repo_id string | organization string | model_name string | world_model_type string | architecture_family string | modalities list | domain list | action_conditioned bool | interactive bool | prediction_target list | planning_support bool | control_support bool | robotics bool | physical_ai bool | spatial_reasoning bool | simulation bool | synthetic_data bool | parameter_count_b float64 | weights_available bool | access_status string | license string | commercial_use string | base_model string | paper_id string | verification_status string | last_verified timestamp[s] | source_urls list | notes string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
nvidia/Cosmos-Predict2-2B-Video2World | nvidia | Cosmos-Predict2-2B-Video2World | world foundation model | latent video diffusion transformer | [
"text",
"image",
"video"
] | [
"physical-ai",
"world-generation"
] | false | false | [
"future video frames",
"world states"
] | false | false | true | true | true | true | true | 2 | true | gated | nvidia-open-model-license | permitted_by_license | null | null | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/nvidia/Cosmos-Predict2-2B-Video2World"
] | NVIDIA describes Cosmos-Predict2 as a world foundation model family for physics-aware world generation and Physical AI. |
nvidia/Cosmos-Predict2-14B-Video2World | nvidia | Cosmos-Predict2-14B-Video2World | world foundation model | latent video diffusion transformer | [
"text",
"image",
"video"
] | [
"physical-ai",
"world-generation"
] | false | false | [
"future video frames",
"world states"
] | false | false | true | true | true | true | true | 14 | true | gated | nvidia-open-model-license | permitted_by_license | null | null | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/nvidia/Cosmos-Predict2-14B-Video2World"
] | Larger Cosmos Predict-2 Video2World checkpoint for higher-fidelity world generation. |
nvidia/Cosmos-Policy-LIBERO-Predict2-2B | nvidia | Cosmos-Policy-LIBERO-Predict2-2B | world action model / visuomotor policy | latent video diffusion transformer | [
"text",
"multi-view image",
"proprioception",
"action"
] | [
"robotics",
"manipulation",
"simulation"
] | true | true | [
"actions",
"future images",
"future proprioception",
"value"
] | true | true | true | true | true | true | false | 2 | true | public | nvidia-one-way-noncommercial-license-nsclv1 | not_permitted_without_custom_license | nvidia/Cosmos-Predict2-2B-Video2World | 2601.16163 | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/nvidia/Cosmos-Policy-LIBERO-Predict2-2B"
] | Jointly predicts actions, future states and values for LIBERO robot manipulation tasks. |
nvidia/Cosmos-Policy-RoboCasa-Predict2-2B | nvidia | Cosmos-Policy-RoboCasa-Predict2-2B | world action model / visuomotor policy | latent video diffusion transformer | [
"text",
"multi-view image",
"proprioception",
"action"
] | [
"robotics",
"kitchen-manipulation",
"simulation"
] | true | true | [
"actions",
"future images",
"future proprioception",
"value"
] | true | true | true | true | true | true | false | 2 | true | public | nvidia-one-way-noncommercial-license-nsclv1 | not_permitted_without_custom_license | nvidia/Cosmos-Predict2-2B-Video2World | 2601.16163 | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/nvidia/Cosmos-Policy-RoboCasa-Predict2-2B"
] | Cosmos Policy checkpoint for RoboCasa kitchen manipulation, predicting actions, future state and value. |
nvidia/Cosmos-Policy-ALOHA-Planning-Model-Predict2-2B | nvidia | Cosmos-Policy-ALOHA-Planning-Model-Predict2-2B | planning world model | latent video diffusion transformer | [
"text",
"multi-view image",
"proprioception",
"action"
] | [
"robotics",
"bimanual-manipulation",
"real-world"
] | true | true | [
"future images",
"future proprioception",
"value"
] | true | true | true | true | true | true | false | 2 | true | public | nvidia-one-way-noncommercial-license-nsclv1 | not_permitted_without_custom_license | nvidia/Cosmos-Policy-ALOHA-Predict2-2B | 2601.16163 | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/nvidia/Cosmos-Policy-ALOHA-Planning-Model-Predict2-2B"
] | Refined world-model and value checkpoint for best-of-N model-based planning on real ALOHA manipulation tasks. |
nvidia/Cosmos-H-Dreams | nvidia | Cosmos-H-Dreams | interactive world model | causal latent video diffusion transformer | [
"image",
"robot kinematics",
"video"
] | [
"surgical-robotics",
"interactive-simulation",
"healthcare"
] | true | true | [
"future video frames"
] | true | true | true | true | true | true | true | 2 | true | public | nvidia-open-model-license | permitted_by_license | nvidia/Cosmos-Predict2.5-2B-Video2World | 2511.00062 | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/nvidia/Cosmos-H-Dreams"
] | Real-time action-conditioned surgical world model for interactive simulation and policy evaluation. |
sii-research/tau-0-wm | sii-research | tau-0-wm | unified video-action world model | video diffusion backbone | [
"multi-view video",
"language",
"robot state",
"action"
] | [
"robotics",
"manipulation",
"real-world"
] | true | true | [
"future visual latents",
"continuous actions",
"task-progress value"
] | true | true | true | true | true | true | false | null | true | public | apache-2.0 | permitted_by_license | Wan-2.2 video diffusion backbone | 2606.01027 | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/sii-research/tau-0-wm",
"https://huggingface.co/papers/2606.01027"
] | Unified Video Action Model plus action-conditioned simulator for robotic manipulation. |
Fleurrr/A2World-World-Model | Fleurrr | A2World-World-Model | action-conditioned video world model | multi-view diffusion world model | [
