There are now dozens of AI image generators, from chat assistants that draw on request to professional tools built into design software and open models you can run yourself. They differ far more than their marketing suggests. The right choice depends less on which model tops a leaderboard and more on what you need to make, how much control you need and what you are allowed to do with the results.

Start with the job, not the tool

Write down the three or four kinds of images you actually need:

  • Marketing visuals — social posts, banners, blog headers in a consistent style.
  • Product imagery — clean shots, lifestyle scenes, variations of a real product.
  • Concept and mood work — fast exploration before a designer takes over.
  • Illustration — characters, scenes or icons that must stay consistent across many images.
  • Photo editing — removing objects, extending backgrounds, relighting real photos.

A tool that excels at photorealistic concept art may be poor at consistent brand illustrations, and vice versa.

The criteria that matter

1. Prompt adherence. Does the image actually contain what you asked for — the right number of objects, positions, colours and text? Newer models follow complex prompts much better, but differences remain large on multi-object scenes and written text inside images.

2. Control. Professional work needs more than a text box: reference images, style presets, aspect ratios, seeds for reproducibility, inpainting (regenerating part of an image) and outpainting (extending it). Open models add fine-grained control through community tools.

3. Consistency. Keeping the same character, product or style across a series is still one of the hardest problems. Look for features that let you upload references or train a custom style on your own assets.

4. Editing. Tools integrated with image editors let you combine generation with selection, masking and layers, which is how most real production happens.

5. Rights and indemnity. Read the terms: who owns the output, whether commercial use is allowed on your plan, and whether the provider was trained on licensed content and offers legal indemnity to business customers. In many jurisdictions purely AI-generated images may not be protected by copyright, which matters if you need exclusivity.

6. Provenance. Some tools attach Content Credentials (the C2PA standard) that record that an image was AI-generated or edited. That supports transparency with audiences and may help with platform labelling rules.

7. Privacy and data use. Check whether your prompts and uploads are used to train future models, and whether a business plan turns that off.

8. Cost. Pricing ranges from free tiers with limits, to monthly subscriptions with generation credits, to pay-per-image APIs and the hardware cost of running open models locally.

A simple test you can run

  1. Pick five prompts from your real work, including one with text in the image and one that needs a consistent character.
  2. Generate four images per prompt in each candidate tool.
  3. Score each set on adherence, usable quality, edits needed and time spent.
  4. Check the licence terms for your intended use.

An afternoon of testing beats any ranking, because results vary so much by subject and style.

Open versus hosted models

Hosted tools are easier and often stronger out of the box. Open models such as those released by Stability AI and others can run on your own hardware, be fine-tuned on your style and keep data in-house, at the cost of setup time and a capable GPU. See our comparison of open and closed AI models.

Responsible use

Avoid prompts that imitate living artists or recreate trademarked characters, never create realistic images of real people in misleading situations, and label synthetic images where platform rules or context require it. Our explainer on how diffusion models work covers what happens behind the prompt.

What to watch next

  • Better text rendering and multi-object accuracy in new models.
  • Character and style consistency features for series work.
  • Wider adoption of Content Credentials in generators and platforms.
  • Court decisions on training data that could change licensing terms.

Key takeaways

  • Choose an image generator by the jobs you need done, not by leaderboards.
  • Prompt adherence, control, consistency and editing matter most in practice.
  • Check ownership, commercial use and indemnity before using images in business.
  • Content Credentials help show that an image is AI-generated.
  • A short test with your own prompts is the most reliable way to decide.

Frequently asked questions

Which AI image generator is best?

There is no single best one. Tools differ by style, control, editing and licensing, so test two or three on your real prompts.

Can I use AI images commercially?

Often yes, depending on the tool’s terms and your plan. Read the licence and check whether the provider offers indemnity for business use.

Do I need a powerful computer?

Not for hosted tools, which run in the cloud. Running open models locally needs a capable GPU with enough memory.