whatmodel.sh / video / Runway Gen-2
Runway Gen-2
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Runway Gen-2 is a closed-weights video model from Runway, released June 2023. Licence: proprietary.
Catalogue identity notes
Introduced March 2023, public release June 2023; not offered in Runway's current API (Gen-3 Alpha Turbo and later).
$ how it compares
The video models ranked either side of Runway Gen-2, out of 139 with a score, then more from Runway.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 129 | 27±4 | comparison only | |||
| 130 | 27±3 | local | |||
| 131 | 27±2 | comparison only | |||
| 132 | 27±2 | comparison only | |||
| 133 | 26±2 | local | |||
| more from Runway | |||||
| 26 | 65±7 | api $0.28/sec | |||
| 36 | 58±2 | api $0.12/sec | |||
| 41 | 56±5 | comparison only | |||
$ what it's good at
text to video▇▅▄▆█▆▇▂▃▃▂▄ #84 of 94 · 98% of its score · 7 tests
Beats ZeroScope v2 576w, Open-Sora 1.2 here, though they rank higher overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| EvalCrafter 2023 motion quality | 56.43 / 100 ✎ | ▄····▄██··▄▄ beats 7/7 | 18% |
| VideoPhy (human, SA=1 & PC=1) | 7.6% ✎ | ▄▄▄·▄▄█····▄ beats 0/7 | 18% |
| EvalCrafter 2023 visual quality | 62.51 / 100 ✎ | ▄█·····▄·█▄▄ beats 7/7 | 17% |
| EvalCrafter 2023 temporal consistency | 64.41 / 100 ✎ | ▄···▄▄▄▄▄··█ beats 6/7 | 17% |
| EvalCrafter 2023 text-video alignment | 60.98 / 100 ✎ | ▂··▂▂·····▃█ beats 3/7 | 15% |
| VideoPhy (auto-evaluator average) | 29.0% ✎ | ▅·▃▅··▃█···▃ beats 0/9 | 7.5% |
| ChronoMagic-Bench-150 GPT4o-MTScore (time-lapse metamorphosis) | 52.4% ✎ | ▄·▄█▄▄▄·▄·▄█ beats 5/10 | 6.2% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · EvalCrafter: original 2023 te… 67%, VideoPhy / VideoPhy-2 officia… 25%, ChronoMagic-Bench: A Benchmar… 6%
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 |
|---|---|---|
| 4 | 67% | |
| 2 | 25% | |
| 1 | 6% | |
| prior · pull toward the middle | 2% | |
| weighted average | = 26.6 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json