NVIDIA Accelerates Robotics Research and Development With New Open Models and Simulation Libraries

Rhea-AI Summary

NVIDIA (NASDAQ:NVDA) has announced major advancements in robotics development with the release of new open-source tools and models. The company unveiled the Newton Physics Engine, co-developed with Google DeepMind and Disney Research, now available in NVIDIA Isaac Lab. Additionally, NVIDIA introduced the Isaac GR00T N1.6 open foundation model for humanlike robot reasoning and new Cosmos world foundation models for AI development.

Key innovations include the Cosmos Reason model, which has been downloaded over 1 million times, and enhanced Cosmos WFMs with over 3 million downloads. The company also announced new AI infrastructure including the GB200 NVL72 system, RTX PRO Servers, and Jetson Thor powered by Blackwell GPU. Leading robotics companies including Boston Dynamics, Figure AI, and Agility Robotics are adopting NVIDIA's technologies.

Positive

• Launch of open-source Newton Physics Engine, enabling more accurate robot simulation and training
• Strong adoption metrics with Cosmos Reason reaching 1M+ downloads and Cosmos WFMs reaching 3M+ downloads
• Partnership with major tech companies like Google DeepMind and Disney Research
• Significant adoption by leading robotics companies including Boston Dynamics, Figure AI, and Agility Robotics
• Introduction of new high-performance AI infrastructure with GB200 NVL72, RTX PRO Servers, and Jetson Thor

Negative

• None.

Insights

AI & Robotics Technology Analyst

NVIDIA's new open-source robotics tools strengthen its AI ecosystem leadership and expand its technological moat in the growing physical AI market.

NVIDIA has unveiled a comprehensive suite of open-source robotics tools that significantly advances its position in the rapidly emerging physical AI market. The release of the Newton Physics Engine (co-developed with Google DeepMind and Disney Research) addresses a critical challenge in robotics development - the gap between simulation and real-world performance. By offering more accurate physics simulation, NVIDIA enables the quarter-million robotics developers worldwide to create robots that can reliably transfer skills from virtual training to physical environments.

The new Isaac GR00T N1.6 model with Cosmos Reason integration represents a substantial leap in robot cognition capabilities. This foundation model brings human-like reasoning to robots, allowing them to break down vague instructions into executable steps using prior knowledge and common sense - solving one of the most difficult problems in robotics: contextual understanding. The impressive adoption metrics for NVIDIA's Cosmos models (over 3 million downloads) and Physical AI Dataset (4.8 million downloads) demonstrate strong developer traction.

The business implications are substantial. NVIDIA is strategically expanding beyond its GPU dominance by creating an end-to-end robotics development ecosystem that spans hardware (Jetson Thor, GB200 NVL72) and software (Newton, Isaac Lab, Cosmos models). By making key components open-source while maintaining control of the underlying infrastructure, NVIDIA is employing the classic embrace-extend-monetize strategy that has proven successful in technology markets.

The impressive roster of partners adopting these technologies - including industry leaders like Boston Dynamics, Google DeepMind, Figure AI, and Meta - validates NVIDIA's approach and suggests growing industry consensus around its robotics stack. The company's dominance in academic research (referenced in nearly half of CoRL's accepted papers) further cements its position as the foundation for advanced robotics development.

This announcement effectively positions NVIDIA to monetize the growing physical AI market through its hardware (GPUs, servers) while expanding its technological moat through software and models that increase switching costs for developers invested in its ecosystem.

 News Summary:

• The open-source Newton Physics Engine — codeveloped with Google DeepMind and Disney Research, and now available in NVIDIA Isaac Lab — helps researchers and developers create more capable and adaptable robots.
• New NVIDIA Isaac GR00T open foundation model brings humanlike reasoning to robots, allowing them to break down complex instructions and execute tasks using prior knowledge and common sense.
• New NVIDIA Cosmos world foundation models enable developers to generate diverse data for accelerating training physical AI models at scale.
• Global researchers at leading universities such as Stanford University, ETH Zurich and the National University of Singapore are tapping NVIDIA accelerated computing and software to advance robotics research.
• Leading robot developers Agility Robotics, Boston Dynamics, Disney Research, Figure AI, Franka Robotics, Hexagon, Skild AI, Solomon and Techman Robot are adopting NVIDIA Isaac and Omniverse technologies.
  

