Nvidia Stock (NVDA). has clearly been AI’s biggest gainer on Wall Street, but Morgan Stanley thinks it has a lot more room to run.
Analyst Joe Moore just topped his price target from $250 TO $235a massive 38% up from Nvidia’s current price to $181.46.
Moore, rated 5 stars on TipRanks, feels the concern about Google-parent Alphabet (GOOGL) or Advanced Micro Devices (AMD) catching up are “exaggerated”, with new checks confirming that Nvidia has not lost any significant market share.
Also Read: Forget Palantir, Another AI Stock Up 180% in 2025
Instead, demand for GPUs, HBM and advanced packaging remains higher than expected as companies race to scale AI models.
Moore believes that Nvidia remains the go-to place for customers as it continues to offer the best overall cost-performance equation, backed by a robust software stack and a reliable long-term roadmap.
Morgan Stanley’s Joe Moore just raised his price target on Nvidia to $250, reaffirming the chipmaker’s dominance in the AI race.Photo by Christian Wiediger on Unsplash” loading=”eager” height=”640″ width=”960″ class=”yf-1gfnohs loader”/>
Morgan Stanley’s Joe Moore just raised his price target on Nvidia to $250, reaffirming the chipmaker’s dominance in the AI race..Photo by Christian Wiediger on Unsplash
Moore’s optimism is due to Nvidia’s “end-to-end advantage” in the GPU space.
That robust combination of superior chip performance, software maturity and deployment speed positions it head and shoulders above its competition.
Essentially, customers don’t choose Nvidia for its raw power, but because it shortens training times and lowers operating costs while keeping large-scale AI projects on time.
More Nvidia:
Moore also notes that tight supply for GPUs, HBM and advanced packaging shows how aggressively hyperscalers are ramping up AI workloads, strengthening Nvidia’s enviable position in the race.
For perspective, the Wall Street consensus on Nvidia stock is flat an average price target of $250.66which implies an advantage of almost 38% from current levels.
Moore’s new $250 price target matches that consensus, while putting Morgan Stanley firmly in the camp, giving Nvidia another leg up. On the street the high-end estimate reaches $352so Moore’s call positions Nvidia toward the bullish end of the range.
Related: Cathie Wood drops $8.46 million into software giant
Beyond Morgan Stanley, other heavyweights have also beaten Nvidia targets recently:
Goldman Sachs and JPMorgan both raised their 12-month Nvidia targets to approx $250amid still growing demand for AI infrastructure and healthy data center visibility.
Jefferies he set his sights on $250 down from $240 while reiterating a buysaying that Nvidia has “answered the bell” on growth, while criticizing AI development.
Cantor Fitzgerald he took a step further, raising his target to a Street $300 from $240, keeping Nvidia as a “Top Pick” overweight. The firm argues that we are still at the beginning of a multi-trillion dollar AI infrastructure cycle.
Related: Nvidia History: Company Timeline and Facts
Moore’s argument that Nvidia hasn’t lost any significant market share may sound like analyst shorthand, but the data actually supports it.
The latest AI server work by TrendForce highlights that Nvidia pretty much dominates 70% of the AI chip market in 2025.
That’s after factoring in all the fuss with the rise of Google’s TPUs and other custom ASICs. It also notes that the hyperscaler’s capex remains heavily “focused on Nvidia’s next-generation GPUs,” with in-house chips largely add-on at this point.
Related: Short seller Michael Burry targets another major tech stock
Moreover, Dell’Oro’s Q2 2025 The Data Center Components report reflects the same view.
Nvidia topped all vendors in data center IT component sales, with Blackwell Ultra notably being the key driver of the accelerator and high-bandwidth memory boom.
Furthermore, broader industry syntheses still put Nvidia’s market share somewhere in between 80% to 95% of the total AI accelerator market and close 92% data center GPU sharing.
Additional checks from TrendForce, Counterpoint, Canalys and Omdia support this model, forecasting 70%-80% in AI-GPU shipment share for Nvidia by 2025-26.
OEMs like Dell, HPE, Supermicro and Lenovo are also sticking with Nvidia in designing their flagship AI servers around Hopper and Blackwell.
Even outside of Wall Street, we see a similar pattern.
For example, in a Reddit post r/dataisbeautiful (a subreddit with fish 1 million visitors weekly), a user presented GPU price-performance trends across several Nvidia generations.
While the post didn’t focus on AI training in data centers, the larger story still aligns; each new generation of Nvidia offers more work for a dollar.
What’s more, that consumer-level performance aligns with what independent AI benchmarks show at a much larger scale.
In a test reported by AIMultiple, an Nvidia H100 pushed close 23,000 tokens per second on a $2.69/hour cloud instance, which is approx 8,600 tokens per second for every dollar spent.
Related: A popular analyst reveals two new AI stocks for 2026
This story was originally published by TheStreet on December 3, 2025, where it first appeared in the Investing section. Add TheStreet as a favorite source by clicking here.
