Nvidia’s (NVDA) bull case just got another massive vote of confidence from Wall Street.
Matt Bryson, a 5-star Wedbush analyst (per TipRanks), just bumped his price target on Nvidia stock to $300 from $230, maintaining an outperform rating, which shows even more confidence in the longevity of the AI buildout.
The upgrade follows a slew of analyst notes after Nvidia’s bombastic earnings report, which once again highlighted the massive demand for AI computing.
In raising his price target, Bryson argues that the structural drivers powering Nvidia’s growth in the colossal hyperscaler capex, AI model development, and enterprise adoption remain firmly intact.
For perspective, as of market closing on March 5, 2026, Nvidia’s stock was trading at $183.34, according to Yahoo Finance, with a market cap north of $4.45 trillion.
Dan Ives is the name that usually pops up when you think about Wedbush’s tech shop, and for good reason.
He’s the Global Head of Technology Research at the firm and has been one of the defining faces in the AI era.
However, when it comes to semiconductors and Nvidia, Matt Bryson isn’t one to play second fiddle. On Nvidia alone, he has delivered an astounding 88% success rate across 47 ratings.
I covered Nvidia in a Goldman Sachs post-earnings note on March 2, when the stock was trading at $182.48. From that level, the stock has gained roughly 0.5%, or $0.86, to reach $183.34.
It wasn’t about a flashy price-target hike, but was perhaps something more important with the bank bumping its earnings estimates following another blowout quarterly showing.
Like Bryson, the bank’s analysts feel that Nvidia’s robust data center strength, incredible guidance, and growing visibility into hyperscaler and AI spending set up a stronger earnings path ahead.
For Wedbush, that improving demand backdrop backs up the firm’s lofty valuation outlook, while reinforcing Nvidia’s position as a critical enabler of the AI economy.
Wall Street price targets for Nvidia stock
- Goldman Sachs: $250
- JPMorgan: $265
- Bank of America: $300
- Bernstein: $300
- Raymond James: $291
- Truist Securities: $283
Sources: Investing, MarketBeat
Wedbush doubles down on Nvidia’s AI leadership
Bryson’s bullishness on Nvidia reflects a broader conviction that the AI infrastructure cycle still has plenty of runway left.
The core thesis is that Nvidia still remains the clearest beneficiary of the ongoing surge in accelerated computing demand.
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Nvidia’s incredible dominance in data-center computing is a big part of it, becoming the company’s potent economic engine.
The segment generated nearly $62.3 billion in sales in the most recent quarter, which accounts for the majority of Nvidia’s total revenues. That growth was spearheaded by the big hyperscalers and enterprises racing to develop large-scale AI clusters.
Wedbush argues that this tremendous cycle is still in its early stages. Spending from the top cloud providers continues to rise at a relentless pace, while a new class of AI-native customers emerges that includes model developers and sovereign AI initiatives.
In cashing in on that demand, Nvidia boasts the platform advantage.
The powerful combination of GPUs, software ecosystems, networking hardware, and integrated systems makes it virtually impossible for its competition, reinforcing its leadership in AI-powered computing.
On top of that, the firm sees stronger visibility into future demand.
Nvidia’s latest quarterly results showed an eye-popping $68.1 billion in quarterly sales, up roughly 73% year over year, underscoring the immense scale of the AI spending wave.
Related: Veteran analyst drops eye-popping price target on Palantir stock
For some color on that unrelenting wave, Broadcom dished out its quarterly results as well, where sales more than doubled to $8.4 billion, while guiding AI chip sales higher for the upcoming quarter.
Also, Broadcom views AI chip sales exceeding a gobsmacking $100 billion on the way to 2027, Reuters reported.
Nvidia is therefore the critical supplier behind the global AI buildout, a dynamic that should continue to support more ongoing revisions in long-term expectations.
Nvidia stock returns vs. the Roundhill Magnificent Seven ETF (MAGS) (proxy for Magnificent 7)
- Over the past 1 month, Nvidia stock returned 5.25%, compared with -2.90% for the MAGS ETF.
- Over the past 6 months, Nvidia stock returned 6.80%, compared with 2.96% for the MAGS ETF.
- Over the past 1 year, Nvidia stock returned 58.07%, compared with 28.13% for the MAGS ETF.
Source: Seeking Alpha
Risks to Nvidia’s bullish thesis
Nvidia sits firmly at the heart of the AI infrastructure buildout, but investors continue circling a handful of risks that muddle its compelling bull case.
Perhaps the most obvious overhang on the tech giant remains China.
Nvidia has apparently been pushed out of the country’s robust data-center compute market due to U.S. export restrictions.
In its latest earnings call, the company’s CFO Collette Kress weighed in.
That’s a dramatic shift from a couple of years ago, when the region represented a massive growth engine.
According to Nvidia’s filings, China (including Hong Kong) generated a massive $19.7 billion, or about 9.1% of revenue in fiscal 2026, down substantially from 19% in fiscal 2025 and about 20% in fiscal 2024.
Having said that, the policy environment is fluid.
Nvidia revealed it was only allowed to ship a minuscule number of chips under license, and even those shipments face a ton of uncertainty.
It’s worth noting that at one point, it took a massive $4.5 billion charge linked to H20 inventory and purchase commitments on the back of changes in export rules.
On a broader scale, Nvidia’s leaving the Chinese market opens the door for local competitors I’ve covered in the past, like Moore Threads and others, to build powerful ecosystems that could challenge its dominance over time.
Moreover, the relentless AI spending cycle itself could be a major headwind.
The bull case shows that hyperscalers continue pouring capital into AI data centers, but there’s always a potential digestion period for investors and customers to consider.
Competition remains another focal issue.
The biggest in tech continue to develop custom AI accelerators, while rivals like AMD are pushing for alternatives.Supply constraints, including HBM memory and advanced packaging, also create bottlenecks.
Related: Amazon’s AWS shocker overseas sends a warning to U.S. investors
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