NVIDIA Expands Open Model Families to Power the Next Wave of Agentic, Physical and Healthcare AI

Rhea-AI Summary

NVIDIA (NVDA) expanded its open model families on March 16, 2026 to power agentic, physical and healthcare AI. Key releases include Nemotron 3 omni-understanding models, Isaac GR00T N1.7, Alpamayo 1.5, Cosmos 3 and the BioNeMo Proteina-Complexa model.

Highlights: Nemotron 3 Ultra offers 5x throughput efficiency; nvQSP simulation reached up to 77x faster performance; ~30M protein complex predictions added, including 1.7M high-confidence entries.

Positive

• Nemotron 3 Ultra: 5x throughput efficiency on Blackwell
• nvQSP GPU simulation: up to 77x faster than CPU
• AlphaFold expansion: ~30M complex predictions added
• 1.7M high-confidence protein complex predictions added
• GR00T N2 preview: >2x task success vs leading VLA models
• Broad adoption by firms including CrowdStrike, ServiceNow, Novo Nordisk

Negative

• None.

News Market Reaction – NVDA

-0.70%

-0.70% Session close to close

In the Mar 17 session, NVDA declined 0.70%, reflecting a mild negative market reaction.

Data tracked by StockTitan Argus on the day of publication.

Market Context

This announcement expands NVIDIA’s open AI model families across agentic, physical and healthcare ap...

Analysis

This announcement expands NVIDIA’s open AI model families across agentic, physical and healthcare applications, adding platforms like Nemotron 3, Cosmos 3, Isaac GR00T N1.7 and Proteina‑Complexa. Historically, AI-tagged news for NVIDIA has produced mixed stock reactions, with an average move of -0.5%. Investors may monitor how adoption by partners, performance gains such as nvQSP’s up to 77x speedup, and continued model releases influence longer-term demand for NVIDIA’s full AI stack.

Key Figures

Nemotron 3 Ultra throughput: 5x throughput efficiency Researchers using Kosmos: more than 50,000 researchers Protein complex predictions: about 30 million predictions +2 more

5 metrics

Nemotron 3 Ultra throughput 5x throughput efficiency Nemotron 3 Ultra on NVIDIA Blackwell platform

Researchers using Kosmos more than 50,000 researchers Users of Edison Scientific’s Kosmos AI scientist

Protein complex predictions about 30 million predictions Expansion of AlphaFold Protein Structure Database

High-confidence complexes 1.7 million predictions High-confidence additions to AlphaFold database

nvQSP speedup up to 77x faster GPU-accelerated nvQSP vs single-threaded CPU simulations

Previous AI Reports

5 past events · Latest: Mar 11 (Positive)

Same Type Pattern 5 events

Date	Event	Sentiment	24h Move	Catalyst
Mar 11	AI cloud partnership	Positive	+0.7%	NVIDIA invests $2B in Nebius to scale full‑stack AI cloud capacity.
Mar 03	AI conference preview	Positive	-1.3%	Announcement of GTC 2026 with 30,000+ attendees and AI-focused agenda.
Feb 17	AI infra partnership	Positive	+1.6%	Multiyear partnership with Meta to codesign large-scale AI infrastructure.
Feb 03	Industrial AI deal	Positive	-2.8%	Long-term partnership with Dassault Systèmes on industrial AI and virtual twins.
Jan 26	AI infra expansion	Positive	-0.6%	Expanded CoreWeave collaboration to build >5GW of AI factories by 2030.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

AI-related announcements have produced mixed reactions, with several positive partnership and infrastructure updates followed by both modest gains and notable pullbacks.

Recent Company History

Over recent months, NVIDIA’s AI news flow has focused on hyperscale infrastructure and strategic cloud and platform partnerships. Deals with Nebius, Meta, Dassault Systèmes and CoreWeave highlighted multiyear, multigigawatt AI factory buildouts and deployment of Grace, Vera and Blackwell/Rubin GPUs. Price reactions to these AI updates have been inconsistent, ranging from gains above 1% to declines near -3%. Today’s expansion of open model families fits this ongoing narrative of scaling AI infrastructure and software ecosystems across industries.

