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Wall Street forecasts Nvidia stock price for the next 12 months

Wall Street forecasts Nvidia stock price for the next 12 months
Jordan Major

Nvidia (NASDAQ: NVDA) is currently trading at $133.59, but Wall Street analysts maintain a highly bullish outlook on their Nvidia stock forecast over the next 12 months, citing strong AI momentum, robust enterprise demand, and its leadership in accelerated computing.

According to aggregated data from 40 Wall Street analysts, the average NVDA stock forecast sits at $164.51, representing a 22.42% upside from its current price. The highest price target is $200, while the most conservative forecast puts the stock at $100 over the next year.

Overall, Nvidia shares carry a “Strong Buy” consensus rating, with 34 analysts rating NVDA a Buy, 5 recommending Hold, and just 1 issuing a Sell.

NVDA stock price target. Source: Finbold

NVDA stock continues to receive upbeat analyst price targets

Recent analyst updates from the past two days reinforce this bullish sentiment. On May 20, Atif Malik of Citi reiterated a $150 price target, representing an 11.62% upside, while Aaron Rakers of Wells Fargo maintained a more aggressive $185 target, projecting a 37.67% upside.

On May 19, four other top analysts weighed in. Vivek Arya of Bank of America and Joseph Moore of Morgan Stanley both reaffirmed their $160 price targets, implying a 19.07% upside. Srini Pajjuri of Raymond James matched Citi’s forecast with a $150 target. An unnamed analyst at William Blair also reiterated a Buy rating, though no price target was disclosed.

Despite a 0.88% dip in the previous session and a small pre-market slide, analysts remain confident in Nvidia’s long-term fundamentals. The company continues to benefit from powerful AI tailwinds, leadership in GPU computing, and a strong pipeline across data centers, enterprise software, and edge AI.

As NVDA stock consolidates near current levels, analysts widely view the recent pullback as a potential buying opportunity, especially given the company’s critical role in powering next-generation AI infrastructure.

Featured image via Shutterstock

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