Cosmos 3: Nvidia unveils a revolutionary AI that finally grasps the complexity of the real world

The artificial intelligence sector takes a decisive step forward with the launch of Cosmos 3 by Nvidia, a major breakthrough presented at the Taipei GTC. Unlike traditional AIs focused on specific tasks, this open-source, omnimodal model marks a revolution by grasping the complexity of the real world through a completely redesigned technology to simulate and understand physical interactions in varied environments. The applications potentially transformed by Cosmos 3 range from humanoid robots to autonomous driving, as well as intelligent systems capable of anticipating and interacting with their environment in unprecedented ways.

Equipped with a novel mixture-of-transformers architecture, Cosmos 3 offers native and simultaneous management of text, images, videos, sounds, and especially actions, granting it an advanced physical understanding surpassing previous models. This allows intelligent machines to learn not only to recognize what they perceive but also to interpret and act in complex, multimodal, and dynamic situations. This technological leap promises to seriously accelerate the development and training of physical AIs, reducing the classic cycles from several months to just a few days.

Understanding the innovation: how Cosmos 3 revolutionizes the modeling of the real world

Cosmos 3 stands out due to its ability to merge data from multiple sources and modalities to create a comprehensive representation of environments and physical interactions. This multidimensional approach relies on a deep learning system that analyzes a huge volume of multimodal data, including texts, images, videos, as well as ambient sounds and traces of human and robotic actions. By cultivating this diversity, the model develops a holistic understanding, opening the way to unprecedented applications.

For example, while most AIs only understand visual or textual content, Cosmos 3 uses traces of actions — such as robotic limb movements and object manipulations — to model the underlying physics of interactions. This ability goes beyond simple visual representation, integrating a behavioral dimension essential to mastering the complexity of the real world.

Take the case of collaborative robotics in a factory. Thanks to Cosmos 3, a robot can anticipate the movements of a human operator not only based on an image but also by understanding action sequences and intentions, thus improving the safety and efficiency of joint work. This innovation directly arises from Cosmos 3’s ability to simultaneously process and generate visual and action data, a progress reinforced by its open-source version that invites developers and industrialists to co-create and customize their solutions.

Versions adapted for all uses: Super, Nano and future Edge

Nvidia designed Cosmos 3 to meet varied needs through several versions, each possessing technical characteristics tailored to specific requirements in the physical AI universe. Two versions are already available: the “Super” version with 32 billion parameters, intended for applications requiring extreme precision, especially in advanced robotics and autonomous driving, and the “Nano” version, more compact with 8 billion parameters, prioritizing execution speed.

The Super version is designed for complex environments where mastering dynamics is critical. Imagine an industrial drone navigating changing environments with moving obstacles, or a surgical robot performing delicate interventions. The power and finesse of this version allow detailed modeling and precise interactions.

In parallel, the Nano version focuses on efficiency and reactivity, targeting embedded systems or less resource-hungry setups, yet capable of performing complex tasks quickly. Nvidia is also working on an “Edge” version, which promises to be usable directly on local devices without dependence on the cloud, thus opening a prospect for decentralized physical artificial intelligence that better respects latency and confidentiality constraints.

An exceptional multimodal model to understand and act simultaneously

At the heart of Cosmos 3’s performance lies training on a phenomenal mass of data: over 20 trillion tokens, nearly a billion images, and about 400 million real and generated videos. This multimodal corpus enables it to master not only texts and images but also videos, ambient sounds, and especially sequences of human and robotic actions. Thus, Cosmos 3 does not just perceive an environment; it understands it by integrating dynamics, representing a major turning point in 3D modeling and physical simulation.

This wealth condemns the old paradigm where each modality (text, image, video) was analyzed in isolation. Cosmos 3 achieves an unprecedented unification, creating a symbiosis between perception and action. For example, in a simulation for an autonomous vehicle, the model can generate not only the scene around the car but anticipate the trajectories of other users, detect surrounding sounds, and simulate various physical reactions such as hard braking, skidding, or evasions, significantly enhancing the realism and relevance of the training.

For Nvidia, this capacity strengthens the notion of “physical AI”: an intelligence reasoning in terms of objects, forces, movements, and interactions, not just static data. This opens the way to a new generation of applications where machines learn by simulation to master their environment before even facing it in reality.

Accelerating the development of autonomous systems through advanced simulation

The energy and time challenge linked to the learning phases of physical AIs is considerable, often hampering innovation. Thanks to Cosmos 3, Nvidia promises a radical reduction in training and evaluation times. Where previously several months were needed between data collection, training, and validation, today these steps can be compressed into a few days. This considerable gain is tied to the model’s advanced architecture, its multimodal self-learning capacities, and the richness of accessible databases.

