Aspect Ratios: Which Resolution Should You Use?
SDXL was trained on specific resolution buckets. Use them and images pop. Ignore them and you get mush. Full cheat sheet inside.
July 5, 2026 · 4 min read

Why buckets matter
Stable Diffusion XL was trained on a small set of specific resolutions. Generate at 1024×1024 or 1344×768 and you'll get sharp, well-composed images. Generate at 1000×750 and you'll get soft, weirdly proportioned mush — because the model never saw a training image at that size.
The SDXL cheat sheet
| Ratio | Resolution | Use for |
|---|---|---|
| 1:1 | 1024 × 1024 | Social posts, avatars, gallery grids |
| 4:3 | 1152 × 896 | Blog covers, standard photos |
| 3:4 | 896 × 1152 | Portrait, book covers, magazine pages |
| 16:9 | 1344 × 768 | YouTube thumbnails, hero banners, desktop wallpapers |
| 9:16 | 768 × 1344 | TikTok, Reels, Instagram stories, phone wallpapers |
| 21:9 | 1536 × 640 | Ultra-wide banners, cinematic |
Imagoat's Generate page uses these exact numbers behind the scenes — pick "16:9" and you get 1344×768, not some in-between size.
Upscaling later
If you need larger — a 4K wallpaper or a print-ready poster — generate at the correct bucket first, then run the result through an upscaler. Upscaling a well-composed 1024 image is dramatically better than generating at 2048 directly.
Portrait tip
For faces specifically, generate in 3:4 at 896×1152. It's the ratio the model saw most human portraits at during training, and the difference in facial coherence is huge.
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