NVIDIA Robotics Company Profile: Isaac Platform, Structure, Financials, Leadership and Stock
Updated: 7 days ago
NVIDIA does not build robots. It supplies the computers, simulation software and AI models that a growing share of the robotics industry uses to train and run them. The company reported revenue of USD 96.2 billion in its latest quarter and is valued at about USD 5.5 trillion, and its chief executive describes physical AI as coming online. This profile sets out NVIDIA's robotics platform, the companies that use it, the financial context, leadership and share data.
NVIDIA at a Glance
Fact | Detail |
Company | NVIDIA Corporation |
Founded | April 5, 1993, by Jensen Huang, Chris Malachowsky and Curtis Priem |
Headquarters | Santa Clara, California, USA |
Employees | About 42,000 |
Revenue | USD 215.9 billion in fiscal 2026 |
Net income | USD 120.1 billion in fiscal 2026 |
Latest quarter | USD 96.2 billion revenue in the quarter that ended July 26, 2026 |
Robotics offering | Isaac platform, Jetson edge computers, Omniverse and Cosmos |
Stock listing | Nasdaq: NVDA |
Market capitalization | About USD 5.5 trillion in October 2026 |
President and CEO | Jensen Huang |
Company Background
NVIDIA was founded in 1993 and built its business on graphics processors. The same chips proved to be well suited to training neural networks, which turned the company into the main supplier of AI computing. Robotics entered the picture through simulation: Omniverse was unveiled in 2020 as a virtual environment for engineers, and Isaac Sim, the robot simulator, was open-sourced in the same period. In 2024 Jensen Huang shifted the company's focus toward humanoid robots and self-driving cars. Isaac GR00T N1, an open foundation model for humanoid robots, and Cosmos, a model for generating synthetic training data, followed in 2025.
The Robotics Platform
NVIDIA describes Isaac as an open robotics development platform for autonomous mobile robots, robot arms, manipulators and humanoids.
Software
Component | What it does |
Isaac Sim | Physically based simulation and rendering with virtual robot and sensor models; also generates synthetic data |
Isaac Lab | GPU-accelerated robot learning built on Isaac Sim, for training and evaluating policies |
Isaac ROS | CUDA-accelerated packages built on ROS 2 for perception, navigation, object detection and trajectory optimization |
Isaac GR00T | Foundation models and tools for humanoid robots |
Newton | Open-source GPU physics engine for robot learning |
OSMO | Cloud-native orchestration for large-scale robotics workflows |
Omniverse and Cosmos | Simulation and world models used to build digital twins and generate training data |
Metropolis | Vision AI platform for video analytics from edge to cloud |
Hardware
Product | Role |
Jetson Thor series | Blackwell-based computer for high-end physical AI at the edge |
Jetson Orin Nano Super | Compact edge computer rated at 67 TOPS for generative AI |
Jetson Orin, Xavier, TX2 and Nano | Embedded AI modules for robots and edge devices, all using the JetPack software kit |
IGX platform | Industrial edge AI platform |
DGX systems | AI training infrastructure |
RTX PRO Server | Robot simulation, digital twins and synthetic data generation |
The three-computer approach
NVIDIA frames robotics as a problem that needs three computers: DGX systems to train the AI, Omniverse and Cosmos on RTX PRO Servers to simulate and test it, and Jetson systems in the robot for real-time inference and control.
Who Uses It
Skild AI: uses NVIDIA accelerated computing, Omniverse, Isaac Lab and Cosmos to train robot foundation models for many kinds of robots and tasks.
Agility Robotics: uses Isaac Sim and Isaac Lab to train its Digit humanoid.
Pegatron: uses NVIDIA AI, digital twin and simulation technologies for its PEGAVERSE factory automation platform.
Apptronik, Foxconn and Boston Dynamics: featured by NVIDIA among the companies working with its robotics technology.
