AI Image Generators Compared: Which One for What

There are more capable AI image generators than any one person can keep up with, and most comparisons rank them on a single quality score that stops being true a month later. For a working creative the better questions are: how much control do I get, can it handle text, can I edit a result without starting over, and may I use the output for a client? This guide compares Midjourney, Flux, Ideogram, ChatGPT Images, Gemini, Adobe Firefly, Leonardo, Recraft and Stable Diffusion on those questions. Model names reflect the current interfaces; check each platform where a label may have changed.

The field at a glance

Control: parameters versus conversation

Generators split into two camps. The parameter camp gives you named settings: Midjourney’s --sref, --raw, stylise and chaos values; Stable Diffusion’s steps, guidance, sampler, seed and LoRA weights; Leonardo’s model, Elements and guidance strength. These reward people who like to tune and who need results to repeat exactly. A seed plus identical settings gives the same image again on most of these.

The conversation camp, led by ChatGPT Images and Gemini, takes a long plain-language prompt and then lets you say 'make the background darker and move the cup to the left'. There are few named settings, and exact repeatability is weaker, but the speed from idea to acceptable image is hard to beat. Flux Kontext sits between the camps: you supply an image and a written instruction, and it edits precisely while keeping what you did not mention.

Text, vectors and formats

• Ideogram renders legible text most reliably, which matters for posters, packaging and social graphics. See our Midjourney vs Flux vs Ideogram comparison for how that plays out on product work.
• ChatGPT handles text well too, and can output a transparent PNG, which saves a cutout step for mockups and overlays.
• Recraft is the one mainstream generator that produces true vectors, so a logo-style mark or icon set comes out as editable SVG rather than a raster you must trace.
• Midjourney remains weak on text. Treat any lettering it produces as placeholder.

Licence and provenance for client work

This is where generators differ most, and where a quick check saves a difficult conversation later. Three models exist.

1. Hosted with plan-based rights. Midjourney, Ideogram, Leonardo, Recraft, ChatGPT and Gemini grant usage rights through their terms, and those rights often differ between free and paid tiers. Read the terms for the plan you are on, and keep a record of which plan and model made each delivered image.
2. Licensed training data and provenance. Adobe Firefly is trained on licensed and public-domain material and attaches Content Credentials, a signed record of how the image was made. For clients with strict brand or legal teams, that is often the deciding factor. Gemini adds a SynthID watermark that marks the image as AI-generated.
3. Open weights. Flux dev and schnell and the Stable Diffusion family publish weights you run yourself, under licences that vary by model and version. Some are permissive for commercial use, some are non-commercial unless you buy a licence. Running locally also keeps client material off third-party servers. Check the specific model card rather than assuming.

Whatever the generator, note the platform, model version, prompt and date for every approved image. If a client later asks how an asset was made, that record is your answer.

How to pick for a project

• Mood boards and campaign looks: Midjourney, with an --sref to keep the look consistent.
• Exact product or scene description: Flux, then Kontext to adjust.
• Anything with a headline or label: Ideogram, or ChatGPT.
• Fast iteration by conversation, mockups with transparency: ChatGPT or Gemini.
• Risk-averse corporate clients: Firefly for its training data and Content Credentials.
• Icons, marks and brand systems: Recraft.
• Repeatable pipelines, trained looks, privacy: Stable Diffusion or Flux locally.

Try it

Run this on three generators from different camps and compare control, text and finish.

Editorial photograph of a ceramic teapot and two cups on a linen tablecloth, soft overcast daylight, warm neutral palette, slight film grain, 4:5 portrait framing, no text, no logo

In Midjourney, add --raw and note the change. In Flux or Stable Diffusion, fix the seed and change one setting at a time. In ChatGPT or Gemini, follow up with 'swap the linen for dark slate' and see how much of the original survives. Record each result with its model version; the next release will move the goalposts.