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| Attribute | Value |
|---|---|
| Model | 1X World Model |
| Lab / Organization | 1X |
| Category | Foundation World Model |
| Subtype | Humanoid Robot Video World Model |
| World Model Type | Physics-grounded action-conditioned video world model |
| Primary Domain | Humanoid Robotics |
| Architecture | Physics-grounded action-conditioned video model for humanoid control |
| Modality | Robot Video + Actions -> Future Observations |
| Training Method | Embodied video prediction grounded in robot interactions and failure-aware learning |
| Status | active |
| Year | 2025 |
| Performance Index | 79/100 (medium confidence, v1.1) |
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The 1X World Model is a video world model used inside 1X's humanoid robotics stack for NEO. According to 1X, it predicts the outcomes of the robot's actions before execution in the real world and now serves as NEO's cognitive core for generalizing to previously unseen tasks. Its emphasis is practical embodied deployment: using a world model as a decision substrate for real household robotics rather than as a benchmark-only research artifact.
1X World Model is a physics-grounded action-conditioned video world model developed by 1X in 2025 for humanoid robotics.
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| Signal | Value |
|---|---|
| Definition | 1X World Model is a physics-grounded action-conditioned video world model developed by 1X in 2025 for humanoid robotics. |
| Short Description | 1X's physics-grounded video world model for anticipating the outcomes of NEO's actions and supporting generalization to unseen household tasks. |
| Benchmark Rows | 0 |
| FAQ Entries | 1 |
| Related Models | 3 |
| Related Guides | 0 |
| Related Research Topics | 0 |
| Last Updated | 2026-06-12 |
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| Reference | Link |
|---|---|
| 1X, 2025-2026. 1X World Model updates for NEO. | Open source |
Nearby models linked from the current editorial record.
| Model | Category | World Model Type | Index v1.1 |
|---|---|---|---|
| AMI World Model | Foundation World Model | Multimodal generative world model | 38/100 |
| RT-2 | Foundation World Model | Web-knowledge transfer model for robotics | 72/100 |
| V-JEPA 2 | Self-Supervised World Model | Joint-embedding predictive world model for video understanding and robot planning | 87/100 |
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1X presents the model as a physics-grounded predictor for NEO's actions, allowing the robot stack to anticipate consequences before acting in the real world.
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Published by world-models.io editorial board.
Lead editor Tyler D. - Technical editor, methodology and benchmark analysis.
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