whatmodel.sh / video / Hailuo 2.3
Hailuo 2.3
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Hailuo 2.3 is a closed-weights video model from MiniMax, released October 2025. Licence: proprietary.
$ how it compares
The video models ranked either side of Hailuo 2.3, out of 139 with a score, then more from MiniMax.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 46 | 55±2 | api $0.020/sec | |||
| 47 | 55±3 | api $0.050/sec | |||
| 48 | 55±2 | api $0.047/sec | |||
| 49 | 55±2 | comparison only | |||
| 50 | 54±12 | comparison only | |||
| more from MiniMax | |||||
| 6 | 78±1 | api $0.13/sec +local | |||
| 10 | 76±4 | api $0.080/sec | |||
| 52 | 54±2 | api $0.047/sec | |||
$ what it's good at
text to video▆▄▃▄▆▅█▃▂▂▂▄ #24 of 68 * · 54% of its score · 1 test
Beats Seedance 1.0 Pro, Kling O1 Pro here, though they rank higher overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena video | 1206.0 ✎ | ▂▂▃▆█▆·▆▅▁▂▇ beats 15/41 | 54% |
image to video▁▂·▂▅█▅▄▅▆▃▄ #31 of 50 * · 36% of its score · 1 test
Beats Seedance 1.5 Pro, Wan 2.2 I2V A14B, P-Video 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 | 1262.0 ✎ | ▁▁▁▁▄▇▃▆▃▂▄█ beats 15/40 | 36% |
other tests1 not in a task · 8.5% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| MindWorldBench intention accuracy (I2V mental-state reasoning) | 13.0% ✎ | ▅·▃▅·█·▃···▃ beats 1/9 | 8.5% |
$ 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-2.3. Settings: resolution=768P, duration=6 s. A 10-s 768P video costs $0.56 ($0.056/s); a 6-s 1080P video costs $0.49. Hailuo-2.3-Fast excluded. Currency: USD. MiniMax pay-as-you-go pricing page, observed 2026-09-25.
$ how the score was worked out · LMArena leaderboard dataset 90%, MindWorldBench: Evaluating Me… 8%
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 | 90% | |
| 1 | 8% | |
| prior · pull toward the middle | 1% | |
| weighted average | = 54.7 |
$ 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