GPT Image resolution above 2560x1440: experimental, and Sume's cap
OpenAI marks GPT Image sizes above 2560x1440 as experimental. Sume's 2.5 custom pixels accept up to a 3840 edge, so check the five size rules before you send.
OpenAI's image guide says resolutions above 2560x1440 are experimental for GPT Image models. Sume's ChatGPT Image 2.5 models accept custom pixels up to a 3840 edge, so a 3840x2160 request is valid on the Sume side, but treat anything above 2560x1440 as the experimental zone OpenAI describes.
Sume rules are from the Image API docs; the experimental line is from OpenAI's guide. Both were read 2026-09-30. The Sume docs do not say whether sizes above 2560x1440 are experimental on Sume.
What are Sume's custom pixel rules?
For the 2.5 models, image_size accepts named presets, auto, or custom pixels. Custom pixels need both edges to be multiples of 16, a maximum edge of 3840, an aspect ratio of at most 3:1, and a total of 655,360 to 8,294,400 pixels. OpenAI's guide lists the same limits and adds that the 8,294,400 ceiling is 4K.
| Size | Valid? | Why |
|---|---|---|
| 2560x1440 | Yes | At OpenAI's experimental line, not above it |
| 3840x2160 | Yes | Exactly 8,294,400 pixels |
| 4096x2304 | No | Edge is over 3840 |
| 3840x1280 | Yes | 3:1 is the allowed maximum |
| 1000x700 | No | Edges are not multiples of 16 |
| 512x512 | No | 262,144 pixels is under 655,360 |
Where do I put the pixels?
In image_size, not size. The docs call size a shorthand for a resolution tier and say not to put custom pixels on it; the parameter table adds that explicit pixels are not served on size in v1. The separate resolution field takes a tier (512, 1K, 2K, 4K).
const response = await fetch("https://api.sume.com/v1/images", {
method: "POST",
headers: {
Authorization: "Bearer " + process.env.SUME_API_KEY,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "openai/gpt-image-2.5",
prompt: "A wide product shot on a pale studio floor",
image_size: "2560x1440",
}),
});
console.log(await response.json());What happens if the size breaks a rule?
The docs state that a request that sets a parameter the selected model does not list is rejected with 400 unsupported_parameter. That sentence is about unlisted parameters; the docs do not spell out the error for an out-of-range value. Validate sizes in your own code first rather than depending on a particular error.
Should I go above 2560x1440 at all?
If you need a 4K deliverable, you have two routes: ask for a 4K-class size directly, accepting OpenAI's experimental label, or generate at or under 2560x1440 and enlarge afterwards. The second route is covered in AI image 4K: generate or upscale. Pick by testing a few of your own prompts; this page does not rank them.
Sources
Related posts
- GPT Image 2.5 resolution: the size rules and the 4K ceiling
- How to upscale an image to 3000x3000 (or any exact size)
- AI image generation API aspect ratios: 4:5, custom sizes, and auto
- 4K AI image: generate at 4K or upscale a 1K image? The cost
- Nano Banana 4K resolution API: the tier strings Sume accepts
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