Write one prompt, run it on GPT Image 2.5 Flare, Nano Banana Pro, Seedream 5 Pro and Ideogram v4 Quality, then judge the results next to each other. Choose the model that understood your idea instead of trusting a ranking written for somebody else.
Every image model has a favorite kind of picture, and none of them announces it. The fastest way to find out which one understands your idea is to give the same prompt to several of them and look at the results next to each other. This page shows how to do that on Picasso IA, how the toolkit handles several generations at once, and where judging by eye stops being enough.
Rankings and leaderboards answer the question of which model is best on average, for somebody else's prompts. You have one specific prompt: a product on a kitchen counter, a poster with a headline, a portrait in soft window light. A model that wins on average can still stumble on exactly that picture, and a model nobody mentions can nail it. The only way to know is to run it.
Picasso IA lists 502 models, and 212 of them are text-to-image, so the question is real: after the first handful of favorites, which of those 212 are worth your credits? Comparing is cheap compared with committing. You spend a few generations up front, and every later project starts from a model you chose on evidence you looked at yourself. New accounts get free credits, so the first round of comparing does not need a plan.
Here is how the toolkit actually behaves today, because it shapes how you compare. The toolkit runs one model at a time in its prompt box. There is no single button that sends a prompt to four models and draws a grid. What it does allow is firing generations in parallel: pressing Generate does not lock the form while the previous picture is still rendering, so you can submit on one model, switch to the next, submit again, and have several in flight together.
Three details matter in practice. The prompt text clears as soon as you submit, so keep your test prompt somewhere you can paste it from. Files you attached as references stay in place for the next submission. And the number of generations that can run at once is a limit on your account that depends on your plan: the toolkit shows these parallel slots next to the prompt box, dims the Generate button when they are all busy, and an active free trial runs one at a time. Finished pictures appear as separate cards in your creations feed, and opening one shows the model that made it and a button to copy its prompt.
Tip: paste the exact same prompt every time, character for character. If you reword it for each model, you are comparing your phrasing, not the models.
These four are all text-to-image models in the catalog, and they differ in ways you can read straight off their settings. Treat the table as a starting lineup, not a verdict.
| Model | What its settings offer | Worth testing when |
|---|---|---|
| openai/gpt-image-2.5-flare | Quality levels, optional transparent background, reference images, up to ten images per prompt | Your picture needs readable text or you want several options from one prompt |
| google/nano-banana-pro | 1K, 2K or 4K output, up to 14 reference images, 11 aspect ratios | You are working from reference photos or need a larger file |
| bytedance/seedream-5-pro | 1K or 2K output, up to 10 reference images, prompts up to 4000 characters | Your prompt is long and detailed |
| ideogram-ai/ideogram-v4-quality | Magic Prompt rewriting, a long list of fixed resolutions, optional structured prompt | You want the model to polish a rough idea for you |
One difference deserves a warning. Ideogram v4 Quality refines your prompt before generating, so what it renders is not strictly your wording. That is a feature when your prompt is rough and a confound when you are testing, so note it when you compare. The models also expose different size controls: some take an aspect ratio, others a fixed resolution, so match the shape as closely as each one allows. If the four do not fit your subject, browse the full catalog or the text-to-image collection and swap in others.
This is the routine that gets you from a vague preference to a choice you can defend, using nothing but the toolkit and a text file for your prompt.
Looking at four pictures and saying you like the third is a fine start, but a little structure keeps you from rewarding the lucky roll. Use the same checklist on every card.
If your picture is text-heavy, the same routine applies to poster design, where lettering decides the winner. And if you are weighing one specific rival product against the whole catalog, the Picasso IA vs Ideogram page covers that comparison.
This method is honest about what it is: a judgment by eye on your prompt, with a handful of generations. It cannot tell you which model is better in general, and nothing on this page claims that. One round is a small sample. Image models vary from run to run even with identical settings, so a model that looked worse on one try might win the next, which is why the repeat check above matters.
It also stops being useful when the test is unfair without you noticing. A prompt written in the style one model likes will favor that model. Different resolutions and aspect ratios change composition, so a wide frame beside a square one is not a clean comparison. And the toolkit cannot put four models in one grid for you, so you will be switching and remembering: keep notes on which card came from which model. Finally, a model that wins a still image test is not automatically the right choice for editing with reference photos or for batches that need one consistent look. If your project is a character that must repeat, test with that goal, as in consistent AI characters, rather than with a single pretty picture.
Yes, in the sense that matters. The toolkit runs one model per prompt box, but submitting does not lock the form while a picture renders, so you can send the prompt to one model, switch to another, send it again, and have several generations in flight together. How many can run at once depends on your plan, and the toolkit shows the slots beside the prompt box. It does not fan a single prompt out to several models with one click.
No. Each finished generation appears as its own card in your creations feed in the toolkit, and opening a card shows which model produced it and lets you copy its prompt. You compare by scrolling and opening the cards one after another. If you want a literal grid, you would assemble the saved pictures yourself in a layout or slide tool. Keep a note of which model made which card while you work, so nothing gets mixed up.
A reasonable first lineup is GPT Image 2.5 Flare, Nano Banana Pro, Seedream 5 Pro and Ideogram v4 Quality, because their settings differ in useful ways: text and quality levels, reference-image counts, resolution options and prompt rewriting. If your subject is narrow, such as a logo or a portrait, replace one of them with a model that fits it. The catalog and the text-to-image collection show what else exists.
Three or four is plenty for a first round. Fewer than three gives you a pair of pictures to argue about, and more than five makes the cards hard to hold in your head at once. If two models are close, run a second round with only those two and a different prompt. Narrowing in stages is cheaper than running a long list every time, and it keeps your notes readable.
No, and that is the point of comparing. Models read prompts differently: some follow long, detailed descriptions closely, some favor short ones, and Ideogram v4 Quality rewrites your text with Magic Prompt before it generates. Settings differ too, since some models take an aspect ratio and others a fixed resolution. Use identical wording and match the size as closely as each model allows, then treat the leftover differences as part of what you are judging.
Generation costs credits, and the cost depends on the model and the settings you choose, so every generation in your comparison uses credits, including the ones from the model you end up not picking. Some models are marked unlimited for certain plans, which changes the math. New accounts get free credits to start with. For current plan details and credit costs, check the pricing page instead of trusting a number written here.
Change one thing at a time, and here the one thing is the model. Use the same prompt word for word, the same reference images, the closest shape each model allows and the same resolution target. Avoid regenerating one model five times while giving another a single try, and avoid picking from thumbnails. Then run the winner again with the same prompt to check the result was not a lucky roll.
Yes, with the same routine. Several models accept reference images alongside the prompt: Nano Banana Pro takes up to 14, Seedream 5 Pro up to 10, and GPT Image 2.5 Flare can edit a photo you supply. Attach the same source image on each, give the same instruction, and compare how faithfully each one keeps the parts you wanted unchanged. Edits vary a lot between models, so this test is worth more than a text-only one if editing is your goal.
You do not, and anyone claiming a single answer without knowing your prompt is guessing. What you can know is which model produced the picture you preferred for this prompt, across a couple of runs. That is a useful answer, because it is yours. If your work changes, for example from photos to posters with lettering, run a new round, since a winner for one kind of picture does not carry over to another.
The all models page lists the whole catalog of 502 models, and the collection pages browse them by category, with 212 in text-to-image. Each model has its own page with its description, its settings and example output. Reading those pages before a round helps you pick a lineup that differs in useful ways, rather than four models that behave alike.
Ready to see which one gets your idea right? Open the Picasso IA toolkit, paste one prompt and run it on a few models.
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