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Finally they arrived. The long-awaited Nvidia data have been published and the market has welcomed them (the stock is rising in the pot market). Well: the star of Artificial Intelligence, in the first quarter of 2024-’25, reported revenues of 26.04 billion dollars (24 billion +/- 2% the group’s estimate for the quarter just ended). This is a value that is above consensus forecasts and up by 262% compared to the same period of the previous year (+18% on a sequential basis). The GAAP Gross Marging was 78.4% (76.3% forecast on GAAP data and 77% on non-GAAP data). Finally, net profit grew to 14.8 billion dollars (+628% compared to the figure 12 months earlier). This number is also higher than what analysts expected.
Experts who, however, were all waiting to see what the prospects for the second quarter were. Nvidia, again, did not disappoint. The group, for the second quarter 2024-’25, expects revenues of 28.0 billion (+/- 2%). Better value than expected.
The leap into fundamentals
In short, with respect to fundamentals, Nvidia’s march continues. This, although the company has been profitable for some time, underwent a real leap forward between 2022-’23 and 2023-’24. For the entire last fiscal year, turnover was 60.922 billion dollars, an increase of 126% compared to 12 months earlier. Net profit, for its part, went from 4.368 billion (fiscal year 2022-23) to 29.760 billion dollars. Then, in the last quarter – again 2023-’24 – revenues increased by 265% compared to the same period of 2022-’23. The Operating margin, however, jumped by 983%.
A story that comes from afar
It goes without saying that artificial intelligence – especially generative – has been the fuel that has helped push the company’s numbers. A group which, it should be remembered, owes its fortune to having proposed, way back in 1999, the so-called Graphics processing unit (GPU). That is to say: a processor composed of many cores (operational cores of the chip) smaller and more specialized than those, for example, of a CPU (the traditional brain of the computer).
The GPU initially, boasting very high performance in the wake of the same parallel processing, has become a leading technology in computer graphics: from the so-called rendering to the world of video games. Then, also thanks to Cuda programming – a programming language that exploits the very high parallelization of video cards – the GPU gradually penetrated other sectors. It is a technology that can support greater workloads with higher speed and high energy savings. A mix of conditions which, in the end, has allowed similar processors to position themselves at the “centre” (in addition to sectors such as those of high-performance computers) of the world of Artificial Intelligence (Ai).
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