SEOUL, South Korea, Sept. 29, 2025 (GLOBE NEWSWIRE) -- CoRL -- NVIDIA today announced that the open‑source Newton Physics Engine is now available in NVIDIA Isaac™ Lab, along with the open NVIDIA Isaac GR00T N1.6 reasoning vision language action model for robot skills and new AI infrastructure. Together, these technologies provide developers and researchers with an open, accelerated robotics platform that speeds iteration, standardizes testing, unifies training with on‑robot inference and helps robots transfer skills safely and reliably from simulation to the real world.

“Humanoids are the next frontier of physical AI, requiring the ability to reason, adapt and act safely in an unpredictable world,” said Rev Lebaredian, vice president of Omniverse and simulation technology at NVIDIA. “With these latest updates, developers now have the three computers to bring robots from research into everyday life — with Isaac GR00T serving as robot’s brains, Newton simulating their body and NVIDIA Omniverse as their training ground.”

Newton Opens New Standard for Physical Simulation in Robotics
Robots learn faster and safer in simulation, but humanoid robots — with their complex joints, balance and movements — push today’s physics engines to the limit. Over a quarter-million robotics developers worldwide need accurate physics, so the skills they teach robots in simulation can be executed safely and reliably in the real world.

Today, NVIDIA announced the beta release of Newton, an open-source, GPU-accelerated physics engine, managed by the Linux Foundation. Built on the NVIDIA Warp and OpenUSD frameworks, and codeveloped by Google DeepMind, Disney Research and NVIDIA, Newton is available now.

With Newton’s flexible design and ability to work with different types of physics solvers, developers can now simulate extremely complex robot actions, like walking through snow or gravel and handling cups and fruits, and successfully deploy them in the real world.

The latest adopters of Newton are esteemed research labs and universities such as ETH Zurich Robotic Systems Lab, Technical University of Munich and Peking University, robotics company Lightwheel, and simulation engine company Style3D.

Cosmos Reason Improves Robot Reasoning for New Open Isaac GR00T N1.6 Model
To perform humanlike tasks in the physical world, humanoids must understand ambiguous instructions and deal with the long tail of never-before-seen experiences.

The latest release of the open Isaac GR00T N1.6 robot foundation model, available soon on Hugging Face, will integrate NVIDIA Cosmos™ Reason, an open, customizable reasoning vision language model built for physical AI. Acting as the robot’s deep-thinking brain, Cosmos Reason turns vague instructions into step-by-step plans, using prior knowledge, common sense and physics to handle new situations and generalize across many tasks.

Cosmos Reason, downloaded over 1 million times and currently at the top of the Physical Reasoning Leaderboard on Hugging Face, can also curate and annotate large sets of real and synthetic data for model training. Cosmos Reason 1 is now available as an easy-to-use NVIDIA NIM™ microservice for AI model deployment.

Isaac GR00T N1.6 now lets humanoids move and handle objects simultaneously, allowing more torso and arm freedom to complete tough tasks like opening heavier doors.

Developers can post-train Isaac GR00T N models using the open-source NVIDIA Physical AI Dataset on Hugging Face. Downloaded over 4.8 million times, the dataset now includes thousands of synthetic and real-world trajectories.

Leading robot makers such as AeiROBOT, Franka Robotics, LG Electronics, Lightwheel, Mentee Robotics, Neura Robotics, Solomon, Techman Robot and UCR are evaluating Isaac GR00T N models for building general-purpose robots.

New Cosmos World Foundation Models for Physical AI Development
NVIDIA announced new updates to its open Cosmos WFMs, downloaded over 3 million times, that let developers generate diverse data for accelerating training physical AI models at scale using text, image and video prompts.

• Cosmos Predict 2.5, coming soon, combines the power of three Cosmos WFMs into one powerful model, cutting complexity, saving time and boosting efficiency. It supports longer video generation — capable of creating up to 30-second videos — as well as multi-view camera outputs for richer world simulations.
• Cosmos Transfer 2.5, coming soon, delivers faster, higher-quality results than previous models, while being 3.5x smaller. It can generate photorealistic synthetic data from ground-truth 3D simulation scenes and spatial control inputs like depth, segmentation, edges and high-definition maps.

New Workflow for Teaching Robot Grasping
Teaching a robot to grab an object is one of the most difficult challenges in robotics. It is not just about moving an arm but turning a thought into a precise action — a skill robots must learn through trial and error.

The new dexterous grasping workflow in the developer preview of Isaac Lab 2.3, built on the NVIDIA Omniverse™ platform, trains multi-fingered hand and arm robots in a virtual world using an automated curriculum. It starts with simple tasks and gradually ramps up the complexity. The workflow changes aspects like gravity, friction and the weight of an object, training robots to learn skills even in unpredictable environments.

Boston Dynamics’ Atlas robots learned grasping using this workflow to significantly improve its manipulation capabilities.

