Nvidia bets on AI inference as chip revenue opportunity hits $1 trillion

Nvidia said the revenue opportunity for its artificial intelligence chips may reach at least $1 trillion through 2027, as the company outlined a strategy to compete more aggressively in the fast-growing market for running AI systems in real time.

Chief Executive Officer Jensen Huang unveiled a new central processor and an AI system built on technology from Groq — a chip startup from which Nvidia licensed technology for $17 billion in December — at its annual GTC developer conference in San Jose.

The moves are part of Huang’s bid to firm up the company’s position in so-called inference computing — the process of answering queries — where its graphics processors face greater competition from central processing units and custom processors built by the likes of Google. Nvidia chips have dominated the process of AI model training, which has been the focus of recent years.

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“The inference inflection has arrived,” Huang said. “And demand just keeps on going up,” he added.

Dressed in his signature black leather jacket, Huang was speaking at a hockey arena with a capacity of more than 18,000 at the four-day conference that has become one of the biggest showcases of AI technology. “I just want to remind you, this is a tech conference,” he told the audience.

But after a dazzling rally that made Nvidia the first company to hit a $5 trillion valuation last October, doubts have risen about its growth. Investors have also questioned if its plan of plowing back profits into the AI ecosystem will pay off. Huang’s comments allayed some fears.

The $1 trillion forecast is up from the $500 billion revenue opportunity through 2026 that Nvidia cited for its Blackwell and Rubin AI chips on its last earnings call in February.

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Shares of Nvidia briefly jumped on the new forecast but pared those gains to close up 1.2%.

“Huang mapping out a $1 trillion opportunity through 2027 underscores the durable demand for Nvidia’s AI infrastructure despite investor concerns,” Emarketer analyst Jacob Bourne said.

“It signals Nvidia is sustaining its leadership in the AI chip market while the overall AI industry expands beyond early experimentation into large-scale deployment.”