Nvidia (NVDA) stock has clearly been Wall Street’s biggest AI winner, but Morgan Stanley feels it has much more room to run.
Analyst Joe Moore just bumped his price target from $250 to $235, a massive 38% upside from Nvidia’s current price at $181.46.
Moore, rated 5 stars on TipRanks, feels the concerns about Google-parent Alphabet (GOOGL) or Advanced Micro Devices (AMD) catching up are “overstated,” with new checks confirming Nvidia hasn’t dropped any meaningful market share.
Also read: Forget Palantir, another AI stock is up 180% in 2025
Instead, demand for its GPUs, HBM, and advanced packaging remains hotter than expected as businesses race to scale AI models.
Moore feels that Nvidia still remains the go-to for customers, because it continues delivering the best overall cost-and-performance equation, backed by a robust software stack and dependable long-term roadmap.
Morgan Stanley’s Joe Moore just hiked his Nvidia price target to $250, reaffirming the chipmaker’s dominance in the AI race.
Photo by Christian Wiediger on Unsplash
Nvidia stock’s ceiling just moved higher
Moore’s optimism is down to Nvidia’s “end-to-end advantage” in the GPU space.
That robust combo of superior chip performance, software maturity, and deployment speed positions it head-and-shoulders above its competition.
In essence, customers aren’t choosing Nvidia for its raw power, but because it shortens training times and cuts operating costs, while maintaining large-scale AI projects on schedule.
More Nvidia:
- Is Nvidia’s AI boom already priced in? Oppenheimer doesn’t think so
- Morgan Stanley revamps Nvidia’s price target ahead of big Q3
- Investors hope good news from Nvidia gives the rally more life
- Bank of America resets Nvidia stock forecast before earnings
- AMD flips the script on Nvidia with bold new vision
Moore also notes that the tight supply for GPUs, HBM, and advanced packaging shows how aggressively hyperscalers are growing AI workloads, reinforcing Nvidia’s enviable position in the race.
For perspective, Wall Street’s consensus on Nvidia stock sits at an average $250.66 price target, which implies nearly a 38% upside from current levels.
Moore’s new $250 target matches that consensus, while putting Morgan Stanley firmly in the camp giving Nvidia another leg up. The Street’s high-end estimate reaches $352, so Moore’s call positions Nvidia toward the bullish end of the range.
Related: Cathie Wood dumps $8.46 million in software giant
Beyond Morgan Stanley, other heavyweights also bumped their Nvidia targets recently:
- Goldman Sachs & JPMorgan both lifted their 12-month Nvidia targets to around $250, on the back of still-surging AI infrastructure demand and healthy data-center visibility.
- Jefferies bumped its target to $250 from $240 while reiterating a buy, saying Nvidia “answered the bell” on growth, while being critical of the AI build-out.
- Cantor Fitzgerald went a step further, lifting its target to a Street-high $300 from $240, keeping Nvidia as a “Top Pick” overweight. The firm makes the case that we’re still in the early innings of a multi-trillion-dollar AI infrastructure cycle.
Related: History of Nvidia: Company timeline and facts
Why Nvidia still owns the AI chip market
Moore’s argument that Nvidia hasn’t lost any meaningful market share may sound like analyst shorthand, but the data actually back him up.
The latest AI-server work by TrendForce highlights that Nvidia dominates nearly 70% of the AI chip market in 2025.
That’s after accounting for all the hullabaloo with the rise of Google TPUs and other custom ASICs. It also notes that hyperscaler capex remains heavily “concentrated on Nvidia’s high-end GPUs,” with in-house chips mostly supplementary at this point.
Related: Short-seller Michael Burry takes aim at another major tech stock
Further, Dell’Oro’s 2Q 2025 data-center components report echoes the same view.
Nvidia trumped all vendors in data-center IT component sales, with Blackwell Ultra in particular being the key driving force of the accelerator and high-bandwidth-memory boom.
On top of that, broader industry syntheses still put Nvidia’s market share somewhere between 80% to 95% of the total AI-accelerator market and nearly 92% of data-center GPU share.
Additional checks from TrendForce, Counterpoint, Canalys, and Omdia support that pattern, forecasting 70%-80% in AI-GPU shipment share for Nvidia through 2025-26.
Also, OEMs such as Dell, HPE, Supermicro, and Lenovo are sticking with Nvidia in designing their flagship AI servers around Hopper and Blackwell.
Even outside Wall Street, we’re seeing a similar pattern.
For instance, in a post from Reddit’s r/dataisbeautiful (a subreddit with over 1 million weekly visitors), one user charted GPU price-to-performance trends across multiple Nvidia generations.
Though the post wasn’t focused on data-center AI training, the broader story still lines up; every new Nvidia generation delivers more work for the dollar.
Moreover, that consumer-level takeaway aligns with what independent AI benchmarks show at a much larger scale.
In one test reported by AIMultiple, an Nvidia H100 pushed nearly 23,000 tokens per second on a $2.69/hour cloud instance, which is approximately 8,600 tokens per second for every dollar spent.