NVIDIA Isaac Sim, Omniverse, and Cosmos – The Robotics & AI Simulation Ecosystem Explained
- Adrian Araya
- Jun 6
- 10 min read
NVIDIA has developed a robust ecosystem of tools for robotics and AI workflows, including NVIDIA Isaac Sim, NVIDIA Omniverse, and the new NVIDIA Cosmos. Each serves a distinct but complementary role: Omniverse provides the underlying platform for 3D simulation and collaboration, Isaac Sim focuses on robotics simulation and testing, and Cosmos leverages generative AI to accelerate synthetic data generation and world modeling. In this post, we’ll demystify these three frameworks – explaining their purpose, how they coexist within NVIDIA’s ecosystem, their use cases and differences, as well as system requirements, installation notes, and when to use each.
NVIDIA Omniverse: The Foundation for 3D Simulation and Collaboration
NVIDIA Omniverse is the foundational platform that ties everything together. What is Omniverse? At its core, NVIDIA Omniverse is a modular development platform of SDKs, APIs and microservices for building 3D applications and services powered by Universal Scene Description (OpenUSD) and NVIDIA RTX. In simpler terms, Omniverse provides the infrastructure for real-time, physically accurate simulation and 3D content creation. It enables multiple tools and users to collaborate on shared virtual worlds.
Omniverse’s key features include support for OpenUSD, which lets it integrate 3D assets from various content creation tools into a single scene. It also has a powerful multi-GPU capable RTX renderer for real-time ray tracing and physics (via NVIDIA PhysX), allowing high-fidelity visualizations and true-to-life physics simulation. With Omniverse’s collaboration servers (Nucleus) and connectors, designers, engineers, and developers can work together on complex simulations, linking tools like CAD software, game engines, and custom applications into one interoperable environment. This makes Omniverse popular not just for robotics, but for digital twins, industrial simulation, visual effects, and design collaboration – anywhere real-time 3D simulation and teamwork are needed.
System Requirements
Omniverse requires an NVIDIA RTX GPU (8GB+ VRAM recommended), a multi-core CPU (4+ cores), and 16–32GB of RAM for complex scenes. It supports both Windows and Linux. For optimal performance, an RTX 3000-series or higher GPU is recommended. More details in the official NVIDIA Omniverse documentation.
Installation
Getting started with Omniverse is straightforward. You can access Omniverse components via NVIDIA NGC (NVIDIA’s cloud container registry) or use the Kit App Template from GitHub to build custom OpenUSD-based desktop or cloud applications using the Omniverse Kit SDK. Since this software is resource-intensive, it’s often best installed on high-performance machines such as GPU-equipped servers, which provide better performance for large-scale simulations. If you're interested in setting it up on a server and accessing the client remotely via a browser, don’t miss our upcoming guide: Installing Omniverse and Isaac Sim on a GPU Server for Remote Access.
Licensing
Omniverse is free for individual developers and enthusiasts, offering full access to client apps and tools for single-user use. For teams needing multi-user collaboration, Nucleus server support, and enterprise-grade services, Omniverse Enterprise licenses are available on a subscription basis. You can start for free and scale up as your project or organization grows.
NVIDIA Isaac Sim: Simulating Robots in Physically Accurate Virtual Worlds
If Omniverse is the foundation, NVIDIA Isaac Sim is one of its flagship applications built on top of that foundation. NVIDIA Isaac Sim is a reference application built on NVIDIA Omniverse that enables developers to simulate and test AI-driven robotics solutions in physically based virtual environments. In practice, Isaac Sim provides a highly realistic robotics simulation environment: think of it as a virtual robotics lab where you can drop in robot models, sensors, and environments to see how your robots would behave in the real world – all before you ever build or deploy a physical robot.
Isaac Sim’s purpose is to accelerate robotics development by providing tools for simulation-first testing. Instead of risking expensive hardware or lengthy field testing, developers and engineers can train robot AI models, test algorithms, and generate training data in simulation. Key features of Isaac Sim include:
Accurate Physics and Dynamics: Isaac Sim uses NVIDIA PhysX under the hood for realistic physics simulation, so robots in simulation respond to forces and environments just as they would physically.
Sensor Simulation: It can simulate a robot’s sensors with high fidelity providing virtual “ground truth” data. This is invaluable for testing perception algorithms.
Pre-built Robot Models and Assets: Isaac Sim comes with a rich library of SimReady assets and popular robot models. Out-of-the-box, you get ready-to-use models of manipulators, mobile robots, humanoids, and more, all with proper physical properties. There are also 1,000+ 3D assets to build virtual test environments. This jump-starts simulation setup since you don’t have to model everything from scratch.
AI & Training Tools: Isaac Sim integrates with robotics AI workflows. It supports generating synthetic data for training perception models (using Omniverse Replicator), and it ties into reinforcement learning and robotics training frameworks. In fact, NVIDIA has introduced Isaac Gym/Isaac Lab – frameworks for robot learning – that leverage Isaac Sim for training robot control policies in simulation.