Key Terms

agentic ai, multimodal, automatic speech recognition, text-to-speech, +4 more

8 terms

agentic ai technical

"NVIDIA open models are being adopted ... for agentic AI;"

Agentic AI refers to computer systems that can make their own decisions and take actions without needing someone to tell them what to do each time. It's like giving a robot a degree of independence to solve problems or achieve goals on its own, which matters because it could change how we work and interact with technology in everyday life.

multimodal technical

"Nemotron 3 omni-understanding multimodal models power AI agents, delivering natural conversations"

Multimodal describes an approach, product, or system that uses two or more different types of inputs, methods, or channels — for example combining text, images and audio in a technology product, or blending drugs, devices and therapy in medical care. For investors, multimodal solutions can broaden market reach and competitive differentiation but also add development cost, operational complexity and regulatory hurdles; think of it like a hybrid car that offers more capabilities but requires more parts and oversight.

automatic speech recognition technical

"The model combines automatic speech recognition, large language model processing and text-to-speech"

Automatic speech recognition is software that listens to spoken language and converts it into written text, like a digital stenographer or a phone that types what you say. Investors care because the technology can cut labor costs, enable new products and services, improve customer support and regulatory record-keeping, and influence revenue or margins for companies that build, license, or rely on voice-driven systems.

text-to-speech technical

"automatic speech recognition, large language model processing and text-to-speech capabilities"

Text-to-speech is software that converts written words into natural-sounding spoken audio, like a narrator reading a page aloud. For investors it matters because it can broaden a product’s audience (for example, people who prefer audio or need accessibility), reduce customer support and content production costs, and create new revenue or engagement channels—factors that can affect user growth, margins, and regulatory compliance.

foundation models technical

"NVIDIA is accelerating the development of autonomous systems with new foundation models and simulation tools"

Foundation models are very large artificial intelligence systems trained on broad, general data so they can be quickly adapted to many different tasks, like a powerful, general-purpose engine or a Swiss Army knife for software. They matter to investors because they can lower costs and speed innovation across industries, create new products or revenue streams, and change competitive dynamics, while also introducing operational and regulatory risks that can affect a company’s financial outlook.

generative model medical

"Proteina-Complexa is a generative model for protein binder design"

A generative model is a computer program that learns patterns from existing data and produces new, realistic content—such as text, images, code, or simulated data—much like a skilled chef who studies recipes and invents new dishes. For investors, it matters because these models can create new products, automate tasks, reduce costs, and open revenue opportunities, while also introducing risks around accuracy, intellectual property, and regulatory oversight that can affect valuations and adoption.

gpu-accelerated technical

"NVIDIA also introduced nvQSP, a GPU-accelerated simulation engine"

Using graphics processing units (GPUs) to run compute‑heavy tasks much faster than standard central processors by handling many small operations at once. For investors, GPU‑acceleration can shorten time to insight and lower costs for advanced workloads like artificial intelligence, large‑scale data analysis, or simulations, potentially boosting product performance, enabling new services, and improving competitive position—think switching from a bicycle to a high‑speed train for moving large data loads.

simulation engine technical

"nvQSP, a GPU-accelerated simulation engine that enables pharmaceutical researchers"

A simulation engine is computer software that creates and runs virtual versions of real-world systems—such as markets, operations, or clinical trials—to predict how they might behave under different conditions. For investors it acts like a flight simulator for money: it lets you test strategies, estimate potential gains or losses, and spot risks without committing capital, improving decision-making and valuation under uncertainty.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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News Summary:

• NVIDIA Nemotron 3 omni-understanding models power AI agents delivering natural conversations, complex reasoning and advanced visual capabilities.
• NVIDIA Isaac GR00T N1.7, NVIDIA Alpamayo 1.5 and NVIDIA Cosmos 3 models push the boundaries of physical AI reasoning and action across robots and autonomous vehicles.
• Part of the NVIDIA BioNeMo platform, the Proteina-Complexa model accelerates protein drug discovery — alongside a new open dataset comprising millions of new, AI-predicted protein complex predictions, developed by NVIDIA, Google DeepMind, EMBL’s European Bioinformatics Institute and Seoul National University.
• NVIDIA open models are being adopted by CodeRabbit, CrowdStrike, Cursor, Factory, ServiceNow and Perplexity for agentic AI; LG Electronics and Milestone Systems for physical AI; and Novo Nordisk, Viva Biotech and Manifold Bio for healthcare AI.

SAN JOSE, Calif., March 16, 2026 (GLOBE NEWSWIRE) -- GTC -- NVIDIA today announced it is expanding its open model families to power the next wave of agentic, physical and healthcare AI, introducing new models that enable developers and scientists to build intelligent systems that can reason and act across digital and real-world environments.

