Nvidia in the AI stack

The business and what the filings show

Nvidia sells the accelerators most AI data centers are built around, along with the networking that ties them together, complete rack-scale systems and the CUDA software platform developers have built on for well over a decade. Over its latest four quarters it reported $303B of revenue, +83% on the year before, at a 75% gross margin and a 65% operating margin: margins usually associated with software, earned on hardware.

Most of that is data-center revenue: $278B over the same four quarters, +90%. Nvidia now reports it split between hyperscale customers and “AI clouds, industrial and enterprise”, a group that includes the GPU clouds Nvidia invests in and buys capacity back from. Two direct customers accounted for 22% and 14% of its fiscal 2026 revenue.

The investment question is not whether Nvidia is the toll booth today but how long it stays one. Every large buyer designs its own accelerators, AMD is buying share with customer warrants, and Nvidia itself is increasingly financing demand: equity investments across its ecosystem, capacity buy-back agreements with AI clouds and lease guarantees for OpenAI. Gross margin is the number that would show the scarcity easing first.

How AI shows up in the numbers

Almost all of Nvidia’s growth is AI. Data-center revenue, which is accelerators, networking and systems sold for AI and accelerated computing, now dwarfs its gaming and professional visualization businesses, so its consolidated numbers are effectively a reading of AI infrastructure demand. That also means its results move with a small number of buyers’ capital budgets: when the clouds raise capex, Nvidia’s revenue follows within a quarter or two, and when they pause, it would follow just as quickly.

For scale, Nvidia’s revenue over the latest four quarters equals 53% of the $566B the five largest buyers spent on capital projects over their latest four quarters. Their capex rose +81% on the year before, while Nvidia’s revenue grew +83%: faster than the spending, a sign it is capturing a growing share of each capex dollar or selling to buyers beyond the five.

How it talks about AI

In its latest earnings release, furnished to the SEC on August 26, 2026, Nvidia mentioned AI 34 times in 1,358 words of narrative text, about 25.0 mentions per 1,000 words. Of its 23 sentences about AI, 1 included a number: a revenue figure, a growth rate, a customer count or another measurable result. Across the 8 releases we read, back to November 20, 2024, AI mentions per 1,000 words went from 25.6 to 25.0.

Specific claims are easier to check against the numbers than general enthusiasm, which is why the share of AI sentences that carry a figure is worth watching alongside how often AI is mentioned. The sentences below are quoted from the release as published, after removing safe-harbor text and company boilerplate.

• “Announced strategic partnerships to establish independent compute financing platforms with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to mobilize over $500 billion of third-party capital for the buildout of AI infrastructure over time, subject to definitive agreements.”
• “This time last year, one lab alone was driving the buildout; today, we have a golden age of new AI labs and startups, multiple frontier labs scaling in parallel, a thriving open-model ecosystem and physical AI coming online — with strong momentum across the U.S. and around the world.”

Source: earnings release (Form 8-K, Exhibit 99.1), August 26, 2026.

The trend in the numbers

Since the start of 2023, Nvidia’s largest quarter by revenue was Q2 2026 at $96.2B, and its highest gross margin was 78% in Q1 2024. The latest quarter set the revenue record for the period.

Quarter by quarter, Nvidia’s revenue grew +62% in Q3 2025, +73% in Q4 2025, +85% in Q1 2026, +106% in Q2 2026 on the same quarter a year earlier. Growth has been accelerating.

Gross margin in the latest quarter was 75%, against 72% a year earlier, so it is keeping more of each dollar as it grows. Operating margin moved from 61% to 66% over the same span. Over the latest four quarters it turned 44% of its revenue into operating cash flow and spent 2% of revenue on capital projects, against 3% a year earlier.

Segments that matter for AI

The parts of Nvidia’s reported results most tied to the AI build-out, from the segment and product disclosures in its 10-K and 10-Q filings.

Where it sits in the stack

Nvidia sits in the chips layer of the AI stack. It is paid by the AI clouds and servers and networking layers; its own spending flows to foundry & tools, memory.

Among the 7 companies in this layer on our map, it ranks first by revenue and first of 6 by revenue growth. Its gross margin of 75% compares with 66% for the layer as a whole, a sign that it keeps more of each dollar than its neighbors. The full layer analysis is on the chips page.

Latest four quarters for 10-Q filers; latest fiscal year for 20-F filers. Companies under $100 million of revenue are left out.

Against the 6 US-listed companies in its layer, Nvidia grew +83% over the latest year versus +52% for the layer combined, and converted 42% of revenue into free cash flow versus 35% for the layer. It is taking share of the layer’s revenue.

What has to go right, and what could go wrong

What has to go right. Demand for accelerators has to keep outrunning supply long enough for Nvidia’s software and systems advantage to keep customers buying complete platforms rather than parts, and the financing it extends to customers has to be repaid by end demand rather than by more financing.

