whatmodel.sh / video / Cosmos-1.0-Autoregressive-5B-Video2World
Cosmos-1.0-Autoregressive-5B-Video2World
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Cosmos-1.0-Autoregressive-5B-Video2World is an open-weights video model from NVIDIA, released January 2025. Its published size is 5B parameters. Licence: nvidia-open-model.
Catalogue identity notes
Comparison-only, proposed so the Cosmos paper's 3D-consistency table counts. The paper's 'Cosmos-Predict1-5B-Video2World' is the Video2World derivative of the 4B autoregressive base (Table 10); weights nvidia/Cosmos-1.0-Autoregressive-5B-Video2World (sha f01be8aaaa18704d1fec4e917992aec1074c94a3, created 2025-01-07).
$ how it compares
The video models ranked either side of Cosmos-1.0-Autoregressive-5B-Video2World, out of 139 with a score, then more from NVIDIA.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 122 |  LaVie (base T2V) | 32±2 | local | ||
| 123 |  LTX-Video 0.9 (2B) | 32±3 | local | ||
| 124 | Cosmos-1.0-Autoregressive-5B-Video2World | 31±5 | comparison only | ||
| 125 |  NOVA-0.6B T2V | 29±3 | local | ||
| 126 | ZeroScope v2 576w | 27±3 | local | ||
| more from NVIDIA | |||||
| 38 | Cosmos3-Super | 58±4 | local | ||
| 60 | Cosmos3-Nano | 52±3 | local | ||
| 72 | Cosmos-1.0-Diffusion-7B-Video2World | 49±5 | comparison only | ||
$ what it's good at
text to video▇▅▄▆█▆▇▂▃▃▂▄ #80 of 94 * · 91% of its score · 2 tests
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Cosmos 3D consistency: camera-pose estimation success rate on generated videos lab | 27.0% ✎ | █·█·······██ beats 0/3 | 86% |
| Cosmos 3D consistency: Sampson epipolar error on generated videos (lower is better) lab | 0.3920 ✎ | █···█···█··█ beats 2/3 | 4.4% |
$ where to run it
No verified API or download recorded yet · add one
Official weights and documentation: huggingface.co/nvidia ↗
$ how the score was worked out · Cosmos World Foundation Model… 91%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 Cosmos World Foundation Model Platform for Physical AI (arXiv:2501.03575v3) · lab-reported | 2 | 91% |
| prior · pull toward the middle | 9% | |
| weighted average | = 30.5 |
$ improve this page
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data updated · sources and licences · json