Open models are essential to advancing innovation at global scale. NVIDIA’s expanding portfolio — including NVIDIA Nemotron™ for agentic systems, NVIDIA Cosmos™ for physical AI, NVIDIA Alpamayo for autonomous vehicles, NVIDIA Isaac™ GR00T for robotics and NVIDIA BioNeMo™ for biomedical research — contributes advanced models and frameworks to unlock new capabilities across industries.

“Open source AI has become a global force for innovation,” said Kari Briski, vice president of generative AI software at NVIDIA. “From biology and scientific discovery to robotics and autonomous machines, NVIDIA open model families extend intelligence beyond language, enabling developers worldwide to build intelligent agents and power breakthroughs across digital and physical industries.”

NVIDIA Nemotron 3 Ultra, Omni and VoiceChat Models Power AI Agents
The NVIDIA Nemotron family is expanding with omni-understanding models across language, vision, voice and safety, extending multimodal intelligence to help developers build specialized, agentic AI.

NVIDIA Nemotron 3 omni-understanding multimodal models power AI agents, delivering natural conversations, complex reasoning and advanced visual capabilities.

• Nemotron 3 Ultra delivers frontier-level intelligence with 5x throughput efficiency with the NVFP4 format on the NVIDIA Blackwell platform to power AI-native applications such as coding assistants, search and complex workflow automation.
• Nemotron 3 Omni integrates audio, vision and language understanding, allowing AI agents to extract insights from videos and documents with high efficiency and accuracy.
• Nemotron 3 VoiceChat supports real-time conversations in which AI listens and responds simultaneously. The model combines automatic speech recognition, large language model processing and text-to-speech capabilities in a single system.
• Nemotron safety models and retrieval pipeline strengthen trustworthy multimodal systems by detecting unsafe content across text and images, while an agentic retrieval pipeline improves the relevance and accuracy of outputs.

LangChain has integrated NVIDIA Nemotron models and other NVIDIA Agent Toolkit software into its agent development platform, enabling businesses to build, deploy and monitor intelligent AI assistants that can automate complex tasks at enterprise scale.

Leading companies including Automation Anywhere, CodeRabbit, CrowdStrike, Cursor, Factory, Distyl, Genspark, Perplexity and ServiceNow are deploying NVIDIA Nemotron models to power advanced agentic applications. Edison Scientific is using NVIDIA Nemotron as an integral component of Kosmos, an autonomous AI scientist used by more than 50,000 researchers that performs hundreds of research tasks in parallel, compressing months of research into a day.

AI developers worldwide are using Nemotron models data and frameworks to build sovereign models that serve billions of people in their native languages and align with local cultures and values. These include AI Singapore, Bielik.ai, Indosat Ooredoo Hutchison, LINAGORA, SOOFI, Stockmark, Trillion Labs, Viettel and YTL AI Labs.

NVIDIA has also released Nemotron-Personas, a collection of privacy-preserving, fully synthetic datasets grounded in local census and demographic data. The France dataset, developed in collaboration with Pleias, is available today, joining existing datasets for the U.S., Japan, India, Brazil and Singapore.

New Open Models Advance Physical AI Reasoning
NVIDIA is accelerating the development of autonomous systems with new foundation models and simulation tools designed to help robots and vehicles perceive, reason and act in the physical world. These include:

• NVIDIA Cosmos 3, the first world foundation model to unify synthetic world generation, physical AI reasoning and action simulation, is expected to come soon, helping physical AI operate in complex environments.
• NVIDIA Isaac GR00T N1.7, an open reasoning vision language action (VLA) model purpose-built for humanoids, is now commercially viable for real-world deployment.
• NVIDIA Alpamayo 1.5, a reasoning VLA model, supercharges autonomous vehicles reasoning with navigation guidance, prompt conditioning, flexible multi-camera support and configurable camera parameters.
  

During his GTC keynote, NVIDIA founder and CEO Jensen Huang also previewed GR00T N2, a next-generation robot foundation model based on DreamZero research. Built on a new world action model architecture, the model helps robots succeed at new tasks in new environments more than twice as often as leading VLA models. Slated to be available by the end of the year, GR00T N2 currently ranks No. 1 on MolmoSpaces and RoboArena for generalist robot policies.

