Nvidia says compute is now revenue! Its guidance asks for another $12 billion in one quarter

Nvidia reported revenue of $96.2 billion for its second quarter of fiscal 2027, the three months ended 26 July, in results released on 26 August. Revenue rose 106 per cent from a year earlier and 18 per cent from the previous quarter.

Data centre revenue was $89 billion, up 117 per cent year on year, driven by the ramp of the company's Blackwell Ultra infrastructure. Gross margin was 75 per cent on both a GAAP and non-GAAP basis. Diluted earnings per share were $2.46 GAAP and $2.22 non-GAAP.

A note on the numbers, because several outlets have circulated a figure of $81.6 billion for what they described as a record quarter. That figure does not correspond to this release. Nvidia's own investor materials give $96.2 billion for the second quarter of fiscal 2027.

The number that matters most

The reported quarter is history. The forward guidance is the claim.

Nvidia guided to $108 billion for the third quarter of fiscal 2027, plus or minus 2 per cent, with gross margin of 74 per cent plus or minus 50 basis points.

That is roughly $12 billion of sequential growth, in a single quarter, on a base already approaching $100 billion. Expressed as a rate it is a little over 12 per cent quarter on quarter. Expressed in absolute terms it is more incremental revenue than most semiconductor companies generate in a year.

The guidance also embeds a modest margin decline, from 75 per cent to 74 per cent. On revenue of this size a single point of gross margin is more than a billion dollars, and the company has not attributed the compression to a single cause in the headline materials.

What the chief executive said

"AI has reached its inflection point. It's doing useful work. Its tokens are productive and profitable. Now, compute is revenue," said founder and chief executive Jensen Huang.

The formulation is worth parsing, because it is doing specific work. Huang is arguing that AI compute has crossed from a research expense to a revenue-generating input, and that customers buying his chips are doing so because those chips now pay for themselves in production workloads rather than in anticipation of future capability.

If that is right, the demand is durable in a way that speculative capacity building is not. If it is not right, the same sentence will be quoted back at him.

Where the money is coming from

The composition of the data centre segment tells more than the total.

Hyperscale revenue was $49 billion, growing 13 per cent sequentially. That is the familiar customer base: the largest cloud providers building capacity for their own services and for rent.

The faster-growing portion came from elsewhere. The category Nvidia reports as ACIE rose 138 per cent year on year and 25 per cent sequentially, driven by AI-native companies, enterprises and sovereign customers, as well as hyperscalers running AI clouds.

Sovereign demand is the strategically interesting component. Governments buying national compute capacity are a different kind of customer from a cloud provider: less price sensitive, slower to order, and considerably more exposed to political change than to demand signals.

The concentration problem

The strongest counter-argument to these results is not that the demand is fake. It is that the demand is narrow.

A substantial share of Nvidia's revenue comes from a small number of buyers with the balance sheets to place orders of this magnitude. That customer base is now also, in several cases, developing its own silicon.

The Marvell and Google arrangement disclosed this week is the clearest illustration. Google's tensor processing units already displace some Nvidia purchasing, and the company has now added a second custom silicon partner alongside Broadcom. Amazon, Microsoft and Meta all run internal accelerator programmes.

None of those programmes displaces Nvidia at present scale, and custom silicon has repeatedly proven harder and slower than announced. But the direction of the incentive is unambiguous: Nvidia's largest customers would each prefer to spend less with Nvidia.

There is a second concentration risk on the supply side. Advanced packaging and high-bandwidth memory remain constrained, and both run through a small number of suppliers in Taiwan and South Korea. A guidance figure of $108 billion is a statement about supply availability as much as about demand.

The case for the bears

The bear case does not require AI to disappoint. It requires only that capital expenditure growth decelerate.

Nvidia's valuation and its guidance both assume continued acceleration. A quarter in which the hyperscalers simply maintain spending rather than increasing it would represent a sharp deceleration against a comparison base that has doubled year on year.

Depreciation is the mechanism most often cited. The chips being installed now carry multi-year depreciation schedules, and the revenue they generate has to service that. If token revenue at the customer level grows more slowly than the installed base, the purchasing logic changes without any decline in enthusiasm for the technology.

Huang's answer is contained in the quote. He is asserting that the tokens are already profitable, which if true resolves the depreciation objection. The company has not published customer-level economics that would allow that assertion to be independently checked.

What to watch

Three things will matter more than the headline in the next quarter.

Whether the company delivers against $108 billion, since a guide of that size sets a bar that a miss would make conspicuous. Whether gross margin stabilises at 74 per cent or continues drifting. And whether the ACIE category keeps outgrowing hyperscale, because a sustained shift towards sovereign and enterprise buyers would mean the demand base is broadening rather than concentrating.

On the reported quarter, the results were unambiguous. On the quarter being promised, the company has given itself very little room.