With Isaac Sim, you can simulate scenarios ranging from a single robot arm picking up objects on a factory line, to a fleet of delivery robots navigating a virtual warehouse. You can iterate on robot design, test control software, and perform regression testing entirely in a virtual world. By the time you deploy to the real world, your robot is much more likely to succeed because it’s been vetted in countless virtual experiments.
System Requirements
Isaac Sim requires a dedicated NVIDIA RTX GPU (RTX 3070 or higher recommended), a powerful multi-core CPU, and at least 32 GB of RAM to handle physics, sensors, and AI workloads. For complex simulations, RTX 40-series or professional GPUs with 16–48 GB VRAM are ideal. Learn more in the official system requirements.
Installation
Isaac Sim can be installed via a Docker container from NVIDIA NGC, ideal for headless or cloud environments, or as a Python package via pip for script-based workflows without the full GUI. After installation, you’ll have access to examples, tutorials, and documentation to help you start building and connecting simulation environments. For more details, see the official NVIDIA guide. If you're planning to run Isaac Sim on a GPU server and access it remotely through a browser, keep an eye out for our upcoming blog: Installing Omniverse and Isaac Sim on a GPU Server for Remote Access.
Licensing
Isaac Sim is free to use for developers with an NVIDIA account and falls under the Omniverse individual license. No separate purchase is needed, making it ideal for research and development. For enterprise support or multi-user collaboration, Omniverse Enterprise may be required.
Isaac Sim & Isaac Lab
Notably, Isaac Sim is extensible and can be combined with other NVIDIA AI tools. NVIDIA has introduced Isaac Lab, an open-source framework built on Isaac Sim for robot learning (training robot policies via reinforcement learning, imitation learning, etc.).
With Isaac Lab, developers can train robots entirely in simulation using advanced AI techniques such as reinforcement and imitation learning. If you're looking to build intelligent robotic behaviors with Isaac Sim, don’t miss our upcoming guide: Getting Started with Isaac Lab: Train Your Robots in NVIDIA Isaac Sim (Coming soon).
NVIDIA Cosmos: Generative AI for World Modeling and Synthetic Data
The newest piece of the puzzle is NVIDIA Cosmos. While Omniverse and Isaac Sim handle simulation and rendering, Cosmos is all about generative AI and world models to supercharge your robotics and AI workflows. NVIDIA Cosmos is described as a platform comprising state-of-the-art generative world foundation models, advanced tokenizers, guardrails, and an accelerated data processing pipeline built to accelerate the development of physical AI systems like autonomous vehicles and robots. In essence, Cosmos brings the power of AI foundation models to simulated worlds and robotics. It helps create richer, more varied, and more realistic data and scenarios for training AI, which is incredibly useful for robotics developers facing data scarcity or needing to test edge cases.
While Isaac Sim focuses on producing structured simulation data, NVIDIA Cosmos takes it a step further by using generative AI to enhance and expand that data. Cosmos acts as a bridge between simulation and reality, turning simulated outputs into photorealistic images or generating entirely new virtual scenes from simple prompts.
Cosmos includes two key components:
Cosmos Predict generates 3D environments or motion sequences from text or image prompts, enabling quick creation of diverse, dynamic scenarios.
Cosmos Transfer converts simulation outputs—such as segmentation maps or depth data—into highly realistic images or videos, perfect for synthetic data generation.
These tools make Cosmos especially powerful for scaling data creation, testing AI under diverse conditions, and accelerating model training. Rather than replacing Isaac Sim or Omniverse, Cosmos complements them as part of an integrated pipeline: simulate with Isaac Sim, enhance and diversify with Cosmos, and train more capable AI systems.
In practice, Cosmos helps robotics teams save time by automating the generation of high-quality training data across a variety of environments, lighting conditions, and layouts — multiplying the value of each simulation run.
System Requirements
NVIDIA Cosmos requires significant GPU power, ideally using data-center class GPUs like the A100 or H100. While smaller models may run on high-end desktop GPUs, larger ones demand multi-GPU setups or cloud solutions like NVIDIA DGX. Cosmos is optimized for scalable AI workloads, making robust hardware essential for effective use.
Installation & Availability
"Note: If you want to try Cosmos without installing it, you can explore some demos published by NVIDIA here."
Cosmos is not a single monolithic software to install like Isaac Sim; instead, it is a collection of AI models and tools. NVIDIA has made Cosmos’s core models available to developers openly. You can download pre-trained Cosmos world foundation models from NVIDIA NGC or Hugging Face (NVIDIA has released model files and checkpoints there). For example, models like Cosmos-Predict1 and Cosmos-Transfer1 can be obtained and run via standard machine learning frameworks. NVIDIA also provides documentation and sample code (e.g., on GitHub) to help developers integrate Cosmos into their workflows. To get started:
Visit the NVIDIA Developer page for Cosmos and download the model checkpoints you need (or use huggingface-cli/NGC CLI to pull them).
Ensure you have the required runtime (typically PyTorch and NVIDIA CUDA drivers for running the models).
