What actually goes wrong with AI text
Most garbled text comes from one of three prompt problems. The words were described instead of quoted (“a sign saying we are open late”), so the model paraphrased them. There was too much copy, so the model ran out of room and invented letterforms. Or the layout was left open, so the model scattered or merged lines. Quoting, trimming, and placing the copy solves the majority of cases before you change models at all.
Choosing where to run the prompt
Vizify’s image capability routes typography-led work differently from general illustration. Posters, covers, labels, and signage start on a graphic-design model: Ideogram V3, Recraft V4.1, or GPT Image 2.5 Flare, which has its own GPT Image 2.5 Generator. Recraft V4.1 is text-only, so it cannot take a reference image. Qwen Image 3.0 is the starting point for long prompts with dense text and for Chinese and other multilingual copy, with Qwen Image 3.0 Pro available for denser layouts. GPT Image 2, the default image model, is a reasonable choice for a short line inside a broader scene. None of these makes a spelling check unnecessary.
Some text jobs are not a good fit for generation at all: long body copy, legal disclaimers, pricing tables, QR codes, and anything that has to match a brand font exactly. For those, generate the image with deliberate empty space where the copy will go (“clear sky across the top third, no text”) and set the words afterward in the tool you already use for layout. You keep the generated visual and get exact, editable typography.
A quick proofreading pass
Read the output at full size, letter by letter, against your quoted copy. Check capitalization, punctuation, and line order, and look for extra invented words in the background of signs and labels. If one line is wrong, keep the prompt identical and repeat that line’s quoted text, since changing several things at once makes it harder to see what helped.