Portraits · Text-to-Image
Elo rankings from blind votes across 1 challenge in this category.
Highlights
5 imagesBest models, by
Best Text-to-Image Models by Price
1 model without pricing omitted.
Best Text-to-Image Models by Speed
36 models waiting for enough speed data.
Best AI Models for Portraits
| # | Model | Elo |
|---|---|---|
| 1 | 1279 | |
| 2 | 1268 | |
| 3 | 1261 | |
| 4 | 1253 | |
| 5 | 1242 | |
| 6 | 1238 | |
| 7 | 1236 | |
| 8 | 1233 | |
| 9 | 1232 | |
| 10 | 1232 |
| 11 | 1229 | |
| 12 | 1228 | |
| 13 | 1215 | |
| 14 | 1212 | |
| 15 | 1212 | |
| 16 | 1204 | |
| 17 | 1201 | |
| 18 | 1196 | |
| 19 | 1196 | |
| 20 | 1195 | |
| 21 | 1188 | |
| 22 | 1181 | |
| 23 | 1176 | |
| 24 | 1175 | |
| 25 | 1171 | |
| 26 | 1168 | |
| 27 | 1161 | |
| 28 | 1159 | |
| 29 | 1157 | |
| 30 | 1156 |
FLUX.2 [dev] Turbo leads the portrait category with a 1,279 Elo and 78.9% win rate, narrowly outpacing Google’s Nano Banana 2 by 11 Elo points. While current-generation FLUX and Google models dominate the top tier, Alibaba’s Qwen Image 2512 maintains a 100% win rate in limited head-to-head matchups, indicating high competitive potential despite its lower Elo ranking (1,238).
Rivalries
Aggregate head-to-head across the arena
Highlighted challenges
The Reversed Rodeo
This competition tests how well AI image models truly understand language versus how much they rely on visual habits from their training data. The prompt is deliberately simple on the surface but devilishly hard in practice. Most models default to the familiar trope of an astronaut riding a horse. By forcing the reversal, we measure three critical capabilities that separate good models from great ones: Strict instruction following (including negations) Accurate subject-object relationships and spatial hierarchy Resistance to strong dataset biases
Geometric Composition
A spatial-reasoning test. Each object has a precise relationship (inside, on top, behind, seen through the glass), so it measures whether a model follows explicit placement instructions and handles transparency and refraction rather than just approximating the scene.
Keep the arena honest
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