GPT Image 2: How to Use It

GPT Image 2 reads long prompts and keeps text crisp on the image. Here's how to write for it, where it beats other models, and where it doesn't.

GPT Image 2 has one trait that sets it apart from the competition: it reads complicated written instructions better than most other models. Not "a nice product shot" but a full paragraph with specifics, where every clause actually gets registered. If you know how to write a clear brief, that changes everything about this model.

The job: text inside an image

This is where it shines. A label on packaging, a headline on a banner, a price tag, a slogan.

The model holds up long strings of text noticeably better than most, though not perfectly. Long phrases can still drift or garble a letter here and there. Short words land correctly almost every time. We ran a text-rendering comparison across a dozen models and saw the same pattern hold up here too.

Here's a trick that works: put the exact text in quotes as its own clause in the prompt, something like the label reads 'Hand Cream.' That tells the model you mean literal text, not a description.

The job: following a detailed description

The second strength, and the main reason to pick this model in the first place.

If a scene needs five specific objects arranged a specific way, GPT Image 2 gets there far more often than its competitors. Other models, once a prompt gets long, start quietly dropping details.

Which means a short, one-line prompt is a waste on this model. It earns its keep on long, specific ones. Write in paragraphs, not a single sentence.

I'll admit this advice cuts against itself. I tell people to write full paragraphs, and when I do exactly that, I regularly end up with a cluttered frame: the model dutifully crams in every single thing I listed.

The job: product photography

Solid, but not a standout. Texture and lighting look believable, though Nano Banana and Seedream 5.0 are often more convincing on fine surface detail.

If the product is simple and the packaging text matters most, go with GPT Image. If texture is what sells the shot, go with one of the others.

The job: speed and volume

The weak spot. It thinks longer than fast models and costs more per generation.

Don't use it for a hundred rough drafts. It's cheaper to burn through variations on Z-Image and bring the winner here for the finished version.

How to write a prompt that actually gets through to it

Here's the order that works best for me, in practice.

Start with the object: what it is, what it's made of, what color, what condition it's in.

Then the scene: what it's sitting on, what's around it, what's in the background.

Then the light: direction, softness, time of day.

Then the camera: close-up, medium shot, angle.

Then any text, in quotes, if the image needs it.

And finish with exclusions: what shouldn't show up in the frame.

None of this order is mandatory; the model handles free-form writing just fine. But once a description gets long, structure keeps you from forgetting half of what you wanted. We broke down prompt structure in more detail in this guide.

I recommend paragraphs, and writing paragraphs is exactly what keeps landing me a cluttered frame because the model dutifully includes everything I wrote. Ten precise phrases beat thirty vague ones.

Where to find more detail

We've got a technical breakdown with benchmark numbers in our GPT Image 2 review and a look at where the model lands on the leaderboards in this piece. The model itself is available on the GPT Image 2 page, where you can also see the current generation cost.

FAQ

What can GPT Image 2 do? Generate images from a detailed text description or a reference image, including text that appears inside the frame. Its biggest strengths are precise instruction-following on long prompts and handling text in an image.

Does GPT Image 2 render text accurately? It handles long strings of text better than most competing models, especially short ones. Longer phrases can still come out slightly off, so it helps to put the exact wording in quotes as its own clause in the prompt.

How is GPT Image 2 different from other models? It's better at parsing complex instructions. On a long prompt packed with details, it follows through on more of them than models that start skipping requirements once the brief gets long.

Is it good for marketplace listing photos? Yes, especially when the packaging text matters or the scene needs to match a specific composition exactly. If surface texture is the priority, it's worth comparing against Nano Banana and Seedream.

GPT Image 2: How to Use It and Where It Actually Wins