This Analyst Sees Nvidia at $8.5 Trillion Next Year. Is It Even Possible?

"On November 20, Lipacis lifted his price target on NVDA stock from $261 to $352. He used the company's inventory buildup "to support large orders" as his rationale for the price target increase. This may look counterintuitive at first, as a bigger inventory usually means products are not being sold . However, the rising inventory is viewed bullishly because Nvidia itself has said they're building up to meet unprecedented AI compute demand, not excess supply."

"The highest such recent price target projects NVDA stock at $352 next year. This implies a massive 101% leap from here and comes from Evercore ISI analyst Mark Lipacis. This analyst has an excellent history of making winning calls, with 69% of his ratings being successful , with an average return per rating of 28.3% over the past year. This is exceptionally good, and puts him at #32 out of over 10,000 tracked Wall Street analysts."

"Lipacis believes revenue growth could accelerate to 79% by mid-2026. If this happens, Wall Street is likely to slap a higher premium on NVDA stock. The current forward price-earnings ratio of 23 times makes NVDA stock cheaper than at 33 times and at 63 times. Can Nvidia keep expanding its lead? Nvidia's competitors have failed to make ground. Many other AI chipmakers have cost-effective products, but they pale in comparison to what Nvidia has to offer."

Nvidia's stock has rallied for over three years while revenue continues rapid growth. Analysts' price targets were initially varied but have recently moved toward higher, more ambitious levels. Evercore raised its target to $352, citing an inventory buildup intended "to support large orders" and a backlog estimated at $500 billion for 2025–2026. The Evercore analyst has a strong track record, with 69% successful ratings and a 28.3% average return over the past year. Forecasts include potential revenue acceleration to 79% by mid-2026 and a forward P/E near 23, while competitors struggle to match Nvidia's AI chip performance.

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