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Wan 2.2 I2V Flash
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Wan 2.2 I2V Flash is a closed-weights video model from Alibaba, released August 2025. Licence: proprietary.
Catalogue identity notes
Alibaba Cloud Model Studio API model wan2.2-i2v-flash (image-to-video; 480P or 720P, fixed 5 s per the image-to-video API reference; released 2025-08-15); international release date from Model Studio's 'newly released models' page (https://www.alibabacloud.com/help/en/model-studio/newly-released-models, observed 2026-09-29). Commercial API tier; not assumed identical to any open Wan checkpoint. No price recorded (no approved price_source read for this tier).
$ how it compares
The video models ranked either side of Wan 2.2 I2V Flash, out of 139 with a score, then more from Alibaba.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 12 |  Grok Imagine Video 1.5 | 75±2 | api $0.080/sec | ||
| 13 |  HiDream-O1-Video 1.0 | 75±3 | comparison only | ||
| 14 | Wan 2.2 I2V Flash | 75±4 | api $0.036/sec | ||
| 15 |  HappyHorse 1.0 | 73±2 | api $0.14/sec | ||
| 16 | Wan 2.2 I2V Plus | 71±5 | api $0.10/sec | ||
| more from Alibaba | |||||
| 2 | Wan 3.0 Prime | 80±7 | api $0.14/sec | ||
| 4 | Wan 3.0 | 79±2 | api $0.10/sec | ||
| 9 | HappyHorse 1.1 | 76±3 | api $0.14/sec | ||
$ what it's good at
image to video▁▂·▂▅█▅▄▅▆▃▄ #8 of 50 * · 92% of its score · 1 test
Beats HappyHorse 1.1, Grok Imagine Video 1.5 here, though they rank higher overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Target-Bench v2 (VGGT planning score, I2V) | 34.1% ✎ | ▃·▃···▃▃█·▃▃ beats 8/8 | 92% |
$ where to run it
Through an API
api · Alibaba Cloud Model Studio · $0.036/sec · www.alibabacloud.com ↗ · price sourceUSD per second of output video, 720P silent video, International deployment (Singapore). Product: Model Studio Wan image-to-video (first frame). API model: wan2.2-i2v-flash. Settings: resolution=720P. Price basis: published list price; only output is billed. 480P $0.015/s. Free quota and other regions excluded. Currency: USD. Alibaba Cloud Model Studio pricing page, observed 2026-10-07.
$ how the score was worked out · Target-Bench: Can Video World… 92%
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 |
|---|---|---|
 Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets? | 1 | 92% |
| prior · pull toward the middle | 8% | |
| weighted average | = 74.9 |
$ 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