversify and establish another high-growth, revenue-generating niche, it’s unlikely to replicate the explosive growth of 2023 and 2024 in the short term. In the interim, the bull case remains intact, but Nvidia’s shares are likely to move in sync with the broader market instead of driving it.

Andrew Prochnow has more than 15 years of experience trading the global financial markets, including 10 years as a professional options trader. Andrew is a contributing editor of Luckbox Magazine.

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