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.
Static HTML snapshot of the model record for crawlers and no-JS readers.
| Attribute | Value |
|---|---|
| Model | Matrix-Game 2.0 |
| Lab / Organization | Skywork |
| Category | Generative World Model |
| Subtype | Real-Time Streaming Interactive World Model |
| World Model Type | Open-source action-conditioned streaming video world model |
| Primary Domain | Interactive Gaming |
| Architecture | Few-step autoregressive diffusion world model |
| Modality | Image + Keyboard/Mouse Actions → Streaming Interactive Video |
| Training Method | Action-conditioned training and autoregressive diffusion distillation |
| Status | active |
| Year | 2025 |
Main editorial body preserved directly in static HTML.
Matrix-Game 2.0 is explicitly presented by its authors as an open-source, real-time, streaming interactive world model. It uses few-step autoregressive diffusion to generate long action-conditioned videos on the fly.
Matrix-Game 2.0 is an open-source action-conditioned streaming video world model developed by Skywork AI in 2025 for interactive gaming.
Short extractable facts for answer engines and no-JS readers.
| Signal | Value |
|---|---|
| Definition | Matrix-Game 2.0 is an open-source action-conditioned streaming video world model developed by Skywork AI in 2025 for interactive gaming. |
| Short Description | Skywork AI's open-source, real-time streaming interactive world model for action-conditioned video generation. |
| Benchmark Rows | 2 |
| FAQ Entries | 1 |
| Related Models | 4 |
| Related Guides | 0 |
| Related Research Topics | 0 |
| Last Updated | 2026-09-01 |
Key capabilities associated with this model.
Representative applications attached to this model record.
Balanced assessment surfaced in static HTML.
Primary references preserved in static HTML for citation extraction.
| Reference | Link |
|---|---|
| He et al., 2025. Matrix-Game 2.0: An Open-Source, Real-Time, and Streaming Interactive World Model. | Open source |
Nearby models linked from the current editorial record.
| Model | Category | World Model Type | Index v1.1 |
|---|---|---|---|
| OASIS | Generative World Model | Real-time playable world model | 66/100 |
| WHAM-RT | Generative World Model | Real-time generative world model for interactive media | N/A |
| Odyssey-2 | Foundation World Model | Causal autoregressive interactive video world model | N/A |
| MatrixGame3 | Generative World Model | Action-Conditioned Interactive Game World Model | N/A |
FAQ answers rendered directly into static HTML for extractable responses.
The paper explicitly defines Matrix-Game 2.0 as an open-source, real-time, streaming interactive world model.
Short extractable summary preserved directly in static HTML.
Editorial provenance and refresh policy preserved directly in static HTML.
Published by world-models.io editorial board.
Lead editor Tyler D. - Technical editor, methodology and benchmark analysis.
This model page synthesizes primary papers, official model pages, benchmark evidence, and related world-models.io context into a reference resource.
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: 2026-09-01.
Pages are refreshed when a new paper, benchmark, release, architecture update, or stronger primary source materially changes the answer a reader or AI system should retrieve.
Each page links back to relevant primary sources and keeps a stable canonical URL so readers can verify claims, trace context, and reference the most up-to-date version. See the editorial policy.
Primary model and lab sources embedded in static HTML.