Most “model X vs model Y” articles end with a hedge: “it depends on your use case.” This one tries not to do that. We use all three regularly. Here’s what we’d tell a friend who asked.
TL;DR — pick by what you’re actually making
| If you’re making… | Use |
|---|---|
| Posters, ads, marketing creative with text | GPT Image 2 |
| Edits to existing photos | GPT Image 2 |
| Multilingual content (Chinese, Japanese, Korean, Arabic…) | GPT Image 2 |
| Concept art, fine-art illustration, dreamy cinematic style | Midjourney |
| Cheap, fast, throwaway visual filler | DALL·E 3 |
| High-volume artistic exploration on a budget | Midjourney (subscription) |
| Anything where the image needs to follow your instructions exactly | GPT Image 2 |
The rest of this post is the why behind that table.
How we tested
We ran the same prompts through all three models (GPT Image 2 via imagesv2, DALL·E 3 via ChatGPT, Midjourney v6 via Discord) across categories: posters with text, product mockups, photo edits, illustrations, multilingual designs. We weren’t timing the runs — we were looking at where each model was useful and where it was frustrating.
Text rendering: it’s not close
This used to be a hard problem for every model. Now it’s essentially solved by GPT Image 2 and still broken on the other two.
A simple test: prompt all three for a movie poster with the title “Journey to the Stars” at the top and “Coming Summer 2026” at the bottom.
- GPT Image 2 produces a poster with both lines of text correctly spelled, in the right positions, in a font that matches the cinematic vibe.
- DALL·E 3 produces a poster with something letter-shaped at the top that almost-but-not-quite spells the title, and gibberish at the bottom.
- Midjourney produces a beautiful poster with completely fake text.
If your output needs words inside the image, this is the only category that matters and it ends the debate.
Photo editing: only one model can do it
You upload an existing image, point to a region, and say what to change.
- GPT Image 2 does this natively. “Add a coffee cup on the table,” “change the shirt to navy,” “make the background a beach” — and the rest of the image stays intact.
- DALL·E 3 doesn’t support this at all. You can only regenerate from scratch.
- Midjourney has variations, vary regions, and upscaling — useful for art exploration, not useful for “fix this one thing in my existing photo.”
For e-commerce shots, real estate photos, product mockups, and headshot retouching, GPT Image 2 is the only serious option.
Aesthetic quality: Midjourney still has a soul
This is where it gets less one-sided.
Midjourney has been quietly training a very specific taste into its model for years: cinematic lighting, painterly atmosphere, color palettes that feel like they came from a film stock or an art book. When you prompt Midjourney for an illustration or a concept art piece, it makes something that looks like a person made it.
GPT Image 2 and DALL·E 3, in comparison, are more literal. They give you what you asked for — accurately — but they don’t add aesthetic surprise. The output is correct. Midjourney’s output is sometimes beautiful.
If you’re making fine-art prints, book covers, RPG concept art, or dreamy cinematic stills, Midjourney is still the right tool. It’s also the tool of choice for designers who use AI for inspiration and then redraw the results by hand.
Instruction following: GPT Image 2 by a clear margin
Take a five-clause prompt: “A wide-angle shot of a small Tokyo backstreet, two children with red umbrellas in the foreground, neon signs reflected in puddles, soft rain, golden hour light, slight film grain.”
- GPT Image 2 delivers something close to all six elements.
- DALL·E 3 keeps three or four, drops the rest, and adds bonus elements you didn’t ask for.
- Midjourney keeps the vibe but interprets the specifics loosely — beautiful, sometimes nothing like what you wrote.
For client work, branded content, or anything where “I needed it to do that thing I asked for” matters, GPT Image 2 is what you reach for.
Multilingual content: GPT Image 2, full stop
If you need text in Chinese, Japanese, Korean, Arabic, Hindi, or really anything outside the Latin alphabet inside the image, the other two models are non-starters. They’ll produce convincing-looking nonsense glyphs. GPT Image 2 produces correct, readable text in dozens of languages, often alongside English.
For brands operating across markets — DTC e-commerce, K-pop and J-pop content, anime promo posters, Chinese New Year campaigns — this changes the production economics. One model, multiple language variants, in minutes.
Pricing reality check
The three models have very different pricing shapes:
- GPT Image 2 — Pay per generation. On imagesv2, that’s credit-based, transparent before you click. Yearly plans land at roughly $0.0033 per credit on Pro, $0.0021 on Ultra. See our pricing breakdown.
- DALL·E 3 — Per image via OpenAI’s API or included in ChatGPT Plus. Cheapest if you only generate a few images a month.
- Midjourney — Monthly subscription only ($10/month basic up to $120/month Pro for fast hours and concurrency). Great value if you generate hundreds of images a month; bad value if you generate ten.
For occasional users, a $14.90 one-time pack on imagesv2 (1,000 credits, never expires) lets you avoid all three subscriptions and just experiment.
Speed
- GPT Image 2 — Medium. The model prioritizes accuracy over raw throughput, which is the right trade-off for most production work.
- DALL·E 3 — Faster, lower quality ceiling.
- Midjourney — Fast on the paid tiers (15 “fast hours” per month on Basic; Pro is essentially unlimited), with strong concurrent generation. If you’re iterating dozens of variants per session, this matters.
Where each one wins
To compress all of the above into a take you can hand to a colleague:
Use GPT Image 2 when you need the output to be correct. Marketing creative, product mockups, posters with real text, editing photos, multilingual content, anything you’ll actually ship. This is the default for most professional work today.
Use Midjourney when you need the output to be beautiful. Concept art, illustrations, mood boards, anything where the aesthetic is the product and small inaccuracies don’t matter. Still the king of taste.
Use DALL·E 3 when you’re already in ChatGPT and need a quick visual. It’s fine. It’s included with your existing subscription. Don’t overthink it.
Try GPT Image 2 on your own work
The fastest way to know whether GPT Image 2 fits your workflow is to put one of your real projects through it. Go to the imagesv2 playground, run the prompt you’d normally pay a designer to brief, and compare. The credit cost shows up before you confirm, so you can experiment without surprises.
If you want to validate end-to-end before subscribing, $14.90 buys 1,000 credits. That’s enough to test the model on a dozen real designs — enough to know.