Nvidia remains the undisputed heavyweight of AI chips, yet its stock is barely outperforming the S&P 500. Four forces explain the disconnect.

Nvidia's business has rarely looked stronger.

Its AI infrastructure franchise continues to expand at extraordinary speed. Its newest chip platforms are rolling out. Networking is becoming a major growth engine. The company remains deeply embedded in the world's largest AI projects.

And yet the stock is behaving strangely.

Nvidia shares are up roughly 14% this year, only slightly ahead of the 12% gain in the S&P 500. That is a striking result for a company widely considered the central beneficiary of the artificial-intelligence boom. Meanwhile, some companies elsewhere in the AI chip supply chain have dramatically outpaced it: Micron has risen about 225%, Intel about 138% and AMD about 124%, according to the Yahoo Finance analysis.

The disconnect becomes even more unusual when Nvidia's earnings history is considered.

The stock has fallen after earnings in six of the past eight quarters, including the last four, according to Yahoo Finance's AlphaSpace analysis.

So why is one of the strongest companies in technology struggling to produce the kind of stock-market gains investors became accustomed to?

The answer appears to involve four competing forces: Nvidia's enormous size, growing fear of an AI bust, the mathematical difficulty of sustaining its growth rate and concerns that both growth and margins could eventually peak.

The first reason is brutally simple.

Nvidia is now enormous.

Its market capitalization is around $5.2 trillion, according to Raymond James analyst Simon Leopold, cited by Yahoo Finance.

At that size, investors need to commit extraordinary amounts of capital to produce extraordinary additional gains.

Nvidia no longer has the luxury of being a relatively small company discovering a new market.

It is already one of the largest companies in financial history.

That creates a mathematical challenge.

A company can grow rapidly and still produce mediocre stock returns if its starting valuation is already huge and investor expectations are already elevated.

The market needs a stream of new surprises.

Another blockbuster quarter.

Another major acceleration.

Another technological breakthrough.

Another expansion of market share.

Simply being excellent is no longer enough.

Investors have already priced in a substantial amount of excellence.

That is perhaps Nvidia's biggest success—and one of its biggest problems.

Leopold's first concern is essentially about ownership capacity.

How much more Nvidia can investors reasonably own?

Large institutional portfolios already have substantial exposure to the stock.

Many technology funds already hold it.

Index funds naturally own it.

AI-themed funds own it.

Retail investors own it.

Hedge funds own it.

The company has become so central to the AI trade that increasing exposure requires investors to reduce something else.

That creates a ceiling of sorts.

It does not mean Nvidia cannot rise.

It means the company needs new sources of demand for the stock or continued earnings growth large enough to overwhelm the valuation constraint.

That is a much harder task.

The second issue is psychological.

The AI boom has been extraordinarily profitable.

But the larger the boom becomes, the more investors begin asking what happens if the spending cycle slows.

This is not necessarily a prediction that AI demand will collapse.

It is an acknowledgment that expectations have become massive.

Data centers are consuming enormous amounts of capital.

Hyperscalers are spending hundreds of billions of dollars on infrastructure.

AI companies are raising huge amounts of money.

Startups are being valued at extraordinary levels.

And Nvidia is benefiting from almost every part of that spending cycle.

Investors therefore face a classic boom-cycle question:

What happens when customers eventually need to prove that all this spending is generating economic returns?

That fear has become more visible across technology markets.

Reuters noted that Nvidia is now facing scrutiny over whether its enormous financial commitments to AI infrastructure could distort market dynamics or artificially stimulate demand, while analysts are also watching increasing competition from custom AI chips.

As long as AI spending accelerates, those concerns can remain theoretical.

If spending growth slows, they suddenly become central.

The third reason is mathematical rather than emotional.

Nvidia has grown at a rate that is extremely difficult to maintain.

When a company is small, a new product or customer can dramatically change its financial results.

When annual revenue reaches enormous levels, even a large new business may only produce a modest percentage increase.

This is the law of large numbers.

Nvidia has not stopped growing.

The problem is that its past growth rates create an almost impossible benchmark.

Investors have become accustomed to extraordinary percentages.

If growth falls from spectacular to merely excellent, the stock can disappoint even while the underlying company remains exceptional.

That is one of the central paradoxes surrounding today's Nvidia.

The company can beat analyst expectations and still fall because investors were expecting a much larger beat.

Market performance is determined by the difference between reality and expectations.

And Nvidia's expectations are extremely high.

Nvidia has repeatedly delivered strong financial results.

Yet the stock has declined after earnings in six of its past eight reports.

This pattern reveals how difficult the company's valuation has become.

A conventional company might jump after reporting strong numbers.

Nvidia increasingly needs to produce something exceptional.

Investors want evidence that demand is accelerating faster than expected.

They want guidance that remains ahead of consensus.

They want management to describe a pipeline that looks stronger than the already bullish forecasts.

Anything less can create disappointment.

That is why today's earnings report is being watched so closely.

The fourth issue may be the most important.

Nvidia's incredible growth has also been accompanied by extraordinarily strong margins.

Those margins cannot expand forever.

As the company becomes larger and competition increases, investors eventually begin asking whether profitability is near its peak.

