whatmodel.sh / video / HappyHorse 1.1
HappyHorse 1.1
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HappyHorse 1.1 is a closed-weights video model from Alibaba, released June 2026.
Model information sources
$ how it compares
The video models ranked either side of HappyHorse 1.1, out of 139 with a score, then more from Alibaba.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 7 | 77±1 | api $0.30/sec | |||
| 8 | 77±2 | api $0.17/sec | |||
| 9 | 76±3 | api $0.14/sec | |||
| 10 | 76±4 | api $0.080/sec | |||
| 11 | 76±2 | comparison only | |||
| more from Alibaba | |||||
| 2 | 80±7 | api $0.14/sec | |||
| 4 | 79±2 | api $0.10/sec | |||
| 14 | 75±4 | api $0.036/sec | |||
$ what it's good at
text to video▆▄▃▄▆▅█▃▂▂▃▄ #8 of 68 * · 16% of its score · 1 test
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Sci-VBench testmini (expert human rating) | 61.2% ✎ | ▅·▃█▃·▅▃▅▃▃▃ beats 13/14 | 16% |
image to video▁▂·▂▅█▅▄▅▆▃▄ #22 of 50 * · 3.2% of its score · 1 test
Trails Runway Gen-4.5, Kling 2.6 Pro, Wan 2.6 here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Rapidata camera movement (I2V) | 1181.1 ✎ | ▄···▄▄▄█··▄█ beats 6/8 | 3.2% |
other tests3 not in a task · 76% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Rapidata relative camera movement (I2V, alignment Elo) | 1290.8 ✎ | █···▄▄██·█▄█ beats 10/12 | 43% |
| Rapidata image-to-video realism (overall Elo) | 1137.9 ✎ | ▂······▃▃▃▃█ beats 3/12 | 23% |
| Datapoint Video Bench (overall Elo) | 998.6 ✎ | ▃▃·▅·▃·▃··▃█ beats 4/9 | 10% |
$ where to run it
Through an API
api · Alibaba Cloud Model Studio · $0.14/sec · www.alibabacloud.com ↗ · price sourceUSD per second of output video, 720P, International deployment (Singapore). Product: Model Studio HappyHorse text-to-video. API model: happyhorse-1.1-t2v. Settings: resolution=720P. Price basis: published list price; only output is billed. 480P $0.07/s, 1080P $0.18/s. Free quota and other regions excluded. Currency: USD. Alibaba Cloud Model Studio pricing page, observed 2026-09-25.
$ how the score was worked out · Rapidata/relative-camera-move… 43%, Rapidata/image-to-video-reali… 23%, Sci-VBench: Evaluating Knowle… 16% and 2 more
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 |
|---|---|---|
| 1 | 43% | |
| 1 | 23% | |
| 1 | 16% | |
| 1 | 10% | |
| 1 | 3% | |
| prior · pull toward the middle | 5% | |
| weighted average | = 76.3 |
$ 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