Leading robot developers Agility Robotics, Boston Dynamics, Figure AI, Hexagon, Skild AI, Solomon and Techman Robot are adopting NVIDIA Isaac and Omniverse technologies.

Evaluating Learned Robot Skills in Simulation
Getting a robot to master a new skill — like picking up a cup or walking across a room — is incredibly difficult, and testing these skills on a physical robot is slow and expensive.

The solution lies in simulation, which offers a way to test a robot’s learned skills against countless scenarios, tasks and environments. But even in simulation, developers tend to build fragmented, simplified tests that do not reflect the real world. A robot that learns to navigate a perfect, simple simulation will fail the moment it faces real-world complexity.

To let developers run complex, large-scale evaluations in a simulated environment without having to build the system from scratch, NVIDIA and Lightwheel are codeveloping Isaac Lab - Arena, an open-source policy evaluation framework for scalable experimentation and standardized testing. The framework will be available soon.

New NVIDIA AI Infrastructure Powers Robotics Workloads Anywhere
To enable developers to take full advantage of these advanced technologies and software libraries, NVIDIA announced AI infrastructure designed for the most demanding workloads, including:

• NVIDIA GB200 NVL72, a rack-scale system integrating 36 NVIDIA Grace™ CPUs and 72 NVIDIA Blackwell GPUs, which is being adopted by major cloud providers to accelerate AI training and inference, including complex reasoning and physical AI tasks.
• NVIDIA RTX PRO™ Servers, which offer a single architecture for every robot development workload across training, synthetic data generation, robot learning and simulation. RTX PRO Servers have been adopted by the RAI Institute.
• NVIDIA Jetson Thor™, powered by a Blackwell GPU, which enables robots to run multi-AI workflows for real-time, intelligent interactions and unlocks real-time on-robot inference — a breakthrough for high-performance physical AI workloads and applications such as humanoid robotics. Jetson Thor has been adopted by partners including Figure AI, Galbot, Google DeepMind, Mentee Robotics, Meta, Skild AI and Unitree.
  

NVIDIA Advances Robotics Research
NVIDIA technologies, including GPUs, simulation frameworks and CUDA^®‑accelerated libraries, were referenced in nearly half of CoRL’s accepted papers — with adoption across leading research labs and institutions such as Carnegie Mellon, University of Washington, ETH Zurich and National University of Singapore.

Also highlighted at CoRL is BEHAVIOR, a robotic learning benchmark project by the Stanford Vision and Learning Lab and Taccel, a high-performance simulation platform for advancing vision-based tactile robotics, developed by Peking University.

Learn more about NVIDIA’s robotics research work at CoRL, running Sept. 27-Oct. 2 in Seoul.

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

For further information, contact:
Paris Fox
Corporate Communications
NVIDIA Corporation
408-242-0035
pfox@nvidia.com

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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.

© 2025 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, CUDA, NVIDIA Cosmos, NVIDIA Grace, NVIDIA Isaac, NVIDIA Jetson Thor, NVIDIA NIM, NVIDIA Omniverse and NVIDIA RTX PRO 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:
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FAQ

What is NVIDIA's new Newton Physics Engine and why is it important for robotics?

The Newton Physics Engine is an open-source, GPU-accelerated physics engine co-developed with Google DeepMind and Disney Research. It's important because it enables developers to simulate complex robot actions like walking through snow or handling objects, allowing safer and more reliable skill transfer from simulation to real-world applications.

How does NVIDIA's Isaac GR00T N1.6 model improve robot capabilities?

Isaac GR00T N1.6 integrates Cosmos Reason to enable humanlike reasoning and task execution. It allows robots to break down complex instructions, use common sense, and handle new situations while providing more torso and arm freedom for complex tasks.

What companies are adopting NVIDIA's new robotics technologies?

Major robotics companies including Boston Dynamics, Agility Robotics, Figure AI, Hexagon, Skild AI, Solomon, and Techman Robot are adopting NVIDIA's Isaac and Omniverse technologies.

What new AI infrastructure has NVIDIA announced for robotics?

NVIDIA announced three key products: the GB200 NVL72 rack-scale system with 72 Blackwell GPUs, RTX PRO Servers for robot development workloads, and Jetson Thor powered by Blackwell GPU for on-robot inference.

How widely adopted are NVIDIA's Cosmos foundation models?

NVIDIA's Cosmos models have achieved significant adoption with Cosmos Reason reaching over 1 million downloads and ranking first on the Physical Reasoning Leaderboard, while Cosmos WFMs have been downloaded over 3 million times.