GPT Image 2.5 Menu Design: 6 Prompts for Menus People Can Actually Read

GPT Image 2.5 can assist with generating cafe menu concepts and making targeted raster-image edits, but reliable menus still require approved source content, careful proofreading, checks of item-price pairings, readability testing, and editable source files for ongoing updates. The guide distinguishes new image generation from reference-based edits and from maintainable layouts built with separate text objects, using examples for a 12-item portrait menu, a single latte-price revision, a landscape board, a bilingual drinks menu, and a blank background intended for later text placement. It recommends supplying exact wording, dimensions, visual requirements, and exclusions in prompts, then reviewing every output against an authoritative content sheet for omissions, duplicates, misplaced prices, layout shifts, and language errors. It also emphasizes testing menus at their real viewing size, confirming printer requirements and effective resolution, using approved food images and independently tested QR codes, and recording model settings, attempts, quoted costs, and accepted versions because image-generation prices and results can vary by quality, size, endpoint, and retries.

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