GPT Image 2.5 API in practice: five hidden settings and how each performed

Practical_Low29 · reddit · 2026-09-16

A hands-on test of the GPT Image 2.5 API, documenting five settings the ChatGPT app never exposes:

Model choice: the API lets you pick gpt-image-2.5-flare or gpt-image-2.5-sunburst; the chat app and Codex built-in tool cannot.
Five quality steps, not a toggle: low/medium/high/xhigh/max plus auto. On a 1024 product shot, flare ranged from 11.6s (low) to 42s (max); sunburst from 18.7s to 82s. Always set the step manually when comparing outputs.
Almost any size: width/height multiples of 16, long side ≤3840, ratio ≤3:1, pixel count between 655,360 and 8,294,400. 1024x1536 and 1920x1080 both returned faster than a 1024 square.
Transparent background is a parameter: background=transparent with png/webp gave 84.5% transparent pixels on a logo; writing "transparent" only in the prompt produces a fake checkerboard painted into RGB pixels — the source of common chat-app complaints. Add "no plate" when the subject usually sits on a plate, or the model draws one.
Up to 16 reference images with a mask: the edit endpoint supports them. The author's product workflow: flare edit for cutout, flare edit to place into a scene, sunburst edit for retouch, with a "Keep exactly" protection paragraph locking product geometry, labels and packaging text.

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