Nvidia $NVDA (NVDA) has become the almost undisputed poster child of the AI boom — and now it’s time to show the receipts.
The $3.3 trillion chipmaker will report its fiscal first-quarter earnings for 2026 on Wednesday, and expectations are enormous. Analysts forecast a revenue surge to $43.26 billion, nearly 66% higher than the same quarter a year ago, with adjusted earnings per share jumping to $0.88 from $0.61, a growth of about 44%.
Still, those forecasts might be selling the semiconductor giant short. The company has a habit of surpassing earnings expectations — topping earnings estimates by an average of about 7% in the last two quarters.
Nvidia, whose chips have become the backbone of modern artificial intelligence, has been on a staggering run. But with stakes this high, investors are laser-focused on whether Nvidia’s latest bets — such as its next-gen Blackwell platform, deepening cloud partnerships, and response to U.S.-China chip tensions — will deliver the kind of blockbuster quarter the markets have come to expect.
The AI engine that keeps on giving
At the heart of Nvidia’s revenue machine is its Data Center business, which has grown into its largest and most profitable segment thanks to insatiable demand from cloud providers, AI startups, and enterprise customers building foundation models. Analysts expect this division alone to generate $21.27 billion in Q1 revenue.
CEO Jensen Huang has positioned Nvidia not just as a chipmaker but as the infrastructure layer powering the AI revolution. The company is hoping that narrative continues with Blackwell, the GPU architecture introduced in March that Huang says will unlock the training and deployment of models that are orders of magnitude more powerful than current systems.
The flagship GB200 Grace Blackwell Superchip is already being integrated by hyperscalers such as Amazon $AMZN Web Services (AMZN), Google $GOOGL Cloud (GOOGL), Microsoft $MSFT Azure (MSFT), and Oracle $ORCL (ORCL).
Nvidia may be dominant, but it’s not operating in a vacuum. Rival chipmakers like AMD $AMD (AMD) and Intel $INTC (INTC) are racing to close the performance gap, while companies such as Google, Amazon, and Microsoft are doubling down on custom silicon to reduce reliance on third-party GPUs. At the same time, a wave of Chinese AI chipmakers is emerging as Nvidia contends with export restrictions, creating fresh competitive pressure in one of its most important markets.
Hardware isn’t the whole story
But Nvidia isn’t just about GPUs anymore. As investor expectations climb, the company is quietly broadening its AI stack — moving beyond silicon into networking, software, and cloud integration in a bid to become the full-stack backbone of AI infrastructure. Nvidia is deepening its economic moat and creating more stable, recurring revenue streams that could smooth earnings volatility over time.
Through partnerships with major cloud providers, Nvidia is embedding itself into the very platforms AI developers rely on. Basically: Nvidia is trying to become more than just a supplier of AI tools. The company wants to become a critical platform for AI development itself.
Investors will be watching closely for clear evidence that Nvidia’s expansion beyond GPUs is starting to pay off in revenue. Wall Street wants to see whether the company’s networking products are contributing to meaningful growth within the data center segment.
Margins will also be a key focus. Networking and software typically deliver higher profitability than hardware, so any signs of margin expansion would support the narrative that Nvidia is transforming into a more durable, high-margin platform business. (Which could reassure investors that Nvidia’s growth is sustainable and not just tied to cyclical chip demand.)
Finally, Wall Street will listen for signs that Nvidia’s AI software stack is gaining adoption among large enterprises outside the hyperscaler ecosystem — into sectors such as healthcare, finance, and manufacturing — which would highlight the long-term potential of Nvidia’s platform strategy and reinforce the company’s role as the backbone of AI development.
The China complication
There is, of course, a major x-factor: China.
Nvidia is ground zero in the U.S.-China tech rivalry — its GPUs might just be the most valuable components in the AI arms race, and its position is increasingly shaped by policy, not just engineering.
Nvidia has long relied on the Chinese market for a sizable chunk of its revenue, but that has changed dramatically in the wake of tightening U.S. export controls and tariffs. Huang said recently that years of U.S. restrictions on AI chip exports were a strategic misfire that cost Nvidia billions and handed Chinese rivals a powerful incentive to innovate.
Nvidia, which was once dominant in China with a market share approaching 95% at the start of the Biden administration, now holds just 50%, Huang has said. To defend — and expand — its foothold, Nvidia is looking to establish an R&D center in Shanghai and is reportedly preparing further downgraded chip models that comply with U.S. rules.
Investors will be looking to see the impact of U.S. export controls: how much they’ve dented sales, whether downgraded chips can sustain demand in China, and more. Wall Street will also be watching for any supply chain stress; Nvidia relies heavily on TSMC $TSM (TSM) for manufacturing, and its capacity constraints remain a gating factor.
While the company remains dominant in many global markets — and is expanding into the Middle East through Saudi Arabia, in what one analyst called a “watershed moment,” and the United Arab Emirates — Wall Street will be looking for updates on how Nvidia plans to navigate what could be its most challenging international landscape in years.
Is the AI boom real — or just priced in?
Nvidia is the poster child of the AI trade, and its financial performance serves as a high-frequency indicator of how far the generative AI economy has progressed from hype to hard returns.
A strong beat would signal that tech giants (see: Microsoft, Google, Amazon) are continuing to pour billions into AI infrastructure, reaffirming the AI investment thesis that has largely powered the Nasdaq $NDAQ’s rally. Nvidia’s valuation is rich, but so are many other AI-linked names.
If Nvidia meets or beats expectations, it could justify the current risk appetite for high-growth names. But a miss, even a tiny one, could trigger a sentiment reset. If forward guidance is strong, it’ll show that enterprises are starting to spend on AI beyond experiments — e.g., in areas such as software integration, inference, and LLM deployment.
Will the rally continue?
Nvidia’s stock has been on quite a wild ride in 2025. After hitting a high earlier in the year, shares fell amid broader market turbulence and investor anxiety about whether the AI trade had gotten overheated.
President Donald Trump’s April 2 “Liberation Day” announcement sent the stock into a sharp dip, but it has since rebounded. Now, this quarter’s results could be a clearing event that could reestablish momentum.
One looming concern: supply chain capacity. Demand for Nvidia’s chips continues to exceed supply, and while the company has worked to scale production, it may still be leaving money on the table simply due to how long it takes to manufacture and deliver its most advanced products.
Investors will also be watching closely for details on capital expenditures and supply chain resilience. Wall Street will want to see how aggressively Nvidia is investing to expand capacity, whether through additional foundry partnerships or securing more critical components. Any signs that supply constraints are easing — or worsening — could influence how sustainable current growth trajectories appear.
But the big question now is whether Nvidia can not only meet but beat expectations — something it has done consistently. While Nvidia remains possibly the most important company in the world’s hottest tech sector, that also means the pressure is greater than ever.