The $500 Billion Question (and 4 More) for Jensen Huang

Nvidia’s fiscal 2026 third-quarter earnings report, arguably the most critical of the season, is slated for release after Wednesday’s market close. All eyes will be on CEO Jensen Huang as he navigates intense scrutiny regarding the ambitious spending commitments fueling the artificial intelligence boom and the strategies tech firms, both giants and emerging players, will employ to finance these investments. Year-to-date, Nvidia shares have surged approximately 35% as of Tuesday’s close, hovering around $181, nearly doubling their 2025 low reached on April 4th.

This performance arrives amid significant shifts in U.S. trade policy, with evolving tariff agreements shaping the landscape since April 2025. Nvidia’s stock, buoyed by these trade developments and its strategic positioning in the AI market, reached a record high of $207 on October 29th, marking its first close above a $5 trillion market capitalization.

The stock’s impressive trajectory has been mirrored by its earnings growth, resulting in a forward price-to-earnings ratio of roughly 27 times fiscal 2027 earnings estimates – a historically low valuation for the company. It’s crucial to note that Nvidia’s earnings calendar reflects its fiscal year, making Wednesday’s report its fiscal 2026 third quarter, which ended in October. Unlike prior quarters, expectations are tempered to a degree, with the stock not exhibiting pre-earnings frenzy. Concerns surrounding AI valuations, which have impacted the broader market, have begun to influence sentiment around Nvidia. The stock has retreated 12% from its peak, now trading around a $4.4 trillion market cap.

What to Expect – and Why

Analysts, as per LSEG data, anticipate Nvidia to report a 53% year-over-year increase in fiscal Q3 earnings per share (EPS) to $1.25, based on revenue of $54.92 billion, representing a 56% increase compared to the same period last year. FactSet data reveals that Wall Street expects a 59% upswing in data center segment revenue for the October quarter, reaching $49.04 billion.

Looking forward to the current fiscal fourth quarter ending in January, analysts project management to guide revenue towards approximately $62.17 billion, with a gross margin of around 74%.

Furthermore, a crucial sign of robust demand emerged on November 10th when reports surfaced that CEO Jensen Huang had contacted Taiwan Semiconductor Manufacturing (TSMC), requesting increased wafer production. This signals Huang’s anticipation of sustained robust demand for Nvidia’s AI chips, aligning with his “$500 billion in order visibility” projection shared at the company’s GTC event.

While Nvidia’s report carries considerable weight, insight into 2026’s outlook already exists. The major hyperscale cloud players – Amazon, Microsoft, and Alphabet’s Google, along with Meta Platforms – have unequivocally stated that their AI infrastructure spending will not only remain steady but will further increase in 2026. All have raised their investment projections, citing the requirement for significantly more computing power than current capacity provides.

Adding to this, OpenAI continues to pursue massive commitments for enhanced power and compute capabilities. Amazon-backed Anthropic recently committed $50 billion towards building data center infrastructure across the nation. Microsoft further solidified its AI commitment by announcing new partnerships with both Anthropic and Nvidia. Anthropic pledged to acquire $30 billion in Azure cloud capacity from Microsoft, alongside computing capabilities from Nvidia’s Grace Blackwell and Vera Rubin systems. These commitments come with Microsoft investing $5 billion into Anthropic and Nvidia investing $10 billion in the startup.

While these major players are undoubtedly pursuing internal specialized chip development, expect their investments with Nvidia to grow synergistically with those internal projects. The industry standard position of Nvidia’s platform with AI software development, along with its versatility, carries significant advantages. This flexibility enables a broader support for a wider array of applications which is paramount for ensuring optimal use of capacity, regardless of evolving customer needs.

The flexibility Nvidia offers is further seen with the neocloud players like CoreWeave. Ahead of CoreWeave’s earnings, Loop Capital analysts noted that their research revealed “up to 8-year neocloud contracts being signed for Ampere,” some at almost 90% of the original cost. Given that Nvidia’s Ampere is the predecessor to Hopper, and Hopper in turn, precedes Blackwell, this highlights the intense GPU supply constraint with companies willing to purchase older generation chips to meet computational demands.

According to Loop analysts, while Blackwell is more power-efficient, Ampere data centers are built in lower-power areas using air cooling. Retrofitting for Blackwell’s liquid-cooling needs could lead to inefficiencies.

CoreWeave reported strong growth recently with a 134% increase in revenue and a 271% increase in revenue backlog, citing a “highly supply-constrained” environment. Furthermore, during the earnings call, Intrator supported findings that even older-generation chips have value.

“In Q3, we saw our first 10,000-plus H100 contract approaching expiration. Two quarters in advance, the customer proactively re-contracted for the infrastructure at a price within 5% of the original agreement. CoreWeave CFO Nitin Agrawal subsequently added, “Demand remains robust for not just the Blackwell platform, but across our GPU portfolio. In the third quarter, we signed a number of deals for older generations of GPUs, adding new customers and re-contracting existing capacity.”

Five Key Questions for Nvidia

Given the aforementioned points – the hyperscaler capex commentary, Huang’s appeal to Taiwan Semi, neocloud agreements highlighting the lasting economic value of Nvidia’s older products, and competitor AMD projecting tremendous near-future growth – here are five important questions as one anticipates Nvidia’s quarterly results:

1. **Can the market sustain 40% capex growth through the end of the decade?** This hinges on end-market demand, use-case developments, and whether Nvidia’s customers, such as cloud providers, can monetize that demand. The last thing anyone wants is for companies to overspend without a path towards monetization.
2. **What does Huang mean by stating China will win the AI race?** Is this related to a competitive mindset driving innovation at Nvidia? Or is it an attempt to raise urgency around U.S. AI strategy?
3. **What are the plans for free cash flow?** Nvidia is generating significant cash, and analysts project growth in the next few years. The company has net cash, leading to questions about share buybacks, acquisitions, and investments.
4. **Clarity on the $500 billion in orders for Blackwell and Rubin?** Details are needed regarding the revenue timing and the financial standing of the customers placing orders.
5. **What about margins?** Given that new products are ramping, margin dynamics will be scrutinized.

AI Spending Concerns

Concerns persist about funding the needs of Nvidia’s customers. While many big players previously funded their data center ambitions with free cash flow, many are now turning to the debt markets. There’s worry that companies are borrowing without discipline and investor value in operating efficiency should be at the forefront. Furthermore, questions around the sheer dollar size of commitments between the players raises questions especially with non-public spenders in the mix.

The escalating interconnectedness of these companies increases systemic risk. If one major player encounters difficulties making commitments, there are downstream domino effect implications throughout the whole AI cohort.

Bottom Line

These concerns caution those considering new investments in the data center sector. At the same time, demand signals that will continue to boost the spending increases will be coming largely to Nvidia. While there may be obstacles, the long term investors should maintain position in Nvidia since it is at the heart of the entire AI investment cycle.