Memory costs are one concern.

AI systems require enormous amounts of high-bandwidth memory and other advanced components, and rising component prices could pressure the economics of AI infrastructure. Recent market reporting has highlighted memory inflation as an important issue investors are monitoring around Nvidia's earnings.

Competition is another.

AMD is investing heavily in AI accelerators.

Google, Amazon and Microsoft are developing custom silicon.

Companies such as Cerebras are pursuing alternative approaches.

Intel is attempting to regain ground.

Nvidia remains far ahead, but the market is increasingly aware that its competitive position does not exist in a vacuum.

And yet the Nvidia story contains a remarkable contradiction.

Despite the stock's relatively modest gains, its valuation is not particularly extreme compared with the broader market.

Raymond James' Leopold estimates Nvidia trades at less than 15 times expected 2027 GAAP earnings, compared with approximately 18.6 times for the S&P 500.

That would be unusual for a company growing as rapidly as Nvidia.

Leopold argues the discount is difficult to justify because Nvidia's projected sales and net-income growth remain above 20% in 2028 estimates, while the company retains significant barriers to entry, including its CUDA software ecosystem and leading GPU performance.

This creates a fascinating investment paradox.

Nvidia looks expensive because the company is worth trillions.

But based on projected earnings, the stock may not be expensive at all.

That does not guarantee the shares will rise.

It means the market is demanding an unusually large margin of safety before rewarding the stock with a higher multiple.

The next potential catalyst may not be GPUs alone.

Leopold points to Nvidia's CPU business as an important future growth opportunity.

CPUs currently represent roughly 3% of Nvidia's sales, according to his estimates, but he expects that share to rise toward approximately 5% by 2028, driven in part by agentic AI workloads.

That may sound small.

But for a company Nvidia's size, even a small percentage of revenue can represent billions of dollars.

The broader significance is strategic.

Nvidia wants to become more than the company that supplies AI accelerators.

It wants to provide the complete computing platform around AI.

That includes GPUs.

CPUs.

Networking.

Systems.

Software.

Interconnect technology.

And increasingly, the infrastructure connecting all of it.

Recent reporting has highlighted the rapid growth of Nvidia's networking business, which has become one of the company's fastest-growing areas. That diversification could help reduce dependence on any single product cycle.

Investors will also be watching the company's transition from Blackwell to Rubin.

The next generation matters because Nvidia's growth depends not only on existing demand but on customers continually upgrading to more powerful architectures.

Reuters reported that analysts expect Rubin to become an important contributor to Nvidia's third-quarter sales.

A smooth transition would reassure investors that Nvidia can maintain its product cycle advantage.

Any delays, supply constraints or weaker-than-expected demand would create concerns about the sustainability of the growth machine.

For years, Nvidia's investment case was simple.

AI is growing.

Nvidia has the best chips.

Therefore Nvidia will grow extraordinarily fast.

Now the market needs something more sophisticated.

Investors want to know how the company behaves as AI becomes a mature industry.

Can Nvidia maintain its margins?

Can it defend CUDA?

Can it benefit from custom silicon rather than simply fight it?

Can networking become a major second business?

Can CPUs become a meaningful contributor?

Can the company continue growing once revenue reaches historic levels?

And can the AI boom produce enough economic value to justify the enormous infrastructure spending behind it?

Those are harder questions.

But they are also the questions that will determine whether Nvidia deserves to return to extraordinary stock-market performance.

Nvidia's results arriving Wednesday will therefore matter beyond the headline EPS number.

The market will watch guidance.

It will watch gross margins.

It will watch data-center growth.

It will listen to CEO Jensen Huang's comments on Blackwell and Rubin demand.

It will watch the company's China strategy.

It will look for signs that customers are still willing to spend enormous sums on AI infrastructure.

And it will listen for evidence that Nvidia is broadening beyond GPUs.

Recent market reporting suggests consensus expectations center around roughly $92 billion to $95 billion of quarterly revenue, while some analysts believe future-quarter revenue could exceed $110 billion if newer platforms accelerate as expected.

At this point, the difference between “great” and “exceptional” could determine the stock's reaction.

That is perhaps the clearest explanation for the stock's unusual behavior.

Nvidia has become so large and so successful that investors now demand proof that the company can reinvent its growth story repeatedly.

The current AI boom created Nvidia's first gigantic growth engine.

Now the company needs to prove it can create the second.

That could come from networking.

CPUs.

New AI architectures.

Software.

Custom-chip integration.

Or continued dominance of accelerated computing.

If Nvidia delivers on several of those fronts, today's muted stock performance could eventually look like a temporary pause.

But if growth slows, margins peak and AI spending becomes more selective, the market may conclude that the extraordinary phase of Nvidia's expansion is beginning to mature.

For now, the biggest irony is that Nvidia's stock is lagging not because the company is failing.

It is lagging because the company has become so successful that ordinary success is no longer enough.

Wall Street already knows Nvidia is great.

The stock is waiting to find out whether Nvidia can still surprise a market that has spent years expecting miracles.

Source basis: Yahoo Finance's August 26, 2026 analysis, supplemented by current Reuters and market coverage ahead of Nvidia's earnings report.