whatmodel.sh / video / Hailuo 02
Hailuo 02
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Hailuo 02 is a closed-weights video model from MiniMax, released June 2025.
Model information sources
$ how it compares
The video models ranked either side of Hailuo 02, out of 139 with a score, then more from MiniMax.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 50 | 54±12 | comparison only | |||
| 51 | 54±3 | api $0.050/sec | |||
| 52 | 54±2 | api $0.047/sec | |||
| 53 | 53±6 | api $0.12/sec +local | |||
| 54 | 53±3 | comparison only | |||
| more from MiniMax | |||||
| 6 | 78±1 | api $0.13/sec +local | |||
| 10 | 76±4 | api $0.080/sec | |||
| 48 | 55±2 | api $0.047/sec | |||
$ what it's good at
text to video▆▄▃▄▆▅█▃▂▂▂▄ #27 of 68 * · 59% of its score · 2 tests
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena video | 1181.1 ✎ | ▂▂▃▆█▆·▆▅▁▂▇ beats 12/41 | 57% |
| HumanScore (T2V) | 85.8% ✎ | ▂··▂··█▄▂··▆ beats 4/11 | 1.8% |
image to video▁▂·▂▅█▅▄▅▆▃▄ #35 of 50 * · 39% of its score · 2 tests
Beats Seedance 1.5 Pro, Kling 2.1 Standard here, though they rank higher overall. Trails Cosmos3-Nano here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena image-to-video | 1223.7 ✎ | ▁▁▁▁▄▇▃▆▃▂▄█ beats 9/40 | 38% |
| V-ReasonBench (average pass@5) | 37.5% ✎ | █·····▄···▄▄ beats 3/4 | 1.7% |
$ where to run it
Through an API
api · $0.047/sec · platform.minimax.io ↗ · price sourceUSD per second of output video, 768P, derived from MiniMax's pay-as-you-go price of $0.28 per 768P 6-second video (÷ 6). Product: MiniMax video generation (listed under Legacy Models). API model: MiniMax-Hailuo-02. Settings: resolution=768P, duration=6 s. 10-s 768P $0.56 ($0.056/s); 6-s 1080P $0.49; 6-s 512P $0.10. Currency: USD. MiniMax pay-as-you-go pricing page, observed 2026-09-25.
$ how the score was worked out · LMArena leaderboard dataset 95%, HumanScore: Benchmarking Huma… 2%, V-ReasonBench: Toward Unified… 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 |
|---|---|---|
| 2 | 95% | |
| 1 | 2% | |
| 1 | 2% | |
| prior · pull toward the middle | 1% | |
| weighted average | = 53.5 |
$ 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