Which AI Image Model Should You Actually Use?
"Best AI image model" gets searched thousands of times a day, and I get why. Our own model picker currently lists twelve options, priced from 5 credits to 200. That's a 40x spread. Nobody wants to learn twelve models, and the lazy assumption, that expensive means better, wastes a remarkable amount of money.
So here's the honest version, from someone who watches what comes out of these things all day. The expensive models are not 40x better. They're better at specific jobs, and for some jobs the 5-credit option wins outright.
To keep myself honest while writing this, I ran one identical, deliberately fussy brief through six of the twelve: a specific pink cardigan, a book held up over the face, a leather chair in a bookshop, a window behind. Same words, one attempt each. Here's what came back, ordered by price.
Look at who kept the pose, who invented a better one, and who skipped the book entirely. We'll come back to this grid a few times.
The short answers
If you only read one section, make it this one:
Iterating on an idea: Z-Image Turbo. 5 credits, about two seconds per image.
Anything with readable text in it: GPT Image 2 High. 110 credits and slow, but it's the only one that can spell.
The most photorealistic, least AI-looking images, money no object: GPT Image 2 and Nano Banana Pro.
Realistic people on a budget: Kling O1 at 20 credits, or Qwen 2 Pro at 60 when you want more detail.
The same face across many images: Nano Banana Pro. Nothing else holds a character like it.
Detailed, instruction-heavy briefs, and edits: GPT Image 2 Medium or High. Nano Banana 2 is the cheaper, faster fallback, a quality step below.
Volume on a budget: Nano Banana 2 Lite in batch mode, 15 credits each.
Texture and fine detail: Flux 2 Pro, 25 credits, about a minute.
The rest of this post is the why, plus a workflow at the end that makes your credits go a lot further than any individual model choice will.
The two-second model nobody believes
Z-Image Turbo costs 5 credits and returns an image in one to two seconds. First reactions are always some version of "okay, what's the catch", because the portraits it makes are genuinely good: natural skin, believable light, none of the plastic sheen you'd expect at the bottom of the price list.
The catch shows up in complexity. One person in one setting and it shines. A crowded market with signage and three interacting characters, and it starts cutting corners. It also can't render text. You can see it in the test grid above: handed the full bookshop brief, it returned a lovely close-up portrait and quietly dropped the chair, the book and the cardigan.
None of that matters much, because its real job is iteration. At 5 credits you can afford to be wrong ten times in a row. Testing a composition, dialing in a character, checking whether an outfit reads the way you hoped: do all of that here, then carry the winning prompt somewhere expensive.
When the image has words in it
Text is the great filter. Most image models produce lettering the way dreams do: plausible at a glance, alien the moment you look directly at it. If your image contains a sign, a product label, a menu, a poster headline, you want GPT Image 2 High, full stop. Its reputation is accurate text and top fidelity, and it earns it. And the fidelity part goes well beyond lettering, which is why this model comes up again in the next section.
It's also the slowest and one of the priciest things in the lineup: 110 credits and around two and a half minutes per render. So don't design in it. GPT Image 2 Low costs 5 credits and follows the same layout logic. Rough out the composition on Low, and pay High prices only once the design is locked.
One quirk worth knowing: the GPT models are the strictest about content, and the strictness is a little random. Now and then a completely harmless prompt gets refused. Run it again before assuming you did something wrong; the second attempt usually sails through.
People who need to look like people
Let's settle the big one first. If you want the absolute ceiling, images that pass for photography even under a suspicious eye, it's a two-horse race: GPT Image 2 and Nano Banana Pro. They're the two priciest names in the picker, and this is the job that justifies it. Skin that has actual texture, light that falls off the way light does, hands that survive zooming in, the small asymmetries that make a face read as a person instead of a render. These two miss least, by a wide margin. When an image is going somewhere that matters, I use one of them and don't gamble.
The value pick is Kling O1, which punches far above its 20 credits. Skin, hair and faces come out photographic rather than illustrated, which is exactly why our selfie-style shortcuts run on it. It won't beat the two at the top on their best day, but at a quarter of the price it gets you most of the way there. Budget about half a minute per image.