What could go wrong. Custom chips could take the most common workloads, buyers could slow their capex, or supply could catch up so customers can negotiate. Any of those would show first in gross margin; the guarantees and capacity buy-backs are where losses would surface if AI capacity ran ahead of what users pay for.

These describe the conditions the business depends on, as the filings show them. They are not a view on the stock.

Through the lens of Investing in AI

Rob May’s book offers six mental models for telling AI moats from traps. The one most useful for Nvidia’s layer is “AI changes markets and corporate strategy”: When creation gets cheap, choke points move. Like the internet shifting newspaper profits to discovery, AI pushes moats toward coordination and control points. The winners sit at the new choke point, not the best AI story.

The question it asks of any company is: What becomes scarce in this value chain as AI makes the work abundant? Applied to Nvidia, the filings on this page are the place to start: the margin trend shows whether it holds scarce value or passes it through, the customer and financing disclosures show who it depends on, and the commitments show what it has promised before the revenue arrives.

Customers and concentration

US companies must disclose any customer that accounts for 10% or more of revenue, and foreign filers usually describe their largest customers. Concentration matters because a company’s growth is only as durable as the handful of buyers behind it, and in the AI stack those buyers are often the same few companies.

• “For fiscal year 2026, sales to one direct customer represented 22% of total revenue and sales to another direct customer represented 14% of total revenue, all of which were primarily attributable to the Compute & Networking segment.” 10-K, February 25, 2026
• “For the second quarter of fiscal year 2027, one direct customer represented 16% of total revenue, which was primarily attributable to the Compute & Networking segment.” 10-Q, August 26, 2026

Financing links

Investments, guarantees, purchase commitments, warrants and power contracts between Nvidia and other companies, each quoted from the filing that discloses it. Numbers match the money-loop map.

• 11Nvidia → OpenAICredit or guarantee

  Lease guarantees for OpenAI, capped at $105B

  “The campus will exclusively host our compute under 20-year leases to OpenAI, subject to limited exceptions, with our obligation capped at $105 billion in the aggregate, subject to certain conditions including SB Energy, the lessor, satisfying applicable ready-for-service conditions.”

  Nvidia 10-Q for the period ended July 26, 2026, filed August 26, 2026

• 12Nvidia → Nvidia’s private holdingsEquity investment

  $99B invested, $25B more committed

  “These include equity investments of $99 billion and equity investment commitments of $25 billion as of July 26, 2026.”

  Nvidia 10-Q for the period ended July 26, 2026, filed August 26, 2026

• 13Nvidia → AI cloud partnersPurchase commitment

  $36B of cloud capacity it has agreed to buy back

  “Our commitments, which are typically six years in duration, totaled $36 billion as of July 26, 2026, and decrease as capacity is used by third-party customers or by us for our research and development efforts.”

  Nvidia 10-Q for the period ended July 26, 2026, filed August 26, 2026

• 14Nvidia → Nvidia’s suppliersPurchase commitment

  $279B of supply and capacity commitments

  “We have significantly increased our supply and capacity commitments from $119 billion last quarter to $279 billion as of July 26, 2026 to meet future demand.”

  Nvidia 10-Q for the period ended July 26, 2026, filed August 26, 2026

• 15Nvidia → CoreWeaveEquity investment

  $2.0B share purchase, January 2026

  “In January 2026, we entered into a securities purchase agreement with NVIDIA Corporation for a private placement of approximately 23 million shares of our Class A common stock at a purchase price of $87.20 per share, for aggregate gross proceeds of $2.0 billion.”

  CoreWeave 10-Q for the period ended June 30, 2026, filed August 12, 2026

Commitments and backlog

• Backlog. Nvidia reports $3.2B of remaining performance obligations, less than a tenth of its revenue over the latest four quarters: contracted revenue not yet earned.
• Purchase commitments. $22.7B of unconditional purchase obligations as of January 25, 2026 (10-K): what it has contracted to buy from its own suppliers.

What to watch

Nvidia’s next quarterly report will cover the quarter ending around October 25, 2026. Large companies must file a 10-Q within 40 days of a quarter’s end and a 10-K within 60 days of the fiscal year’s end, so the new figures should arrive by about December 24, 2026 at the latest. This page, the layer pages and the next quarterly report all update from that filing.

• Gross margin each quarter, and any guidance that it will fall: margin, not revenue, is where easing scarcity or rising competition would show first.
• The split of data-center revenue between hyperscalers and AI clouds, since the second group includes customers Nvidia invests in and buys capacity back from.
• Equity investments, capacity buy-backs and guarantees in the 10-Q: if they grow faster than revenue, more of Nvidia’s demand is being financed by Nvidia.
• Its place in the next quarterly AI Stack Report, which updates every company on the map from the new filings.

Figures from Nvidia’s SEC filings, latest period ended July 26, 2026. Other companies: all company pages.