Why AI Gets Hands and Text Wrong (and How to Fix It)

Six fingers on one hand. A sign written in an alphabet that doesn't actually exist. Someone else's logo, stitched onto a model's shirt for no reason. If you've generated product photos with AI even once, you've seen this. Here's why AI gets hands and text wrong, no mystery involved, just how these models actually work, and seven fixes I use myself to get a clean shot for a product listing.

Why This Even Happens

A model doesn't know that a hand is five fingers, or that a word is letters in a fixed order. It builds an image out of probabilities: what usually sits next to what. Hands show up in hundreds of positions, fingers overlap each other, and somewhere in that overlap the model happily tacks on an extra digit or bends a joint the wrong way. Text works the same way. To a generator, letters are a pattern, not meaning, so it paints something that looks like text without actually being text.

Logos are their own problem. The model has seen countless brands during training and likes to slip something familiar onto a piece of clothing or packaging. For a product listing that's a real risk. Someone else's logo in frame is exactly the kind of thing that gets flagged during marketplace review.

Where It Breaks Most Often

Hands and fingers break most often, especially when a model is shown holding a product. Text on packaging and in infographics comes next, especially when the script isn't well represented in training data. Small repeating patterns trip things up too: chain links, teeth on a zipper, grid patterns, anywhere the model loses count. Reflections and glare on glass or glossy surfaces are another weak spot. And then there are the logos the model invents on its own.

What I Use to Clean Up a Shot

Pick the right model for the job. If a shot has a lot of text in it, go straight for models built around typography: Ideogram 3.0 for in-image text and GPT Image 2 for layouts and labeling. I covered both in more depth in my Ideogram 3.0 review and my GPT Image 2 review. For non-Latin scripts specifically, Qwen Image 2.0 and Z-Image punch above their weight, I go deeper on that comparison in my piece on non-Latin text in AI images.

Use a negative prompt. Wherever the tool supports it, spell out exactly what shouldn't appear: extra fingers, distorted text, watermarks, stray logos. It won't catch everything, but it reliably cuts down the junk.

One more thing on hands: don't ask for a complicated grip. If you can show the product without a tight hold on some small detail, do that. The simpler the hand position, the lower the odds of a sixth finger showing up.

Add text separately. The most reliable way to get a clean, correct label is to generate the background with AI and drop the text in with an editor afterward. The model handles the image, a human handles the letters.

Shoot the detail tight when texture is involved. Small repeating elements confuse a model on a wide shot. Give it a close crop with fewer links or teeth to track, then build your final composition from pieces like that.

Change one variable at a time. Don't rewrite the whole prompt after a bad result. Adjust one thing, hand position, camera angle, how you phrase the text request, and regenerate. That way you actually know what fixed it.

And the least exciting tip, which also happens to be the one that works best: look at the shot before you upload it, right alongside a quick before-and-after comparison shot. Half of these problems get caught right there. A sixth finger or a borrowed logo is obvious once you actually look.

Running one scene through several models and picking the version without a sixth finger takes about a minute on Flami. The models known for clean hands and text are already there, no extra hunting required.

FAQ

Why does AI draw extra fingers?

A model doesn't count fingers, it assembles a hand from shapes it's seen before. In complicated poses, where fingers overlap or grip something, it's easy for it to add an extra one or bend a joint wrong. A simpler hand position and a tighter crop both cut the risk.

Why does AI-generated text come out garbled?

To a generator, letters are a visual pattern, not meaning, so it paints something that resembles text rather than text itself. They still stumble on scripts that were underrepresented in training, like Cyrillic. For anything that has to be correct, use a model built for typography, or add the text yourself in an editor afterward.

How do I get rid of unwanted logos in a shot?

Add a line banning stray logos to your negative prompt, and check the image before you upload it. A borrowed brand on clothing or packaging is a real risk during marketplace review, so a shot like that is worth regenerating rather than shipping.

Can I actually trust AI with text on packaging?

With some caution. Even the models that are strong with text miss sometimes, especially on scripts they saw less of during training. For anything that matters, the safest route is still a clean AI-generated background with the text added by a person afterward.

Sources

1. Flami: non-Latin text in AI image generators
2. Flami: infographics and text on product images