Before sharing my prediction about where Nvidia stock will trade in December 2026, I want to discuss the most bullish and bearish forecasts among Wall Street analysts:<\/p>\n
At the bullish extreme, Mark Lipacis at Evercore recommends buying Nvidia. His target price of $352 per share implies 83% upside from the current share price of $192.
\nAt the bearish extreme, Jay Goldberg at Seaport Research recommends selling Nvidia. His target price of $140 per share implies 27% downside from the current share price.<\/p>\n
Here’s what investors should know.<\/p>\n
![\"An](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/01\/1769868129_337_.jpeg\"\/)
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Image source: Getty Images.<\/p>\n
The bull case: Nvidia stock soars 83% to $352 per share<\/p>\n
Nvidia is an accelerated computing company best known for its graphics processing units<\/a> (GPUs), chips that accelerate complex data center workloads like artificial intelligence<\/a> (AI). Nvidia holds about 85% market share in the AI accelerator market, and the company is well positioned to maintain its leadership due to its full-stack strategy.<\/p>\n In addition to designing GPUs, Nvidia develops adjacent data center hardware like CPUs and networking gear. The company integrates those components into rack-scale systems, providing customers with a turnkey solution for AI infrastructure. Additionally, Nvidia has an unmatched ecosystem of software tools that help developers build GPU-accelerated applications.<\/p>\n That full-stack strategy affords Nvidia a competitive moat<\/a> because it allows the company to optimize data center systems for performance and power efficiency in ways its competitors cannot. Consequently, while Nvidia GPUs are very expensive, its systems generally have a lower total cost of ownership than alternative options.<\/p>\n Evercore analyst Mark Lipacis says that moat will not only help Nvidia maintain its leadership in data center GPUs, a market forecast to grow at 36% annually through 2033, but also capture a larger percentage of data center spending. In addition, Lipacis expects Nvidia to be a major winner as the physical AI (autonomous vehicles<\/a> and robots<\/a>) revolution unfolds.<\/p>\n Nvidia’s full-stack approach should be equally advantageous in that market. The company provides the data center hardware and software needed to train models. It also provides the simulation engine needed to validate those models. And it provides the embedded processors needed to run physical AI applications in autonomous cars and robots.<\/p>\n Today’s Change<\/p>\n (-0.72%) $-1.38<\/p>\n Current Price<\/p>\n $191.13<\/p>\n Key Data Points<\/p>\n Market Cap<\/p>\n $4.6T<\/p>\n Day’s Range<\/p>\n $189.47 – $194.49<\/p>\n 52wk Range<\/p>\n $86.62 – $212.19<\/p>\n Volume<\/p>\n 179M<\/p>\n Avg Vol<\/p>\n 182M<\/p>\n Gross Margin<\/p>\n 70.05%<\/p>\n Dividend Yield<\/p>\n 0.02%<\/p>\n The bear case: Nvidia stock falls 27% to $140 per share<\/p>\n Jay Goldberg at Seaport Research sees growing demand for custom AI chips as a problem for Nvidia. In particular, Alphabet’s Tensor Processing Units (TPUs) have emerged as a serious challenger to Nvidia GPUs, with recent reports indicating Meta Platforms and Anthropic<\/a> will spends billions on the chips in the coming years.<\/p>\n However, while many of Nvidia’s largest customers have deployed custom AI accelerators, including Amazon and Microsoft, those chips lack prebuilt software tools, which means developers must build them from scratch. Few companies have the necessary resources, according to Nvidia CEO Jensen Huang<\/a>: “There just aren’t that many teams in the world who are extraordinary at building these incredibly complicated things.”<\/p>\n Beyond competition, Goldberg thinks Nvidia’s margins will be pressured in the next year. One reason is that high bandwidth memory (HBM) chips, which play a critical role in feeding data to GPUs, have skyrocketed in price due to an unprecedented supply shortage<\/a>. Another reason is that Nvidia has committed to spending $26 billion on cloud capacity in the next six years, primarily for research and development<\/a>.<\/p>\n Goldberg raises reasonable concerns, and investors should monitor Nvidia’s gross margins, but I do not think his argument is strong enough to justify selling the stock. In fact, investors should consider buying shares. The valuation of 47 times earnings<\/a> is reasonable for a company whose earnings are forecast to grow at 37% annually over the next three years.<\/p>\n My prediction: Nvidia stock will increase 35% to $260 per share<\/p>\n I think Nvidia will trade at $260 per share by December 2026. That implies about 35% upside from the current share price of $192. I selected that figure because it splits the bullish and bearish extremes, and because it represents a slight premium to the median target price of $250 per share.<\/p>\n![\"Nvidia](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/01\/1769868130_906_.png\"\/)
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