Nvidia Faces Its Biggest Test Yet: Earnings Set to Reveal Whether the AI Gold Rush Still Has Fuel

After three years of powering one of the most extraordinary rallies in U.S. market history, Nvidia now finds itself at a crossroads.

When the AI chip giant reports quarterly earnings Wednesday, investors won’t just be looking at revenue and profit. They’ll be searching for something far more consequential: proof that the artificial-intelligence spending boom driving Nvidia’s meteoric rise is still sustainable—and that rivals aren’t quietly building an exit ramp from its dominance.

Nvidia’s growth has been tightly coupled to a historic surge in capital expenditures from hyperscalers—massive cloud and platform companies racing to build AI infrastructure. Collectively, those firms are expected to deploy roughly $630 billion into AI-related spending, constructing data centers packed with Nvidia’s high-performance processors.

But the same customers fueling Nvidia’s ascent are increasingly exploring ways to reduce their dependence.

Alphabet, through its Google division, has emerged as a formidable challenger by promoting its in-house Tensor Processing Units (TPUs). Google recently struck agreements to supply chips to Anthropic, the creator of the Claude chatbot, and is reportedly in talks to expand supply relationships with Meta, historically one of Nvidia’s largest customers.

Meanwhile, Advanced Micro Devices is preparing to unveil a flagship AI server later this year—another signal that competitors are targeting Nvidia’s most lucrative turf.

To reinforce its lead, Nvidia has moved aggressively to secure new footholds in AI computing.

Last year, the company reportedly struck a $20 billion deal with Groq to license technology tailored for inference—the phase where trained AI models generate real-time responses. Analysts see inference as the next massive revenue frontier as AI applications shift from development to everyday deployment.

Nvidia has also agreed to sell millions of chips to Meta in a fresh supply arrangement, underscoring how demand for its hardware remains intense even as customers diversify.

Yet Nvidia itself has raised eyebrows by slowing discussions around what had been framed as a potential $100 billion investment into OpenAI, reportedly scaling that figure back to roughly $30 billion. For some investors, that recalibration hints at a more measured pace of AI infrastructure expansion.

“This earnings in particular is important because people are so concerned about AI spending—whether we’re in a bubble,” said Ivana Delevska, chief investment officer at Spear Invest.

Nvidia’s stock performance reflects that uncertainty. After years of explosive gains, shares have risen only about 2% so far in 2026, suggesting markets are waiting for confirmation that growth can continue at scale.

Analysts forecast another blockbuster quarter—but with signs of moderation.

Even that “slowdown” would represent expansion most companies can only imagine.

Nvidia has beaten sales expectations for 13 consecutive quarters, though the size of those beats has narrowed—a sign comparisons are getting tougher as the company scales.

Despite rising competition, analysts widely believe Nvidia will remain the primary beneficiary of hyperscalers’ AI infrastructure buildout in 2026.

Its GPUs continue to function as the “brains” of AI servers handling enormous workloads, and company executives hinted earlier this year that customers are already discussing orders for next-generation data centers extending into 2027.

Some analysts expect Nvidia to update a massive $500 billion order backlog figure first disclosed last October, a number that—if expanded—would reinforce confidence in long-term demand visibility.

The biggest constraint on Nvidia’s near-term growth may not be demand, but manufacturing capacity.

Like its rivals, Nvidia relies heavily on TSMC for advanced chip fabrication. Competition for scarce 3-nanometer production lines has intensified as AI chipmakers scramble for supply.

“We think Nvidia will meet expectations, but it is hard to see them delivering much upside in light of TSMC capacity,” said Jay Goldberg of Seaport Research Partners.

Another potential growth lever is China.

After U.S. export restrictions limited sales, Nvidia is now working to reintroduce its H200 AI chips into the Chinese market. CEO Jensen Huang recently said he hopes licensing approvals will soon be finalized, reopening access to a critical customer base.

Competitors are already moving: AMD has re-added AI chip sales to China into its forecasts after receiving approval to ship modified processors there.

Nvidia is expected to post an adjusted gross margin of roughly 75%, reflecting formidable pricing power driven by insatiable demand for its most advanced chips.

Analysts also believe the company has largely insulated itself from the global memory supply crunch, having secured high-bandwidth memory allocations well in advance.

Nvidia’s earnings report has become more than a quarterly update—it’s a referendum on the trajectory of the entire AI economy.

If results confirm sustained demand and strong forward guidance, investors may regain confidence that the AI buildout is still in its early innings. If not, markets could begin recalibrating expectations for one of the most transformative—and expensive—technology shifts in modern history.

For now, Nvidia remains at the center of that transformation.

The question is whether it will continue to lead the AI revolution—or start sharing the stage with the very customers who helped build it.