GPT Image 2.5 cost by aspect ratio: square, 3:2, 4:5, 16:9
At the same quality, wide shapes cost less than a square in GPT Image 2.5 output tokens: 1536x864 is 36% below 1024x1024. Estimates for common ad shapes.

On GPT Image 2.5 the shape you ask for changes the output-token estimate. At medium, 1024x1024 is $0.01317, 1536x1024 (3:2) is $0.01029, 1024x1280 (4:5) is $0.01134 and 1536x864 (16:9) is $0.0084, before input tokens and Sume pricing. A square is the dearest of these because it has the most pixels on the short edge. Choose the shape the placement needs, not the shape that looks cheapest.
Estimates by shape
The numbers use the output-token estimate from OpenAI's size and quality calculator, which the Image API docs say Sume's estimates follow, at $30 per million output tokens, the rate listed on Fal's GPT Image 2.5 Flare page, and sizes that satisfy the rules in OpenAI's image generation guide. The 3:2 column is 1536x1024, which OpenAI lists as a recommended landscape size.
| Quality | 1:1 1024x1024 | 3:2 1536x1024 | 4:5 1024x1280 | 16:9 1536x864 |
|---|---|---|---|---|
| low | $0.00588 | $0.00474 | $0.00519 | $0.0036 |
| medium | $0.01317 | $0.01029 | $0.01134 | $0.0084 |
| high | $0.05268 | $0.04116 | $0.0453 | $0.03234 |
| xhigh | $0.09366 | $0.07377 | $0.08106 | $0.05751 |
| max | $0.21072 | $0.16464 | $0.18357 | $0.12936 |
What to take from it
Against the square at the same tier, 3:2 is about 22% cheaper, 4:5 about 14% cheaper and 16:9 about 36% cheaper. The saving is fractions of a cent at low and medium and noticeable at max.
The estimate depends on the short edge as well as the total pixels, which is why a frame with a shorter short edge costs less even when its pixel count is close to the square's.
Pick by placement
- Feed square or carousel: 1:1.
- Mobile portrait: 4:5; ask for 1088x1360 if you need exact pixels, see the 4:5 post.
- Photo-like landscape: 3:2.
- Video thumbnails and headers: 16:9.
- Edits:
aspect_ratio: "auto"keeps the reference's shape, so the shape is whatever you sent.
Send the ratio
aspect_ratio takes the normalised ratios in the docs; read the model's descriptors first, because a model only accepts the values it lists.
curl -X POST "https://api.sume.com/v1/images" \
-H "Authorization: Bearer $SUME_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-image-2.5",
"prompt": "A flat-lay of coffee beans and a brass scoop",
"aspect_ratio": "3:2",
"quality": "medium"
}'Caveat
These are estimates for output tokens. Verify with usage.cost on a real call; Sume applies its own pricing, and the endpoint pricing lines are what your wallet is charged.
Sources
Related posts
More in Pricing
- GPT Image 2.5 max quality: $0.21 at 1024, and when to use it
At 1024x1024, GPT Image 2.5 max output is $0.21072 and xhigh is $0.09366 before input tokens and Sume pricing. Quality levels, auto behavior and a request.
- Does a longer prompt cost more on GPT Image 2.5? Text token math
Prompt text is billed at $5 per million tokens on GPT Image 2.5, so a 2,000-token brief adds about $0.01, as much as a medium image. Numbers and rules.
- GPT Image 2.5 quality auto reserves max on Sume: pin quality
Sume's image docs say quality auto reserves max, and auto size reserves the output token upper bound. What to set instead, plus the 1024 by 1024 figures.
- Grok Imagine: 20 MiB image cap and per-second prices
xAI lists Grok Imagine video at $0.020 to $0.080 a second and a 20 MiB image limit. On Sume, check the live catalog and add the x1.25 billing rule.
Written by Sume