The automotive sector is a striking example: while road tests for an autonomous vehicle are costly, lengthy, and often limited by variable real conditions, Cosmos 3 enables the simulation of diverse scenarios, including high-risk situations like collisions or unexpected obstacles. These scenarios are artificially generated but with remarkable physical fidelity, representing a true paradigm shift in AI preparation.

Another impacted field is industrial robotics. By virtually reproducing gestures, fine manipulations, or interactions with fragile or dangerous materials, machines can train in a secure dematerialized environment, limiting material costs and accident risks. This ability also facilitates the rapid customization of autonomous behaviors according to the specific constraints of the usage site.

Concrete applications of Cosmos 3 in robotics and autonomous driving

In robotics, Cosmos 3 enables machines to better apprehend gestures, from manipulating complex objects to navigating dynamic environments. For example, a service robot can adapt its movements to coordinate with humans and avoid collisions by modeling interlocutors’ trajectories and intentions in real time.

In autonomous driving, the model plays a crucial role in integrated understanding of road elements, pedestrian and other vehicle behaviors, environmental conditions, and emergency situations. Cosmos 3’s physical precision ensures effective anticipation of reactions, adaptive trajectory management, and safe decision-making.

This capacity is supported by the model’s ability to generate detailed action data. The rotation angles of a robot’s joints or the movements of a mechanical gripper are simulated with finesse, enabling algorithms to be trained to move fluidly and coordinately, thus reproducing tasks hitherto difficult to realize without intensive training in real conditions.

Collaboration and ecosystem: openness at the heart of Nvidia’s innovation

One of Cosmos 3’s major strengths lies in its open-source nature, which facilitates adoption and collaboration with the industrial and academic community. Following the Nemotron families’ lineage, Nvidia invites manufacturers, researchers, and developers to customize, optimize, and extend the model according to their specific needs. This sharing strategy accelerates research and implementation of physical AI technologies across various sectors.

To support this dynamic, Nvidia has partnered with an extensive network of technological partners such as Agile Robots, Black Forest Labs, and Runway. These collaborations strengthen the diversity of explored use cases and enable easier integration of Cosmos tools into production chains and innovation platforms.

This openness is also strategic from an industrial perspective, as it guarantees fine adaptability to business, technical, and regulatory constraints of different domains. The Cosmos3 ecosystem thus becomes a crucible of sustainable innovation, where every stakeholder can contribute to refining physical modulation, simulation, or the action/perception interface.

Key advantages list of Cosmos 3 for developers and industrialists

• Integrated and multimodal modeling: native management of text, images, videos, sounds, and actions for holistic understanding.
• Open source: free access to models to facilitate adaptation to specific needs and collaboration.
• Reduced training times: cycles go from several months to a few days, accelerating time to market.
• Specialized versions: Super for high precision, Nano for speed, and soon Edge for local embedded systems.
• Simulation of rare or dangerous scenarios: ability to generate and train situations difficult to reproduce in real conditions.
• Diverse applications: advanced robotics, autonomous vehicles, drones, collaborative systems in industry.
• Strategic partnerships: extensive network facilitating dissemination and innovation in the ecosystem.

Comparative table of main characteristics of Cosmos 3

Aspect	Super Version	Nano Version	Edge Version (upcoming)
Number of parameters	32 billion	8 billion	Adapted to local devices
Processing speed	Optimized for precision	Optimized for speed	Optimized for low latency
Data types	Text, images, videos, sounds, actions	Text, images, videos, sounds, actions	Text, images, videos, sounds, actions
Main usages	Robotics, autonomous driving	Fast embedded systems	Local decentralized AI
Access	Open source	Open source	Coming soon

What is Nvidia’s Cosmos 3?

Cosmos 3 is a revolutionary open-source artificial intelligence model designed to understand and simulate complex physical interactions of the real world by natively processing text, images, videos, sounds, and actions.

What are the main advantages of Cosmos 3?

It enables complete multimodal modeling, drastically accelerates AI training, offers versions adapted to various uses, and facilitates collaborative creation thanks to its open-source nature.

How does Cosmos 3 contribute to robotics?

The model finely simulates the movements and physical interactions of robots, allowing better preparation of their actions in real environments through precise and comprehensive simulations.

Can Cosmos 3 be used without an internet connection?

An Edge version, intended to be used directly on local devices, is under development to offer this possibility while ensuring performance and low latency.

What types of data are used to train Cosmos 3?

The model has been trained on a huge multimodal database including millions of images, real and synthetic videos, audio data, and traces of human and robotic actions.