Nvidia’s third-quarter results along with optimistic comments from CEO Jensen Huang impressed analysts who cover Nvidia but did little to ease investors' fears of an AI bubble.
Nvidia beat expectations for last quarter with a record $57 billion in revenue, a 62% year-over-year increase that beat financial analysts’ expectations. The GPU maker raised its guidance for this quarter to $65 billion, above the $62.1 billion analyst predicted.
“Blackwell sales are off the charts, and cloud GPUs are sold out,” Huang said of Wednesday’s earnings report. “Compute demand keeps accelerating and compounding across training and inference — each growing exponentially. We’ve entered the virtuous cycle of AI. The AI ecosystem is scaling fast — with more new foundation model makers, more AI startups, across more industries, and in more countries. AI is going everywhere, doing everything, all at once.”
There has been concerns about an AI bubble after the large tech companies and hyperscalers pledged to increase spending by billions of dollars. The question is whether customer demand warrants that level of infrastructure spend.
In a note to clients, Jefferies analyst Blayne Curtis said Nvidia “answered the bell,” and relieved those concerns for now.
“We don't expect every AI bear to be satisfied, but these results and added context from management around demand outlook should offer some near-term reprieve,” Curtis told clients.
That near-term reprieve was nearer than Curtis originally thought. Nvidia’s stock rose immediately after earnings, as did the shares of other big tech companies. But those gains disappeared quickly as Nvidia and tech shares dropped.
Nvidia’s GPUs provide much of the computing required to power AI applications. Huang pointed out AI now increasingly includes agentic AI as well as generative AI that has been in use for several years.
“We're excellent at every phase of AI,” Huang said on Nvidia’s earnings call. “Everybody's always known that we're incredibly good at pre-training. We're obviously very good at post-training, and we're incredibly good, as it turns out at inference because inference is really, really hard. People think that inference is one shot and therefore, it's easy, anybody could approach the market that way. But it turns out to be the hardest of all because thinking as it turns out is quite hard. We're great at every phase of AI.
“And so whether you install NVIDIA GPUs for data processing or you did it for generative AI for your recommender system or you're building it for agentic chatbots and the type of AIs that most people see when they think about AI, all of those applications are accelerated by NVIDIA.”
Is Nvidia the major AI driver, or is AI the major Nvidia driver? At this point, it probably doesn’t matter. Financial analysts equate Nvidia’s success with the success of AI.
“If Nvidia keeps beating and raising, the party essentially keeps going,” Tech Cache investing group leader Joe Albano wrote via email to Seeking Alpha. “And Nvidia didn't disappoint this quarter either, with another beat and another serious guide above consensus - all without China.”