Nvidia Says 'Demand Has Gone Parabolic' — Here's Why, Plus 5 AI Stocks To Watch

Nvidia Corp. (NASDAQ:NVDA) CEO Jensen Huang used the company's Wednesday evening earnings call to deliver a clear message about the state of the AI boom: demand is not just strong, it has "gone parabolic."

"This was an extraordinary quarter. Demand has gone parabolic," Huang said. "The reason is simple. Agentic AI has arrived. AI can now do productive and valuable work. Tokens are now profitable. So model makers [are] in a race to produce more."

• NVDA stock is moving. See the chart and price action here. 

Compute = Revenue

The comments cut straight to the center of the current AI trade. 

Huang argued that the next phase of artificial intelligence is no longer just about experimentation, model launches or chatbot adoption. It is about AI systems doing economically useful work at scale.

In that world, compute is not merely infrastructure. It becomes a direct driver of revenue.

"In the AI era, compute capacity is revenue and profits," Huang said.

That framing helps explain why Nvidia remains at the heart of Wall Street's AI narrative. 

Huang said Nvidia is "the platform of this era," pointing to the breadth of demand across frontier model developers, hyperscale cloud providers, sovereign AI initiatives, enterprise infrastructure and physical AI applications.

"Of all the platforms in the world, Nvidia Compute supports the richest diversity of demand," he said.

Huang's 5 Reasons

Huang laid out five reasons Nvidia believes its position remains central. 

First, Huang said Nvidia is the only platform that runs every frontier AI model, citing partners including Anthropic, OpenAI, xAI, Meta Platforms (NASDAQ:META), Gemini and others. He added that Nvidia's share of frontier AI is growing.

Second, Huang said Nvidia is present in every hyperscale cloud, supporting core data processing, machine learning workloads, internal AI services and public cloud demand from Nvidia users.

Third, he pointed to Nvidia's full-stack AI factory approach, saying the company's systems, software and ecosystem allow it to address new AI data center segments, AI native clouds, sovereign AI clouds and on-premise enterprise and industrial infrastructure.

Fourth, Huang emphasized the reach of CUDA beyond the data center and into edge markets such as robotics, autonomous vehicles, embedded medical instruments and AI-RAN telco base stations. He called physical AI "the next wave," describing a future with billions of autonomous and robotic systems operating in the physical world.

Finally, Huang highlighted Vera, Nvidia's CPU purpose-built for agentic AI, calling it a major new growth driver. He said Vera opens a $200 billion total addressable market for Nvidia and that every major hyperscaler and system maker is partnering with the company to deploy it.

"The world is rebuilding computing for agentic AI and robotic physical AI," Huang said. "Nvidia sits at the center of these transitions."

Stocks To Watch

Here are 5 AI names that could ride the same "compute capacity is revenue and profits" demand curve Nvidia described.

• Advanced Micro Devices, Inc. (NASDAQ:AMD): AMD could benefit as hyperscalers and enterprises look for additional AI accelerator supply beyond Nvidia. The company is positioning its Helios AI rack system as a direct competitor to Nvidia's Vera Rubin infrastructure for large-scale AI workloads. 
• Broadcom Inc. (NASDAQ:AVGO): Broadcom is tied to the AI buildout through custom AI accelerators and high-speed networking chips. Its AI networking business has been driven by demand from hyperscalers building large AI clusters. 
• Marvell Technology, Inc. (NASDAQ:MRVL): Marvell could see demand from the optical and data-center interconnect layer of the AI boom. 
• Micron Technology Inc. (NASDAQ:MU): If agentic AI means more inference, more tokens and more compute, it also means more demand for high-bandwidth memory (HBM) and AI server memory, where Micron is a key supplier.
• Super Micro Computer, Inc. (NASDAQ:SMCI): Super Micro could benefit from demand for AI servers and liquid-cooled rack-scale systems. The company sits between Nvidia's GPUs and customers building AI infrastructure, with recent guidance reflecting strong AI server demand. 

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