HCLTech, Johnson & Johnson MedTech, Milestone Systems, mimic robotics, Skild AI, Tulip, and The Toyota Research Institute are using NVIDIA Cosmos to accelerate physical AI training and video analytics. Humanoid, LG Electronics, NEURA and Noble Machines are adopting NVIDIA Isaac GR00T N1.7 to scale humanoid robot deployment.

Open Models Accelerate Healthcare and Life Sciences Research
NVIDIA is advancing AI-driven discovery in healthcare and life sciences with open, multimodal foundation models and datasets that accelerate biomedical research, drug discovery, medical imaging and understanding of scientific literature.

NVIDIA BioNeMo is expanding as an open AI development platform for healthcare and life sciences, enabling researchers to model, design and simulate biological systems at scale.

Proteina-Complexa is a generative model for protein binder design that accelerates structure-based drug discovery and therapeutic development. Novo Nordisk, Viva Biotech and Manifold Bio are using Proteina-Complexa to design proteins that bind to a target protein, and have experimentally tested the generated designs.

NVIDIA has collaborated with EMBL’s European Bioinformatics Institute, Google DeepMind and Seoul National University to massively expand the AlphaFold Protein Structure Database — calculating about 30 million protein complex predictions and adding 1.7 million high-confidence predictions to the AlphaFold database — to speed the discovery of new drug targets and disease biology.

NVIDIA also introduced nvQSP, a GPU-accelerated simulation engine that enables pharmaceutical researchers to explore far more treatment scenarios in computer models before clinical trials begin. In benchmark tests, nvQSP delivered up to 77x faster performance compared with traditional single-threaded CPU simulations, allowing scientists to analyze hundreds of dose levels and patient subpopulations in the time it previously took to simulate just a few.

Availability
Select NVIDIA open models, data and frameworks are available on GitHub and Hugging Face, a range of cloud, inference and AI infrastructure platforms, and build.nvidia.com.

Many of the models are also available as NVIDIA NIM™ microservices for secure, scalable deployment on any NVIDIA-accelerated infrastructure, from the edge to the cloud.

Watch the GTC keynote from Huang and explore sessions.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.

For further information, contact:
Natalie Hereth
Corporate Communications
NVIDIA Corporation
press@nvidia.com

Certain statements in this press release including, but not limited to, statements as to: from biology and scientific discovery to robotics and autonomous machines, NVIDIA open model families extending intelligence beyond language, enabling developers worldwide to build intelligent agents, power breakthroughs and accelerate innovation across digital and physical industries; the benefits, impact, performance, and availability of NVIDIA’s products, services, and technologies; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, BioNeMo, Nemotron, NVIDIA Cosmos and NVIDIA NIM are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/99dd8586-2925-4cd6-a028-fedebf38d15c

FAQ

What performance gains does NVIDIA Nemotron 3 Ultra offer for NVDA users?

Nemotron 3 Ultra delivers about 5x throughput efficiency on Blackwell hardware. According to the company, this uses the NVFP4 format to enable higher-throughput agentic applications like coding assistants and workflow automation.

How much faster is nvQSP compared to CPU simulations for drug modeling?

nvQSP achieved up to 77x faster performance versus single-threaded CPU simulations. According to the company, this lets researchers simulate many more dose levels and patient subpopulations before clinical trials.

What did NVIDIA add to the AlphaFold protein complex database on March 16, 2026?

NVIDIA helped add about 30 million protein complex predictions, including 1.7 million high-confidence entries. According to the company, collaborators included DeepMind, EMBL-EBI and Seoul National University.

Which NVIDIA models support physical AI for robots and autonomous vehicles (NVDA)?

NVIDIA released Cosmos 3, Isaac GR00T N1.7 and Alpamayo 1.5 for physical AI and autonomous vehicles. According to the company, these models enable perception, reasoning and action in complex real-world environments.

How is Proteina-Complexa being used in protein drug discovery for NVDA stakeholders?

Proteina-Complexa is a generative model for protein binder design used to accelerate structure-based drug discovery. According to the company, partners like Novo Nordisk have experimentally tested generated designs.

Where can developers access NVIDIA open models and datasets for NVDA deployment?

Select open models, data and frameworks are available on GitHub, Hugging Face and build.nvidia.com as well as NIM microservices. According to the company, many models deploy across cloud and edge NVIDIA-accelerated infrastructure.