Industrial robot makers: FANUC has integrated its ROBOGUIDE simulation software with Isaac Sim and Omniverse, KUKA presented its automation platform at NVIDIA's GTC conference in 2026, and Yaskawa's MOTOMAN NEXT runs on Jetson Orin.
Automation suppliers: Omron names NVIDIA as its partner for digital twins.
Recent Robotics Announcements
NVIDIA's results release for the quarter that ended in July 2026 listed these physical AI highlights:
Isaac GR00T Reference Humanoid Robot: an open humanoid reference design built on Jetson Thor and the GR00T development platform.
Cosmos 3: an open frontier model for physical AI.
Open source agent tools for Isaac: tools that turn robotics, autonomous vehicle and vision AI workflows into tasks that AI agents can execute.
Halos for Robotics: a full-stack safety system for physical AI that combines AI compute and safety in one platform.
Alpamayo 2 Super: an open reasoning model for robotaxi and autonomous vehicle development, available for commercial use.
Financial Performance
Item | Quarter ended July 26, 2026 |
Revenue | USD 96.2 billion, up 106% from a year earlier |
Data Center revenue | USD 89.0 billion, up 117% |
Edge Computing revenue | USD 7.2 billion, up 27% |
GAAP net income | USD 59.7 billion |
Gross margin | 75.0% |
Outlook for the next quarter | Revenue of USD 108.0 billion, plus or minus 2% |
Robotics is not reported as a separate line. It falls within Edge Computing, which at USD 7.2 billion is about 7% of revenue. Data centers generate the rest. The significance of robotics to NVIDIA is strategic: every robot trained with its tools also needs its training and simulation computers.
Leadership
Name | Role |
Jensen Huang | Co-founder, President and CEO |
Colette Kress | Chief Financial Officer |
Bill Dally | Chief Scientist |
Stock Information
Item | Detail |
Listing | Nasdaq: NVDA |
Share price | About USD 229 in October 2026 |
Market capitalization | About USD 5.5 trillion |
One-year change | Up about 25% |
Indices | Nasdaq-100, S&P 500, Dow Jones Industrial Average |
Note: share prices are indicative figures as of early October 2026 and change daily. This section is general information, not investment advice.
Strengths and Challenges
Strengths
A complete stack for robot development: training, simulation and on-board computing.
Adoption by humanoid start-ups and by established industrial robot makers.
Open models and tools that draw developers to the platform.
Financial resources no robotics company can match.
Challenges
Robotics remains a small part of revenue.
The outlook assumes no data center compute revenue from China.
Much of the humanoid robot market its tools target is still at an early stage.
Outlook
NVIDIA's bet is that robots will become a major computing market in the way data centers did. Its 2026 releases, from the GR00T reference humanoid to safety systems and open models, are aimed at making its platform the default starting point for anyone building a robot.
Current Catalogue Coverage
Catalogue checked on 15 October 2026: 3 associated product records. The links below are representative entries, rather than a claim that every historical model is currently available.
NVIDIA Robotics FAQ
Does NVIDIA make robots?
No. NVIDIA supplies computers, simulation software and AI models that other companies use to develop and run robots. It has published an open humanoid reference design.
What is NVIDIA Isaac?
Isaac is NVIDIA's open robotics development platform. It includes Isaac Sim for simulation, Isaac Lab for robot learning, Isaac ROS for perception and navigation, and Isaac GR00T for humanoid robots.
What is Jetson?
Jetson is NVIDIA's family of embedded AI computers for robots and edge devices. Jetson Thor is the high-end model for physical AI.
What is the three-computer approach?
NVIDIA's view that robotics needs one computer to train AI, one to simulate it and one inside the robot to run it.
Is NVIDIA publicly traded?
Yes, on Nasdaq under the symbol NVDA.
Who is the CEO of NVIDIA?
Jensen Huang, who co-founded the company in 1993.
Sources
NVIDIA: robotics
NVIDIA: financial results for second quarter fiscal 2027
Wikipedia: Nvidia
FANUC America: physical AI with NVIDIA technologies
KUKA: Automation 2.0 at NVIDIA GTC
