Guide · · 6 min read
How to choose an AI image generator
They all make pretty pictures in the demo. The differences that matter only show up once you're working. Here they are.
By Manish
There is no best AI image generator, and every article claiming otherwise is picking a winner on one dimension and hoping you do not notice the others. The models have diverged into genuinely different tools that happen to share an input box.
What follows is the set of questions that actually determine which one fits, in rough order of how much they matter.
First question: what are you making?
This decides more than anything else, and most people skip it because they assume image generation is one capability.
- Concept art and mood exploration. You want aesthetic strength and interesting failures. Precision is not the point.
- Product and marketing imagery. You need consistency, commercial licensing, and the ability to place a real product in a scene.
- Anything with text in it. Logos, posters, thumbnails, packaging. This is a specific capability that most models are still bad at.
- Photorealistic people. The hardest category, and where the gap between the best and the rest is widest.
- Assets at volume. Game art, icon sets, illustration systems. Style consistency across hundreds of outputs matters more than any single image.
A model that is excellent at the first is frequently mediocre at the third. Picking on overall reputation rather than on your category is the most common mistake, and it is why people conclude the technology does not work when they have simply chosen the wrong instrument.
Text rendering is a real dividing line
If your images need legible words in them, this narrows the field immediately and dramatically. Most models still produce text that looks correct at a glance and dissolves into nonsense on inspection.
A handful were trained specifically for typography and they are meaningfully ahead. If you are making thumbnails, posters or anything with a headline, start from that shortlist rather than starting from the general leaderboard and hoping.
Test it with your actual words, not with the word the demo used. Short common words render far better than brand names, and brand names are usually what you need.
Consistency is what production work needs
Generating one beautiful image is a solved problem. Generating forty images that look like they belong to the same brand is where tools separate, and it is what almost all commercial work actually requires.
The capabilities to look for have specific names. Style references let you supply an image and get outputs matching its look. Character references keep the same person across scenes. Custom model training goes further, learning your style from a set you supply.
One striking image is a demo. Forty consistent images is a workflow, and only some tools can do the second.
Licensing, before you ship anything
This is the part that gets skipped and occasionally becomes expensive. The questions are simple and the answers vary substantially by provider.
- Do you own the output, or hold a licence to use it?
- Does commercial use require a paid plan? On several tools the free tier is explicitly non-commercial.
- Was the model trained on licensed data, and does the provider indemnify you if a claim arrives?
- Can you use it for client work, or only for your own?
For personal projects none of this matters much. For anything client-facing or brand-facing, the models trained on licensed libraries with indemnification attached exist precisely for this, and they are the correct choice even where the raw output quality is slightly behind.
The interface matters more than people admit
Image generation is iterative. You will run twenty variations to get one keeper, and the tool that makes iteration fast will beat the tool that produces marginally better single images.
Look at what happens after the first generation. Can you edit part of an image without regenerating the whole thing? Can you extend a canvas? Can you take a result and vary it, or do you have to start over? Inpainting and variation tooling saves more time than any quality difference.
Cost, and how it is disguised
Pricing is deliberately hard to compare. Some tools charge per image, some per month with a generation cap, most use credits where the credit cost varies by resolution and model.
Convert everything to cost per usable image before comparing, and be honest about the ratio. If you need twenty generations to get one you would actually ship, a tool at half the price with a worse hit rate is not cheaper.
How to choose in an afternoon
Pick three candidates from your category rather than from the general rankings. Write five prompts that represent your real work, including the awkward one you are worried about. Run all five through all three.
Judge on your own outputs rather than on gallery pages, which are curated from thousands of attempts by people who are very good at this. Then check the licence for the one that won before you commit.
Most people are surprised by the result, and the surprise is usually that the model everyone recommends is not the one that handled their particular work best. That is the whole reason to run the test rather than read the leaderboard.
The prompt is not the skill people think it is
There is a persistent belief that image generation rewards elaborate prompts full of camera specifications, lens lengths and artist names. That was true of earlier models and is much less true now.
Modern models handle natural description well and increasingly ignore the incantation-style prompting that circulated in 2023. Long strings of quality tokens, masterpiece, 8k, highly detailed, trending on artstation, mostly do nothing on current models and occasionally push the output toward a generic look, because that is what those tokens were attached to in training.
What still works is describing the subject clearly, saying what should not be in the frame, and specifying composition. Where the subject sits, what the light is doing, how close the camera is. Those are real instructions. The rest is superstition that outlived the models it worked on.
Where each model tends to fail
Knowing the failure modes is more useful than knowing the strengths, because you will meet the failures on your third prompt.
- Hands and small anatomy. Substantially improved and still the first place to look when an image feels wrong.
- Counting. Ask for exactly five objects and you will frequently get four or six. Models do not count reliably.
- Spatial relationships. To the left of, behind, on top of are followed loosely, and complex arrangements are close to unachievable.
- Consistent secondary detail. The same character across two images will have subtly different clothing unless you are using reference tooling.
- Negation. Saying no text often produces text, because the model attends to the concept rather than the instruction to exclude it. Use the dedicated negative prompt field where one exists.
Speed changes how you work
A model that returns in three seconds and one that takes ninety produce genuinely different working styles, and the difference matters more than a few points of quality.
Fast models let you explore. You run thirty variations, discover a direction you did not anticipate, and follow it. Slow models force you to commit before you have seen anything, which pushes you toward safe prompts and predictable results.
The productive pattern for most people is to explore on a fast model until the composition is right, then re-run the winning prompt on the slower high-quality one for the final render. Using one model for both jobs is usually the wrong trade in one direction or the other.
One thing to stop worrying about
People spend considerable energy choosing between models whose outputs they cannot reliably tell apart in a blind test. If you have narrowed it to two well-regarded options in your category, the remaining difference is smaller than the difference your own prompting will make in a week of practice.
Pick one, learn it properly, and revisit in six months. Familiarity with one tool beats shallow knowledge of four, and the field moves fast enough that a considered choice today will need revisiting anyway.
Compare image generators side by side
See prices, styles, good points and bad points before you pick one.
Compare Midjourney and Ideogram