Two semiconductor exchange-traded funds (ETF) have posted their best quarterly performances since 2020 as investors bet chipmakers are on the rebound as interest in artificial intelligence (AI) gains momentum.

The VanEck Semiconductor ETF (SMH  ) has risen over 30% year-to-date, while the iShares Semiconductor ETF (SOXX  ) has climbed 29% this quarter, marking their best respective quarterly performances since 2Q and 4Q of 2020.

That broader market outperformance -- as the S&P 500 (SPY  ) and Nasdaq Composite (QQQ  ) have only risen roughly 7.5% and 21%, respectively, in the first quarter -- was driven by outstandingly strong performances from chipmakers including Nvidia (NVDA  ), Advanced Micro Devices (AMD  ), Intel (INTC  ) and Micron Technology (MU  ).

Standing out from its peers, Nvidia has risen over 94% year-to-date, soaring over 22% in the month of March alone, as the stock posts its best quarterly performance since the fourth quarter of 2001.

Much of Nvidia's gains come from investor optimism that the chipmaker is going to become an industry leader for the hardware that powers AI technology.

This week, Bernstein analyst Stacy Rasgon reiterated the firm's Outperform rating Nvidia and raised the stock's price target to $300 from $265 as the firm becomes increasingly bullish towards the chipmaker's semiconductors use in the generative AI industry.

That rating comes as Nvidia CEO Jensen Huang recently announced an array of partnerships and AI services that are all powered by the company's microchips.

"Generative AI's incredible potential is inspiring virtually every industry to reimagine its business strategies and the technology required to achieve them," Huang said during the Nvidia GTC Developer Conference earlier in March, quoted by Barron's. "Nvidia and our partners are moving fast to provide the world's most powerful AI computing platfrom to those building applications that will fundamentally transform how we live, work and play."

To that point, generative AI products, like Open AI's popular ChatGPT and others recently introduced by Microsoft (MSFT  ) and Google (GOOGL  ), rely on powerful semiconductors in order to "train" machines to produce human-like responses to user provided text or image prompts.

Rasgon believes that Nvidia's chips will benefit from increased demand as more companies work with their own AI language models to compete in the exploding new tech frontier, and as these models are integrated into more industries.

"We are early on the adopter curve," Rasgon wrote in a note on Tuesday. "Over time we believe the [total addressable market] could potentially reach into the billions as model complexity grows and adoption widens."