whatmodel.sh / image / Grok Imagine Image
Grok Imagine Image
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Grok Imagine Image is a closed-weights image model from SpaceXAI (xAI).
Score within the LMArena text-to-image comparison set only.
$ how it compares
The image models ranked either side of Grok Imagine Image, out of 197 with a score.
| # | model | score | where |
|---|---|---|---|
| 24 | 66±3 | api $0.075/image | |
| 25 | 66±3 | comparison only | |
| 26 | 66±2 | api $0.020/image | |
| 27 | 65±2 | api $0.10/image | |
| 28 | 65±2 | api $0.050/image |
$ what it's good at
text to image▂▅▅▃▄▄█▃▁▂▁▁ #21 of 126 * · 64% of its score · 1 test
Trails Uni-1.1 Max here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena text-to-image | 1169.7 ✎ | ▂▂▃▄▇█▄▂▄▂·▂ beats 53/75 | 64% |
image to image / editing▁▁·▃▂▃█▃▃▄▁▁ #17 of 62 * · 24% of its score · 1 test
Beats Nano Banana 2 Lite (Gemini 3.1 Flash-Lite Image), Qwen-Image-2.0-Pro (2026-06-22), Uni-1.1 here, though they rank higher overall. Trails Grok Imagine Image Pro, Uni-1.1 Max here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena image edit | 1329.0 ✎ | ▂▁▁▂▆▇█▄▆▅▁▂ beats 35/53 | 24% |
other tests1 not in a task · 10% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Rapidata Benchmark.ai image benchmark (overall Elo) | 988.6 ✎ | ▁▁▁▄▂█▂▁▁▂▁▁ beats 14/34 | 10% |
$ where to run it
Through an API
api · xAI · $0.020/image · docs.x.ai ↗ · price sourceUSD per generated image on the xAI API (output $0.02 per image). Product: xAI API image generation. API model: grok-imagine-image (alias grok-imagine-image-2026-03-02). Settings: one image. Price basis: published per-image list rate. grok-imagine-image-2.0 ($0.04) and grok-imagine-image-quality ($0.05) are separate models. Currency: USD. xAI official models and pricing page, observed 2026-09-26.
$ how the score was worked out · LMArena leaderboard dataset 88%, Rapidata/text-to-image-human-… 10%
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 | 88% | |
| 1 | 10% | |
| prior · pull toward the middle | 2% | |
| weighted average | = 65.7 |
$ 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