Can NVIDIA be stopped? Inside the $44bn quarter that redefined the AI infrastructure race

NVIDIA Corporation (NASDAQ: NVDA) posted another seismic quarter to open fiscal 2026, clocking in $44.1 billion in revenue—up 69% year-over-year. But while headlines zeroed in on a $4.5 billion write-down tied to unsold H20 chips amid escalating U.S.-China tensions, the real story lies beneath the numbers: NVIDIA is evolving into the central nervous system of global artificial intelligence infrastructure. This is no longer just about GPU sales. It’s about owning the stack—the compute, the platform, and the future of automation.

The quarter, which ended April 27, 2025, underscores a broader inflection point in enterprise technology and geopolitical power dynamics. NVIDIA isn’t merely outperforming; it’s reshaping the way the world builds and deploys intelligent systems.

Why NVIDIA’s Revenue Surge Isn’t Just About Chips

At first glance, the topline growth looks like a classic story of demand outpacing supply. But delve deeper, and a more fundamental transformation is apparent. Data center revenue came in at $39.1 billion, a 73% year-on-year explosion and up 10% sequentially. What’s driving this is not simply the adoption of more powerful GPUs, but the convergence of sovereign AI ambitions, hyperscale infrastructure investment, and the emergence of AI agents that require continual reasoning and token inference.

Jensen Huang, NVIDIA’s co-founder and CEO, compared the rise of AI to the advent of electricity and the internet—core infrastructure without which modern economies cannot function. That metaphor is rapidly becoming reality as national governments, research institutions, and hyperscalers begin treating NVIDIA-based compute platforms as essential to their digital sovereignty agendas.

This quarter’s performance is a reflection of NVIDIA’s AI factory thesis coming to life, not just in Silicon Valley, but in Abu Dhabi, Riyadh, and Taipei.

How the Blackwell Architecture Is Powering a New Industrial Era

At the center of this transformation is Blackwell. The newly introduced NVL72 supercomputing system, based on the Blackwell GPU architecture, marks a major step in AI reasoning capacity. It’s not just faster—it’s smarter, optimized for inference, agentic logic, and real-time orchestration. Blackwell is now in full-scale production, with deployments underway across AWS, Oracle Cloud, Google Cloud, and Microsoft Azure.

But NVIDIA is no longer just supplying chips—it’s dictating system architecture. Its new DGX SuperPOD, NVLink Fusion fabric, and Spectrum-X networking stack allow enterprises to build full-scale AI factories capable of training and deploying generative AI and humanoid robotics at industrial scale. These aren’t modular add-ons—they’re designed as vertically integrated platforms.

In parallel, the company launched the Llama Nemotron family of models to accelerate development of next-generation AI agents, alongside DGX Cloud Lepton for connecting developers to a global compute mesh. NVIDIA’s AI Data Platform now serves as a customizable reference layer for inference workloads, positioning the company as both the builder and the benchmark for AI performance.

What the H20 Export Ban Tells Us About U.S.-China Tech Tensions

On April 9, 2025, the U.S. government imposed new restrictions requiring licenses for exports of NVIDIA’s H20 chips into China. The chips, engineered to comply with earlier export bans on A100 and H100 GPUs, were designed specifically for the Chinese market. But the new ruling effectively nullified those adaptations.

NVIDIA had already booked $4.6 billion in H20 revenue for Q1 FY26, but was unable to ship another $2.5 billion in expected sales. The result was a $4.5 billion charge against excess inventory and supplier purchase obligations, dragging down gross margins to 60.5% GAAP and 61.0% non-GAAP. Excluding the charge, NVIDIA’s non-GAAP gross margin would have landed at 71.3%.

While painful, this episode underscores a broader risk: the increasing politicization of supply chains and export controls. With AI compute now viewed as a national security asset, NVIDIA finds itself at the center of a growing battle for technological influence. Its ability to pivot—by investing in domestic U.S. manufacturing and diversifying geographically—is now as important as its technical roadmap.

Why Wall Street Still Loves NVIDIA (Despite the Hit)

Despite the H20 cloud, Wall Street sentiment remains overwhelmingly bullish. As of May 29, 2025, NVIDIA shares were trading at $134.81—down slightly by 0.5% on the day, but up over 25% in the past month. The rally reflects investor confidence in the durability of AI infrastructure demand and the scalability of Blackwell-based systems.

Analyst price targets range from $120 to $160, with some ultra-bullish forecasts extending to $220. Retail sentiment on Reddit’s r/stocks and StockTwits supports a “buy-the-dip” narrative, while institutional investors have shown robust inflows in recent weeks. With adjusted EPS at $0.96 (excluding H20-related impacts) and free cash flow at $26.1 billion, NVIDIA’s capital efficiency and earnings quality remain a magnet for long-term capital.

The dividend, albeit modest at $0.01 per share, is symbolic of consistent shareholder returns. But it’s NVIDIA’s command over AI capital spending—not its dividend yield—that keeps asset managers overweight on the stock.

Can NVIDIA Maintain Its AI Infrastructure Monopoly?

One of the central questions emerging from this quarter is whether NVIDIA’s dominance is sustainable—or whether competitors will erode its lead. AMD and Intel continue to push alternatives, and Google’s TPU and Amazon’s Trainium offer internal competition within the hyperscale cloud market.

Yet NVIDIA is responding by moving up the stack. Its collaborations with OpenAI, Alphabet, Oracle, SAP, and Siemens embed its platforms deep into software layers. The NVIDIA Omniverse, Cosmos, and Isaac stacks are extending the company’s footprint from data center GPUs to digital twins, robotics, and AV simulation. The introduction of Isaac GR00T-Dreams—a motion data generator for humanoid robotics—illustrates how NVIDIA is laying the groundwork for physical AI dominance.

By creating a platform ecosystem akin to Apple’s iOS or Microsoft’s Windows, NVIDIA is setting up long-term developer and infrastructure lock-in. As the AI era matures, this kind of control over both hardware and orchestration software becomes a formidable advantage.

What Happens If NVIDIA Becomes the “Electricity” of AI?

If Jensen Huang’s vision plays out—where NVIDIA becomes the global utility layer for AI compute—the implications go far beyond quarterly earnings. In such a world, NVIDIA would be to autonomous systems what Intel once was to personal computing. The company’s influence would extend into policy, national defense, public health, and financial infrastructure.

But with this centrality comes risk. Overdependence on a single provider for AI infrastructure could raise questions about resilience, antitrust, and national sovereignty. Governments are already exploring “sovereign compute” strategies, not to replace NVIDIA, but to ensure they are not entirely beholden to it.

Still, in Q1 FY26, there is little sign of erosion. NVIDIA’s $44.1 billion revenue run, strategic expansion into sovereign data centers, and unrelenting push into full-stack AI solutions signal one thing clearly: this is NVIDIA’s moment, and it is defining the infrastructure of the next industrial revolution.