32:9 super ultrawide wallpaper from a 4:1 image: crop 11% of width
32:9 is 3.56:1, between GPT Image 2.5's 3:1 cap and Nano Banana 2.1's 4:1. Generate 4:1 on Sume at $0.20 for 4K and keep 88.9% of the width. Request and math.

A 32:9 super ultrawide screen is 3.56:1. The widest ratio GPT Image 2.5 takes on Sume is 3:1, and Nano Banana 2.1 lists 4:1, so a 4:1 image at 4K for $0.20 can be cropped to 32:9 by keeping 88.9% of its width.
Which ratio can get there
| Option | Widest ratio | Gets to 32:9? | Price |
|---|---|---|---|
| GPT Image 2.5, custom size | 3:1 cap | No, it is narrower | n/a |
| Nano Banana 2.1, 21:9 | 2.33:1 | No | n/a |
| Nano Banana 2.1, 4:1 at 2K | 4:1 | Yes, crop 11.1% of width | $0.15 |
| Nano Banana 2.1, 4:1 at 4K | 4:1 | Yes, crop 11.1% of width | $0.20 |
| Nano Banana 2.1, 8:1 at 4K | 8:1 | Yes, crop 55.6% of width | $0.20 |
Why 4:1, not 8:1
Both reach 32:9, but 8:1 would throw away more than half the width you paid for. 4:1 keeps 3.556 / 4 = 88.9% of the width, so almost every pixel stays in the wallpaper.
import os, requests
body = {
"model": "google/nano-banana-2.1",
"prompt": "Ultra-wide desktop wallpaper, calm mountain lake at dusk, no text, no people",
"aspect_ratio": "4:1",
"resolution": "4K",
}
r = requests.post(
"https://api.sume.com/v1/images",
headers={"Authorization": f"Bearer {os.environ['SUME_API_KEY']}"},
json=body, timeout=60,
)
print(r.status_code) # 200 = image body, 202 = job envelope
if r.status_code == 200:
out = r.json()
print(out["data"][0]["url"], out["usage"]["cost"])Gotchas
- Crop evenly from both edges so the focal point stays on the middle of the screen.
- A 4K call can take longer than the 30-second sync window; on a
202, poll the job and read the result. - Check the returned file's dimensions before you decide the crop box.
Sources
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