Follow NVIDIA’s examples to run inference with the model – feeding in your simulation data and getting AI-generated outputs. (There are detailed guides, such as “Scale Synthetic Data and Physical AI Reasoning With Cosmos WFMs”, that walk through using Cosmos models).
Because Cosmos is relatively new (launched in late 2024/early 2025), expect rapid evolutions. NVIDIA’s ecosystem might incorporate Cosmos more tightly into tools like Isaac Sim over time. For now, developers can experiment with Cosmos models as standalone AI components that complement their simulation.
Licensing
The licensing model for Cosmos is developer-friendly – the models are provided openly (free), though they come with NVIDIA’s terms of use (and of course require NVIDIA GPUs to run well). This openness means you can start using Cosmos models in your projects today without special purchases, accelerating your AI training pipeline with synthetic data.
Use Cases Recap
Use Cosmos when you need to massively scale or enhance your data. If your robot’s AI needs to see millions of diverse scenarios, Cosmos can generate those scenarios far faster than manual modeling or real-world collection. If you need highly realistic sensor data (camera footage that looks like real life), Cosmos can produce it from simulation outputs. On the other hand, if you’re at the stage of developing the robot’s control logic or testing a specific algorithm, you’ll be inside Isaac Sim (with Omniverse) for the physics accuracy and interactive simulation. Cosmos shines in the data preparation and AI model training phase, while Isaac Sim + Omniverse shine in the simulation and testing phase. Together, they ensure the robot’s AI is both well-trained and well-tested.
We will delve deeper into leveraging Cosmos for AI training in an upcoming blog post. Stay tuned for Accelerating AI Training Workflows with NVIDIA Cosmos: From Synthetic Data to 3D Video, where we’ll walk through an example of using Cosmos to generate training data and even 3D video outputs for an AI workflow (link in the references). Accelerating AI Training Workflows with NVIDIA Cosmos: From Synthetic Data to 3D Video.
Comparing NVIDIA Isaac Sim, Omniverse, and Cosmos
Now that we’ve introduced each framework, let’s compare NVIDIA Isaac Sim vs Omniverse vs Cosmos and clarify when to use each. It’s important to note that these tools are complementary rather than strictly alternatives – they often work best in tandem. However, they do have different focuses and strengths within the NVIDIA ecosystem:
NVIDIA Omniverse is the platform and infrastructure. It’s the base layer that provides the 3D world representation (OpenUSD), rendering, physics, and connectivity. Use Omniverse when you need to build or integrate complex 3D pipelines or collaborate across teams. It’s the general-purpose toolbox for simulation and is not limited to robotics.
NVIDIA Isaac Sim is a specific application (built on Omniverse) tailored for robotics simulation. It uses Omniverse’s capabilities but adds robotics-specific conveniences (robot models, ROS support, sensor models). Use Isaac Sim when your goal is to develop or test a robotics system in a virtual environment – for example, tuning a robot’s navigation software, generating labeled images from a robot’s camera for training, or validating a robot design under various conditions.
NVIDIA Cosmos is an AI model suite that operates alongside these. It doesn’t do physics simulation itself; instead, it leverages AI to enhance or generate data and scenarios. Use Cosmos when you need to create synthetic data at scale, increase realism, or incorporate AI-based world generation or reasoning into your workflow. It’s particularly useful post-simulation: after you have your simulation results, or to generate environment content before simulation.
Omniverse, Isaac Sim, and Cosmos each target different layers of the robotics and AI workflow. Omniverse is the general platform (broad and flexible), Isaac Sim is the domain-specific simulation tool (deep in robotics needs), and Cosmos is the AI data/model toolkit (cutting-edge generative tech). Depending on your project stage or focus, you might lean more on one than the others:
If you are setting up a collaborative simulation pipeline or need to integrate with multiple content creation tools, start with Omniverse.
If you are primarily concerned with robotics algorithms, sensor data, and testing robot behavior, dive into Isaac Sim (which implicitly uses Omniverse in the background).
If you find yourself needing more data, more realism, or automated scenario generation to train your AI, incorporate Cosmos into your workflow after or alongside simulation.
Many projects will ultimately use all three: for example, a robotics team might build their virtual lab in Omniverse, develop and test their robots in Isaac Sim, then employ Cosmos to generate additional training data and validate the AI under countless variations. The coexistence of these frameworks in NVIDIA’s ecosystem means you don’t have to choose one over the other – instead, you compose them as needed. NVIDIA has designed them to interoperate (Isaac Sim running on Omniverse, Cosmos reading/writing Omniverse data), which creates a powerful virtuous cycle for developing smarter robots faster.
Ready to Bring Simulation and AI into Your Workflow? Contact Us
If you're exploring how to use NVIDIA Isaac Sim, Omniverse, or Cosmos to enhance your robotics or AI workflows, we’d love to hear from you. Whether you’re starting a new project or scaling an existing one, we can help you navigate the tools and set up an efficient development pipeline.
Reach out at support@ridgerun.ai — let’s build something together.
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