A generative fill alternative for changing the words in an image

Generative fill is a good tool for changing an image, and the wrong-shaped one for changing the words in it. For words, the better choice is an editor that points the model at the exact text and keeps only the pixels that changed — so the background behind and between the letters stays your original.

That is the short answer. The rest of this post is why the two diverge, and how to tell which one your task is.

What is generative fill actually for?

You select a region, type a prompt, and a model repaints the selection. Adobe's own description of Generative Fill is precise about the job: adding, extending or removing content in an image. Removing a photobomber or extending a sky is exactly that shape of problem, and generative fill is very good at it.

Why does region repainting struggle with words?

The whole selection is repainted, not the letters

Everything inside the selection is regenerated — the words and the ground they sit on. On a flat colour you may never notice. On a gradient, a texture, a rule running through the text or a product edge behind it, the ground comes back reimagined, and the seam lands wherever the selection boundary was drawn.

A prompt is a vague way to point at a word

"Change the date to Friday" has to be matched to pixels by the model, inside a selection that usually holds more than the date. Text rendering is already the known weak spot of image models — improving it is still announced as a headline result, as in OpenAI's introduction of 4o image generation — and an imprecise instruction gives it more room to go wrong.

What does a text editor do instead?

Edit text in an image keeps the model and changes the two things that go wrong:

1. The words are marked, not described. Each piece of text to change is boxed on the image the model sees, and the instruction names the box and the new words.
2. Only what changed is kept. The model returns a whole picture, but the result takes from it only the pixels that differ along the marked lines. Background inside the box that the model left alone is still the original's, and everything outside is untouched.

Here is the first half of that in the editor: the headline boxed on the picture, and the new words typed against its number rather than described in a prompt.

What that leaves is small enough to see. The difference map for a real edit shows under 4% of a poster changed, all of it in the headline's strokes.

The cost is an edge. Where the kept pixels meet the original on a textured background, a faint outline can show around the new words. The editor's answer is a Whole redraw switch on the result — the model's full picture, no edge, small details elsewhere free to shift. It is the same generation, so the switch is free.

Which should you use?

	Generative fill	Text editor
Built for	objects, regions, backgrounds	words on the image
How the target is given	a selection and a prompt	the exact words, boxed
What is regenerated	everything inside the selection	only the pixels that changed on the marked lines
Outside the target	untouched	untouched
Where it can show	the selection boundary	a faint edge on textured ground (whole redraw avoids it)

The decision is not which tool is better. It is which of two questions you are asking:

• "Make this region into something else." Generative fill. The region is meant to change, and plausibility is the standard.
• "Change these words and touch nothing else." A text editor. The picture is meant to survive, and the standard is that nothing but the words moved.

If the question is really about Canva's built-in version of the second one, the comparison with Canva Grab Text covers where a general design tool stops. If the new words must look like the original lettering, that case has its own page.