whatmodel.sh / video / HappyHorse 1.0
HappyHorse 1.0
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HappyHorse 1.0 is a closed-weights video model from Alibaba-ATH, released April 2026. Licence: proprietary.
$ how it compares
The video models ranked either side of HappyHorse 1.0, out of 139 with a score.
| # | model | score | where |
|---|---|---|---|
| 13 | 75±3 | comparison only | |
| 14 | 75±4 | api $0.036/sec | |
| 15 | 73±2 | api $0.14/sec | |
| 16 | 71±5 | api $0.10/sec | |
| 17 | 69±2 | api $0.050/sec |
$ what it's good at
text to video▆▄▃▄▆▅█▃▂▂▃▄ #9 of 68 * · 43% of its score · 1 test
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena video | 1427.2 ✎ | ▂▂▃▆█▆·▆▅▃▂▇ beats 33/41 | 43% |
image to video▁▂·▂▅█▅▄▅▆▃▄ #12 of 50 * · 45% of its score · 2 tests
Beats HappyHorse 1.1 here, though they rank higher overall. Trails Kling 3.0, Grok Imagine Video here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena image-to-video | 1441.7 ✎ | ▁▁▁▁▄▇▃▆▃▂▄█ beats 31/40 | 29% |
| Rapidata physics realism (I2V, with reference) | 1085.0 ✎ | ▂··▂▂▆█▆▂▂▆▄ beats 9/19 | 16% |
video editing▄··█··▄··█▄█ #6 of 9 * · 8.8% of its score · 1 test
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena video edit | 1306.7 ✎ | █··█··▄··█▄█ beats 4/9 | 8.8% |
other tests1 not in a task · 1.8% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| MechVerse mechanical-motion I2V (WorldModelBench-judge sum) | 75.6% ✎ | ▂···▂······█ beats 3/5 | 1.8% |
$ where to run it
Through an API
api · Replicate · $0.14/sec · replicate.com ↗ · price sourceUSD per output video second. Text-to-video, 720p output, no starting image; 3–15 second clips. 1080p costs $0.28/output-second. Replicate output/character billing; hardware-time rates are not added to this tariff. Taxes and separate services excluded. Bertrande, https://bertrande.com/en/ai/replicate/alibaba--happyhorse-1.0; observed 2026-09-20T01:44:15Z. CC BY 4.0; units normalized and model identifier mapped.
$ how the score was worked out · LMArena leaderboard dataset 81%, Rapidata/world-model-physics… 16%, MechVerse: Evaluating Physica… 2%
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 |
|---|---|---|
| 3 | 81% | |
| 1 | 16% | |
| 1 | 2% | |
| prior · pull toward the middle | 1% | |
| weighted average | = 72.7 |
$ 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