A world model is an AI system that learns a predictive representation of how an environment changes over time. It can use observations, actions, or language to estimate future states and possible outcomes before an agent acts. World models support planning in model-based reinforcement learning, robotics, embodied AI, autonomous driving, and interactive simulation. This site catalogs these systems with model records, research papers, benchmark context, and source links. Start with the world models database, compare systems on the leaderboard, or read the Performance Index methodology.
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A learned generative model that produces realistic, controllable simulations of environments and their dynamics. OpenAI describes Sora as a world simulator; the term emphasizes systems that aim to replace or augment hand-built simulators.
World Simulator is a glossary concept in the concepts layer of the world models knowledge base.
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| Attribute | Value |
|---|---|
| Term | World Simulator |
| Category | Concepts |
| Definition | A learned generative model that produces realistic, controllable simulations of environments and their dynamics. OpenAI describes Sora as a world simulator; the term emphasizes systems that aim to replace or augment hand-built simulators. |
| Related Models | 3 |
| Related Research | 2 |
| Model | Lab | Category |
|---|---|---|
| Sora | OpenAI | Generative World Model |
| NVIDIA Cosmos | NVIDIA | Foundation World Model |
| UniSim | Google DeepMind | Generative World Model |
| Topic | Summary |
|---|---|
| AI Simulation Systems | How AI simulation systems and learned simulators reduce the reality gap and extend or replace hand-crafted engines for autonomous agents. |
| Foundation World Models | How foundation world models such as Cosmos and Genie 2 bring large-scale learned simulation to robotics, autonomous driving, and physical AI. |
| Term | Category | Definition |
|---|---|---|
| Foundation Model | Paradigms | A large-scale model trained on broad data that can be adapted to many downstream tasks. Foundation world models (like NVIDIA Cosmos and Genie 2) learn general-purpose representations of world dynamics, analogous to how GPT models serve as foundations for language tasks. |
| Action Conditioning | Architecture | A property of a world model whose predictions of future states depend explicitly on the action taken by the agent. Action-conditioned models support interactive simulation and planning, distinguishing true world models from passive video generators. |
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Published by world-models.io editorial board.
Lead editor Bernard Grenat.
This glossary page publishes stable definitions linked to related models, research topics, and primary-source context.
Each editorial page is assembled from primary sources, normalized into extractable summaries, checked for factual drift, and reviewed before publication or major refreshes. Last reviewed: 2026-09-27.
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