This all-important figure provides the most complete picture of Nvidia’s health and that of the artificial intelligence (AI) revolution.
On Wall Street, important data releases are a common occurrence. Federal Reserve Open Market Committee meetings, the monthly inflation and jobs reports, and even the quarterly filing of Form 13Fs with the Securities and Exchange Commission, provide invaluable data that investors can use to formulate an effective investment strategy.
Tomorrow (Aug. 28), the company that’s played the biggest role in sending the Dow Jones Industrial Average, S&P 500, and Nasdaq Composite to record highs — Nvidia (NVDA -2.25%) — will be lifting its proverbial hood and allowing Wall Street to examine its operating performance over the prior three months. This is, arguably, just as important of a data release as any that I mentioned above.
Although investors are liable to be laser-focused on Nvidia’s headline figures (revenue and net income), there’s a considerably more important metric to look for that’ll provide broader context on the health of the artificial intelligence (AI) revolution and Nvidia’s future.
Image source: Getty Images.
How did Nvidia become Wall Street’s most-awaited and important earnings report?
Before digging into this critical metric, it’s imperative to provide background on how we got to this point. In other words, some explanation is needed for Nvidia’s meteoric rise from a $360 billion market cap at the end of 2022 to a nearly $3.2 trillion valuation, as of the closing bell on Aug. 23, 2024.
As you may have rightly guessed, AI is behind this historic move. In short order, Nvidia’s H100 graphics processing unit (GPU) became the preferred choice in high-compute data centers. These chips are effectively the brains powering split-second decision-making, overseeing generative AI solutions, and helping to train large language models (LLMs).
Nvidia has also received an undeniable boost from its CUDA software platform. CUDA is the toolkit developers use to build LLMs and get the most out of their GPUs. CUDA is working seamlessly with the H100 to keep enterprise clients loyal to Nvidia’s product and service ecosystem.
The other key piece of the puzzle for Nvidia is enterprise demand heavily outstripping the supply of its AI-GPUs. When demand for a good or service overwhelms supply, the price of that good or service usually increases until demand tapers. The cost for Nvidia’s H100 typically comes in between $30,000 and $40,000, which is more than double the cost of the MI300X, which is a rival chip developed by Advanced Micro Devices.
It’s this AI-GPU scarcity that you’ll want to keep in mind when digging into Nvidia’s fiscal second-quarter operating results, which are slated for release after the closing bell on Aug. 28.
Image source: Getty Images.
Forget revenue and net income — this metric trumps them both
Over the five previous quarters (i.e., the entirety of Nvidia’s fiscal 2024 and the first quarter of fiscal 2025), Nvidia has completely blown Wall Street’s loftiest sales and profit expectations out of the water. With Wall Street analysts having a history of providing beatable consensus forecasts, it wouldn’t be remotely shocking if Nvidia’s revenue and net income sailed past expectations, once again.
But these two headline figures only tell part of the story. If you want a more complete picture of Nvidia’s health and that of the AI revolution, focus on the company’s gross margin. With Nvidia, I tend to hone in on its adjusted gross margin, which excludes factors like stock-based compensation and acquisition-based expenses.
Although Nvidia has been selling more of its H100 GPUs, thanks in large part to a meaningful increase in chip-on-wafer-on-substrate capacity from world-leading chip-fabricator Taiwan Semiconductor Manufacturing, the bulk of Nvidia’s growth has come on the heels of its otherworldly GPU pricing power. Being able to charge 50% to 75% more than competing AI-GPUs propelled Nvidia’s adjusted gross margin from 64.63% to 78.35% in five quarters.
NVDA Gross Profit Margin (Quarterly) data by YCharts.
Following Nvidia’s fiscal first-quarter results (ended April 28), management called for an adjusted gross margin of 75.5% (+/- 50 basis points) for the fiscal second quarter. This would imply a decline of between 235 and 335 basis points from the sequential quarter.
While this might just represent management being conservative as cost of goods climb in lockstep with new orders, a meaningful decline in adjusted gross margin might also hint at a shift in the AI landscape.
Once again, everything has revolved around the idea that AI-driven GPUs are scarce and in high demand. If Nvidia’s adjusted gross margin comes in toward the low-end of its previous forecast, or its outlook calls for a further retracement in gross margin, it would pretty clearly signal that competitive pressures are beginning to be felt.
In particular, reports emerged this month that Nvidia’s next-generation Blackwell platform would be delayed by at least three months due to design flaws and various supply chain constraints.
Despite a healthy order backlog for its Blackwell chip, there’s the potential we might see businesses opt for cheaper AI-GPU alternatives that they can get their hands on quicker. First-mover advantages in the AI space are a thing, and some businesses aren’t going to want to wait months on end for orders to be fulfilled. This opens the door for Advanced Micro Devices, Samsung, and other hardware developers to steal valuable space in AI-accelerated data centers.
Adjusted gross margin can also tell us if Nvidia is contending with internal competitive pressures. The company’s four-largest customers, which are all members of the “Magnificent Seven,” comprise around 40% of Nvidia’s net sales. However, all four of these industry leaders are internally developing AI-GPUs for use in their data centers. A lower adjusted gross margin forecast may be reflective of Nvidia losing valuable data center “real estate” to these in-house chips.
Instead of honing in on Nvidia’s sales and net income tomorrow, dig deeper and seek out the adjusted gross margin figure that’ll give you a more complete picture of what the future holds for Nvidia and artificial intelligence.