There is no single best AI image generator, and anyone who tells you otherwise is selling one. The models have genuinely different aesthetics, and the right choice depends on what you are making.
Here is how to think about it.
Match the model to the job
| What you want | What to look for |
|---|---|
| Photorealism | A model tuned for photography — convincing lighting, materials, skin |
| Illustration / design | A model tuned for flat art and stylization |
| Editing an existing image | An editing model, which is a different skill entirely |
| Text inside the image | The newest model you have access to; check every time |
| A consistent character | A model known for identity consistency across edits |
Photorealism — you want an image that could pass as a photograph. Product shots, people, interiors. The models tuned for this produce convincing lighting and materials; the ones tuned for illustration will give you something subtly plasticky that you will notice only after you have published it.
Illustration and design — flat art, icons, stylized scenes. A different set of models is better here, and a photorealism-tuned model will fight you, adding depth and texture where you wanted flatness.
Editing an existing image — a genuinely different task from generating one. You want a model built for it, which will change what you asked and leave the rest alone. Google's Nano Banana is the current standout.
Text inside the image — the historical weak point across the whole field. It has improved a lot. It is still the first thing to check before you ship anything.
What actually improves your results
The model matters less than people think. These matter more:
Be specific about the medium. "Photograph, 35mm, natural light" and "flat vector illustration" get you to completely different places, faster than any amount of adjective-stacking. Naming the medium is the highest-leverage word in most prompts.
Describe the composition. Where things are, what is in focus, what the camera is doing. Models are much better at following spatial instruction than they used to be — "subject centred, shallow depth of field, background falls away" is instruction they can actually use.
Set the lighting. "Soft window light from the left", "harsh midday sun", "studio softbox". Lighting does more for perceived quality than any other single descriptor, and it is the thing amateur prompts most often omit.
Iterate instead of restarting. If an image is 80% right, edit it. Most people regenerate from scratch and lose the 80%.
Say what you don't want. Cluttered background, no text, no watermark.
Generate several. These models are not deterministic. The same prompt four times gives four images, and picking the best of four beats perfecting one prompt.
A prompt, built up
Watch what each addition does. Starting point:
a coffee cup
You will get something generic — a mug, centred, ambiguous lighting, probably a café-stock aesthetic.
photograph of a white ceramic coffee cup
Now the medium is set, which rules out illustration and painterly output.
photograph of a white ceramic coffee cup on a light oak table, soft window light from the left, shallow depth of field
Medium, subject, surface, lighting, and lens behaviour. This is where most of the quality gain happens.
…, no text, no logo, background softly out of focus
Exclusions last. You now have a usable product-style image, and none of it required the words "stunning", "hyperrealistic", or "8k".
Common mistakes
Stacking adjectives. "Beautiful stunning amazing hyperrealistic 8k masterpiece" does very little. Concrete nouns and camera language do a lot.
Expecting exact counts. "Five people" often produces four or six. Models are weak at precise quantities, and no phrasing reliably fixes it.
Not checking hands, text, and reflections. The three places artifacts survive a casual glance.
Judging a model on one prompt. Model strengths are style-specific. A model that loses on your portrait prompt may win decisively on your product shot.
Assuming one model does everything. The single most common and most expensive mistake, because it usually means paying for a subscription that is wrong for half your work.
Things no model does well yet
Set expectations here and you will waste less time:
- Long or precise text in an image. Short words sometimes; a paragraph, no.
- Exact brand colours. You will get close, not exact. Composite in a real editor if it must match.
- Reliable counts of anything.
- Consistent characters from scratch. Generating "the same person" twice from a text prompt does not work. Generate once, then edit — that is what editing models are for.
- Diagrams and infographics where the relationships have to be correct.
The cost problem
Serious image work means trying the same prompt across a few models, because you often cannot predict which one will nail a given style. That is exactly the workflow that separate subscriptions make expensive — you end up paying three times to do one job.
Trying them
All Chatbots AI includes multiple image models on one plan, plus image-to-image editing, so you can generate in one and refine in another without switching accounts.
Common questions
Which AI image generator is best? There is no single answer. Photorealism, illustration, and editing are three different jobs with different best-in-class models.
Which is best for editing existing photos? A model built for image-to-image editing. Nano Banana is the current standout for keeping the subject consistent.
Can AI image generators do text? Better than they used to, still unreliable. Always check before publishing.
Why do I get different results from the same prompt? They are not deterministic by design. Generate several and pick.
Do I need a separate subscription for each model? Not if you use a service that bundles several on one plan.
Can I use the images commercially? Usually, but terms differ by provider and change. Check for anything client-facing.
How do I get a consistent character across images? Generate one good image, then use an editing model to vary it. Text prompts alone will not reproduce the same person twice.
What resolution do I get? Varies by model and tier. For print, plan to upscale, and check the result at full size before committing.