Bank of America resets Nvidia stock forecast after key event
I concluded last year with two in-depth articles. Nvidia. While I was writing “What awaits Nvidia shares in 2026”, I thought there would be no news from Nvidia for a while.
Then Nvidia completed its investment in Intel, and I wrote a detailed analysis of this collaboration, “Nvidia delivers on an important promise for 2025.”
At that point I thought January would be a quiet month, but I was so wrong.
Nvidia decided to continue with its announcements during CES. It looks like the company has nothing left to announce at its own GTC conference in March.
The company went so far as to introduce their next-generation GPU, Vera Rubin, something it would usually reserve for the GTC.
Why this rush? Is the bubble about to burst or not? AMDIs the Helios rack system planned to be released this year putting pressure on Nvidia?
I think it was AMD’s Helios and Google’s TPUs that made Nvidia shift gears, and it shows.
Nvidia CEO Jensen Huang believes "The ChatGPT moment for physical AI is here."Shutterstock-Glen Photo” loading=”eager” height=”540″ width=”960″ class=”yf-lglytj loader”/>
Nvidia CEO Jensen Huang believes that “the ChatGPT moment for physical AI is here.”Shutterstock-Glen Photo
Bank of America analyst Vivek Arya and his team say Nvidia (NVDA) CES 2026 keynote and financial analyst Q&A session on January 5. Following the event, they updated their views on NVDA shares in a research note shared with TheStreet.
The team, Nvidia CEO Jensen Huang He noted that demand was “very high.” artificial intelligence computing continues and announced its new Vera Rubin AI platform.
AI scaling remains on track, with token generation reduced by five times and annual cost by 10 times.
Six new AI chips have been announced for the Vera Rubin platform, planned for the second half of 2026.
The company introduced a new pod-level context memory storage platform.
Nvidia continues to manage all major LLMs today.
Artificial intelligence will be financed by modernizing artificial intelligence and changing R&D methods.
Groq/SRAM negotiation can be useful for extremely low latency workloads.
AI is scaling beyond Master’s to physical AI.
China has demand for H200 but is still waiting for a license.
An informed and attentive reader will notice that the analyst team may have overlooked the fact that Google Gemini 3 is trained and runs on Google’s own TPUs. CNBC.
Nvidia’s continued dominance in the AI computing, networking and ecosystem trades at only about a 19x price-to-earnings ratio, or in line with the broader price-to-earnings ratio, the team said. S&P 500 index, despite having a superior EPS CAGR of over 35% and an EPS CAGR of over 40% free cash flow.
Arya reiterated a buy rating and $275 target price based on Nvidia’s 28x cash-exclusive price-to-earnings ratio estimate for the calendar year 2027, which is within the historical forward-year price-to-earnings range of 25 to 56.
Weakness in the consumer-focused gaming market
Competition with large public companies
Bigger-than-expected impact of restrictions on IT shipments to China
Erratic and unpredictable sales in startups, data centers, and automobiles markets
Potential to slow capital returns
Enhanced government review of Nvidia’s dominant market position in artificial intelligence chips
Nvidia Introduced the next generation AI Rubin platform, consisting of six new chips.
The Rubin platform uses exceptional common design across its six chips: Vera CPU, Rubin GPU, NVLink 6 Switch, ConnectX-9 SuperNIC, BlueField-4 data processing unit (DPU), and Spectrum-6 Ethernet Switch.
“Rubin comes at exactly the right time, as the demand for AI computing for both training and inference is skyrocketing. With our pace of delivering the next generation of AI supercomputers every year and outstanding co-design on six new chips, Rubin is taking a giant leap towards the next frontier of AI,” Huang said.
Related: Bank of America resets Micron stock price target and rating
The company has also launched its own. Alpamayo A family of open AI models, simulation tools, and datasets designed for reasoning-based autonomous vehicle (AV) development. According to the company, the Alpamayo family offers thought-chain, reasoning-based vision language action models that bring human thinking to AV decision-making processes.
Huang said: “The ChatGPT moment for physical AI has arrived, when machines begin to understand, reason and act in the real world. Robotaxies are among the first to benefit. Alpamayo brings reasoning to autonomous vehicles, allowing them to think through rare scenarios, drive safely in complex environments and explain driving decisions; it is the foundation of safe, scalable autonomy.”
More Nvidia:
Siemens and Nvidia announced the expansion of its partnerships for the development of industrial and physical artificial intelligence solutions.
Roland Busch, chairman and CEO of Siemens NETWORK“Together, we are building the Industrial AI operating system by redefining how the physical world is designed, built, and operated to scale AI and deliver real-world impact. By combining Nvidia’s leadership in accelerated computing and AI platforms with Siemens’ leading hardware, software, industrial AI, and data, we empower our customers to develop products faster with the most comprehensive digital twins, adapt manufacturing in real time, and accelerate technologies from chips to AI factories.”
The companies plan to build the world’s first fully AI-driven, adaptive manufacturing facilities. According to the plan, the first one will be the Siemens Electronics Factory, which will be established in Erlangen, Germany, in 2026.
Related: Experienced analyst gave a clear message about Intel shares