The odd pair in the lineup is Qwen. On paper, Qwen 2 Pro at 60 credits is the premium version of Qwen 2 at 30. In practice the Pro model is also twice as fast: sixteen seconds against thirty-five. I don't have a good explanation for that, but the conclusion is easy. If you're choosing Qwen at all, choose Pro.
Qwen has one more trick that's easy to miss: it's the only model here with a true negative prompt, an actual parameter for things you want kept out of the image. Every other model gets your "no hats, no glasses" folded into the prompt text and treats it as a polite suggestion.
The all-rounders
The Nano Banana family (Google's Gemini image models, if you're keeping score) is the default for a reason, but it has a split personality that's worth understanding before you spend 80 credits on the wrong half.
Nano Banana Pro's superpower is consistency. Give it the same character twice and the same person comes back: the same face, the same features, the same presence. Nothing else in the picker holds a face across renders the way Pro does, which makes it the model to build a recurring character on. Pair that with the photorealism crown it shares with GPT Image 2, and its 80 credits are easy to defend.
Now the flaw, and I'll be blunt because this one costs people real credits: Pro is terrible at following detailed instructions. Hand it a precise brief, the cup handle facing left, exactly three buttons on the coat, logo in the top-right corner, and it hands back a gorgeous image that ignores half of it. It's an artist with opinions, not a technician. The test grid at the top catches it red-handed: same brief as everyone else, and Pro moved the book away from her face, crossed her legs and reframed the whole shot into the photo it would rather have taken. Arguably the prettiest image in the grid. Also the least obedient.
So when the brief is detailed, take it to GPT Image 2 Medium or High. They're the best instruction-followers in the lineup, and it isn't close. In the bookshop test, both GPT renders kept every single constraint, and they were the only ones that printed a legible book cover while doing it. Nano Banana 2 is the budget route: it listens far better than Pro and turns around in thirteen seconds, but its output sits a clear quality step below GPT Image 2 Medium and High. Fine for iterating on a fussy brief, a compromise for the final. And since editing an existing image is nothing but detailed instructions, the same ranking applies when you're editing.
Two family perks worth knowing. Batch mode cuts every Nano Banana price in half, so Pro drops to 40, Nano Banana 2 to 30, and the Lite model to 15, the cheapest volume in the app. And one honest limitation: the Gemini-based models flatly refuse to draw real public figures. That's policy, not a bug, and no clever phrasing gets around it.
Where Flux fits
Flux 2 Pro is the specialist I reach for when the subject is the surface itself. Fabric weave, brushed metal, food photography, product close-ups. It renders detail with a patience the faster models don't have, and I mean that literally: about a minute per image, starting at 25 credits and climbing with resolution. Not the model for exploring ideas. Very much the model for the final render of something tactile.
How I'd spend 500 credits
Say you need one great image and you have 500 credits.
The blind approach is six Nano Banana Pro rolls and hope. That's 480 credits, and if the concept itself is off, you're finding out at 80 credits per lesson.
The better approach: ten quick rounds on Z-Image Turbo, 50 credits total, to find the composition, the pose, the light. Then one batch of four on Nano Banana Pro, 160, from the winning prompt, or a couple of GPT Image 2 High renders instead if that prompt turned into a detailed brief along the way. You've spent about 210, you've seen fourteen images instead of six, and every expensive render was aimed at something you'd already confirmed works.
Draft cheap, finish expensive. That single habit outperforms every model opinion in this post.
The model is the last twenty percent
Here's the uncomfortable truth about model comparisons: a specific, photographic prompt on the 5-credit model beats a vague prompt on the 200-credit setting every single time. If your images keep coming out generic or fake-looking, the fix is almost never in the picker. It's in the prompt, and I wrote up the six biggest prompt-level tells separately.
The nice thing about writing one good prompt is that the models become interchangeable. In Image Prompt Maker, the same persona and scene render on any of the twelve, so moving from a draft model to a finishing model is one click rather than a rewrite. Try the cheap-then-expensive loop once and you'll never blind-roll a premium model again.