"multi-view image",
"robot action",
"video"
] | [
"robotics",
"manipulation",
"simulation"
] | true | false | [
"future robot observations",
"video rollout"
] | true | false | true | true | true | true | false | 2 | true | public | nvidia-open-model-license | subject_to_nvidia_open_model_license | nvidia/Cosmos-Predict2-2B-Video2World | 2606.29501 | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/Fleurrr/A2World-World-Model",
"https://huggingface.co/papers/2606.29501"
] | Predicts future robot observations from initial camera observations and a 20-step action chunk; supports autoregressive rollout. |
BLM-Lab/Boundless-World-Model | BLM-Lab | Boundless-World-Model | action-conditioned video world model | DiT + action encoder | [
"video",
"robot action"
] | [
"robotics",
"manipulation"
] | true | false | [
"future video frames"
] | false | false | true | true | true | true | false | 5 | true | public | not_documented_on_hf_model_card | unknown | Wan-AI/Wan2.2-TI2V-5B | null | verified_with_license_gap | 2026-09-24T00:00:00 | [
"https://huggingface.co/BLM-Lab/Boundless-World-Model"
] | Physically consistent action-conditioned video world model; license was not displayed on the Hugging Face model card at verification time. |
facebook/vjepa2-vitg-fpc64-384 | facebook | V-JEPA 2 ViT-g 384 | predictive representation / world-model backbone | joint-embedding predictive architecture | [
"video",
"image"
] | [
"video-understanding",
"physical-world-representation"
] | false | false | [
"latent video representations"
] | false | false | true | true | true | false | false | 1 | true | public | apache-2.0 | permitted_by_license | null | 2506.09985 | verified | 2026-09-24T00:00:00 | [
"https://huggingface.co/facebook/vjepa2-vitg-fpc64-384",
"https://huggingface.co/papers/2506.09985"
] | Base V-JEPA 2 checkpoint is action-free; the associated work post-trains V-JEPA 2-AC as an action-conditioned world model for robotic planning. |
World Model Registry
World Model Registry is a curated, source-linked dataset for mapping the world-model ecosystem across Physical AI, robotics, learned simulation, planning and predictive representations.
Version: 0.1.0
Last verified: 2026-09-24
Initial records: 10
Why this registry exists
The label world model now covers several technical patterns:
World Foundation Model
World Action Model
Interactive World Model
Planning World Model
Action-Conditioned Video World Model
Predictive Representation / World-Model Backbone
The registry makes those differences explicit instead of placing every model in one undifferentiated list.
Core fields
repo_idorganizationmodel_nameworld_model_typearchitecture_familymodalitiesdomainaction_conditionedinteractiveprediction_targetplanning_supportcontrol_supportroboticsphysical_aispatial_reasoningsimulationsynthetic_dataparameter_count_bweights_availableaccess_statuslicensecommercial_usebase_modelpaper_idverification_statuslast_verifiedsource_urlsnotes
Classification principles
USE THE MODEL CARD
LINK THE SOURCE
SEPARATE DOCUMENTED FACTS FROM INTERPRETATION
MARK GAPS INSTEAD OF GUESSING
A model is only marked action-conditioned, interactive, planning-capable or control-capable when its documentation supports that property.
Initial scope
The first release includes examples of:
- NVIDIA Cosmos Predict-2 world foundation models
- Cosmos Policy world-action / planning models
- Cosmos-H-Dreams interactive simulation
- τ₀-WM unified video-action world modeling
- A2World action-conditioned robotics simulation
- Boundless World Model
- V-JEPA 2 as a predictive representation / world-model backbone
Important taxonomy note
Not every predictive video model is a full world model.
The registry therefore distinguishes between:
- full action-conditioned world models
- world foundation models
- interactive simulators
- planning models
- predictive representation backbones
This is particularly important for V-JEPA 2: the base checkpoint is action-free, while the associated research post-trains V-JEPA 2-AC as an action-conditioned world model for robotic planning.
Intended uses
This dataset can support:
- model discovery
- world-model landscape mapping
- registry interfaces
- comparison tools
- robotics research
- Physical AI research
- planning research
- simulation research
- taxonomy analysis
Limitations
This is an intentionally small first release.
It is not:
- a complete list of all world models
- a benchmark
- a model-quality ranking
- a legal opinion
- a safety certification
Data architecture
WORLD MODELS ORGANIZATION
↓
WORLD MODEL REGISTRY DATASET
↓
STRUCTURED TAXONOMY + VERIFIED METADATA
↓
WORLD MODEL REGISTRY SPACE
↓
SEARCH · FILTER · DETAILS · COMPARE
Collaboration & Partnerships
The World Models organization is open to collaboration with world-model research teams, robotics companies, Physical AI companies, simulation platforms, research labs, universities and infrastructure providers.
Relevant collaboration areas include:
- verified registry contributions
- taxonomy
- world-action models
- interactive world models
- Physical AI
- robotics
- planning
- control
- simulation
- benchmarks
- dataset integration
Collaboration: agenten@magenta.de
Independence
World Models is an independent Hugging Face community organization.
This registry is not an official registry of Hugging Face, NVIDIA, Meta, SII, BLM Lab or any other model developer listed here.
License
The original registry structure, curation and documentation are released under Apache-2.0.
This does not relicense any listed model. Each model remains subject to its own license and terms.
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