Main comparison summary preserved directly in static HTML.
V-JEPA 2 dramatically scales up Meta FAIR's self-supervised video world model, achieving state-of-the-art visual understanding and zero-shot robot control, capabilities V-JEPA didn't demonstrate.
Primary editorial conclusion preserved for non-JS crawlers and readers.
V-JEPA 2 is a major leap: it proves the JEPA paradigm works at foundation scale, beating supervised models on visual understanding while enabling zero-shot robotics. V-JEPA was the research proof; V-JEPA 2 is the practical world model.
Extractable difference list generated from the comparison table.
Static decision guidance for no-JS readers.
Choose V-JEPA 2 when its capabilities best match your research or deployment requirements.
Choose V-JEPA when its capabilities best match your research or deployment requirements.
V-JEPA 2 is a major leap: it proves the JEPA paradigm works at foundation scale, beating supervised models on visual understanding while enabling zero-shot robotics. V-JEPA was the research proof; V-JEPA 2 is the practical world model.
| Dimension | V-JEPA 2 | V-JEPA |
|---|---|---|
| Visual Understanding | State-of-the-art (surpasses supervised models) | Strong but below supervised baselines |
| Robot Control | Zero-shot robot planning in unseen environments | Not demonstrated |
| Physical Reasoning | New PhyBench benchmark (89.2%) | Not evaluated |
| Scale | Foundation-scale training | Smaller scale |
| Open Source | Fully open-source | Open-source |
| Year | 2025 | 2024 |
High-level scoring context for the models referenced in this comparison.
| Model | Category | Index v1.1 | Confidence |
|---|---|---|---|
| V-JEPA 2 | Self-Supervised World Model | 87/100 | medium |
| V-JEPA | Self-Supervised World Model | 70/100 | medium |
| I-JEPA | Self-Supervised World Model | 61/100 | medium |
| LeWorldModel | Self-Supervised World Model | 78/100 | medium |
FAQ answers rendered directly into static HTML for extractable responses.
Yes. Like V-JEPA, V-JEPA 2 predicts in latent space rather than reconstructing pixels, following LeCun's JEPA philosophy.
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 Bernard Grenat.
This comparison page publishes a direct answer, explicit trade-offs, and source-backed evidence that can be validated against primary materials.
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: 2026-06-21.
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 papers and official sources for the models discussed on this comparison page.