NVIDIA Launches Nemotron 3 Super Model with 120 Billion Parameters
Written by Emily J. Thompson, Senior Investment Analyst
Updated: Mar 11 2026
0mins
Should l Buy NVDA?
In a blog post, Kari Briski, vice president of generative AI software for enterprise at NVIDIA, wrote, "Launched today, NVIDIA Nemotron 3 Super is a 120-billion-parameter open model with 12 billion active parameters designed to run complex agentic AI systems at scale. Available now, the model combines advanced reasoning capabilities to efficiently complete tasks with high accuracy for autonomous agents. AI-Native Companies: Perplexity offers its users access to Nemotron 3 Super for search and as one of 20 orchestrated models in Computer. Companies offering software development agents like CodeRabbit, Factory and Greptile are integrating the model into their AI agents along with proprietary models to achieve higher accuracy at lower cost. And life sciences and frontier AI organizations like Edison Scientific and Lila Sciences will power their agents for deep literature search, data science and molecular understanding. Enterprise Software Platforms: Industry leaders such as Amdocs, Palantir, Cadence, Dassault Systemes and Siemens are deploying and customizing the model to automate workflows in telecom, cybersecurity, semiconductor design and manufacturing."
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Analyst Views on NVDA
Wall Street analysts forecast NVDA stock price to rise
41 Analyst Rating
39 Buy
1 Hold
1 Sell
Strong Buy
Current: 175.750
Low
200.00
Averages
264.97
High
352.00
Current: 175.750
Low
200.00
Averages
264.97
High
352.00
About NVDA
NVIDIA Corporation is an artificial intelligence (AI) infrastructure company. The Company is engaged in accelerated computing to help solve the challenging computational problems. Its segments include Compute & Networking and Graphics. The Compute & Networking segment includes its Data Center accelerated computing and networking platforms and AI solutions and software, and automotive platforms and autonomous and electric vehicle solutions, including software. The Graphics segment includes GeForce GPUs for gaming and personal computers (PCs), and Quadro/NVIDIA RTX GPUs for enterprise workstation graphics. Its technology stack includes the foundational NVIDIA CUDA development platform that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, frameworks, algorithms, software development kits (SDKs), and application programming interfaces (APIs). Its platforms address four markets, which include Data Center, Gaming, Professional Visualization, and Automotive.
About the author
Emily J. Thompson
Emily J. Thompson, a Chartered Financial Analyst (CFA) with 12 years in investment research, graduated with honors from the Wharton School. Specializing in industrial and technology stocks, she provides in-depth analysis for Intellectia’s earnings and market brief reports.
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- Market Capitalization Changes: Despite Nvidia's stock being down 15% from its all-time high, resulting in a market cap loss of approximately $1 trillion, CEO Jensen Huang emphasized that AI will be a crucial growth driver for the company, potentially prompting investors to reassess its investment value.
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- Future Revenue Projections: OpenAI anticipates generating $280 billion in annual revenue by 2030, up from just $13.1 billion last year, with nearly half of its 2026 sales expected from enterprise customers, highlighting the potential of its business model.
- User Base Growth: ChatGPT boasts 900 million weekly active users, far surpassing competitors, with 50 million paying customers and 9 million business users, demonstrating its strong market appeal and growth potential.
- Compute Spending Plans: OpenAI plans to reach $600 billion in total compute spending by 2030; despite investor concerns about rising AI expenditures, this spending will drive the demand for rapid revenue growth post-IPO.
See More
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- Technological Advancement Showcase: Intel unveiled its Core Ultra Series 3 processors at CES 2026, built using 18A process technology, marking the latest progress in semiconductor manufacturing, which is expected to drive demand for AI data center chips and enhance the company's competitiveness.
See More
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- Alphabet's Growth Prospects: Alphabet's robust presence in digital advertising and cloud computing positions it for strong growth, particularly as AI applications enhance Google Search usage, with expected earnings growth of 15% annually, making current valuations attractive for investors.
- TPU Commercialization Progress: Alphabet's tensor processing units (TPUs) are now monetized through external customers, with agreements in place with companies like Meta and OpenAI, indicating a strengthening competitive edge in the AI infrastructure market and further solidifying its market position.
See More
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- Market Size Forecast: According to McKinsey, global spending on data centers could reach $7 trillion by 2030, indicating a shift in funding sources from hyperscalers to private equity and debt financing, which alters the financial landscape of the industry.
- Insurance Industry Pressure: Gallagher reports that the construction and operation of data centers have posed a 'real stress test' for major insurers over the past four to five years, particularly when investments exceed $20 billion at a single site, challenging the market's insurance capacity.
- Complex Financing Structures: With decreasing transparency in data center financing, Quinn Emanuel's Rana warns that current financing structures could expose downstream investors to second-order litigation risks, especially for pension funds and insurers unaware of concentration risks.
- GPU Lifecycle Issues: CoreWeave recently secured $8.5 billion in GPU-backed loans, yet the average GPU lifecycle of seven years contrasts sharply with the decades-long lifespan of data centers, creating potential risks in financing structures that could destabilize the industry.
See More
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- Market Financing Shift: With global spending on data centers projected to reach $7 trillion by 2030, tech giants are increasingly turning to private credit and debt markets to finance the capital-intensive construction of these facilities, indicating a challenge and opportunity for traditional financing models.
- Insurance Industry Pressure: The construction of AI data centers poses a 'stress test' for insurers, as the concentration of high-value assets in specific areas complicates the ability to provide sufficient insurance capacity, particularly in high-wind risk zones.
- Custom Insurance Policies: Insurance brokers are forming specialized teams and bespoke policies to address the unique risks associated with data centers, especially the additional risks introduced during the import and storage of equipment, reflecting a growing demand for specialized services in the market.
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See More
