AI Image Model Comparison in 2026: Same Five Prompts, Four Models, Scored Side by Side

Every AI image model looks great in its own launch post. The real question is what happens when you give four of them the exact same prompt, then count how many tries it takes to get something you'd actually publish. Most comparisons skip that second part, and it's where the money goes.

My name is Artem, and I run the Writingmate blog. I spend a lot of time switching between image models for product shots, social graphics and thumbnails, so I've stopped trusting single-sample comparisons. This post gives you a repeatable test: five prompts, four models (Flux, Seedream, Ideogram and Recraft), a scoring rubric, and a retry-cost formula. You can run it yourself on the Writingmate text-to-image page in about 30 minutes.

One honest note up front: I'm not going to hand you a made-up leaderboard. Image models change versions often, and your prompts matter more than a stranger's. What I can give you is the method, the public data points I could verify, and a worked example so the math is clear. The scores are yours to fill in.

How the test works (and why one sample proves nothing)

Image models are stochastic. Run the same prompt twice and you get two different images, sometimes one great and one unusable. Even the sites that publish comparisons admit this: one pricing comparison I read (Gradually's Seedream vs Ideogram page) notes that its capability scores come from four sample tests with one archived output per model, so they're "indicative rather than conclusive."

So the fix is simple: generate more than one image per prompt, and judge the whole batch. Here's the setup I use:

• Same prompt, word for word across all four models. No per-model prompt tuning in round one.
• Four attempts per model per prompt. That's 5 prompts × 4 models × 4 attempts = 80 images. If that's too many, do two attempts and accept noisier results.
• Same aspect ratio (I use 1:1 for products and portraits, 16:9 for the illustration).
• Score blind if you can. Have a teammate rename files 1 to 80 so you don't favor the brand you like.
• Log every attempt, including the failures. The failures are your retry cost.

Pick the models from the Writingmate models page so all four sit in one workspace and you aren't juggling four accounts and four billing pages.

The five prompts to copy

Each prompt stresses a different weakness. Together they cover most of what people actually use image models for.

1. Product shot: "A matte black ceramic coffee mug on a pale oak table, soft window light from the left, shallow depth of field, visible steam, no logo, 1:1 commercial photo."
2. Text in image: "A vintage-style poster that reads 'OPEN LATE' in large red letters, with 'Fresh bagels, 6am to midnight' in smaller text underneath, cream background."
3. Portrait: "Close-up portrait of a woman in her sixties with silver hair and laugh lines, natural window light, 85mm lens look, visible skin texture, five fingers on any visible hand."
4. Illustration: "Flat vector illustration of a small team around a whiteboard, limited palette of teal, coral and cream, consistent line weight, no gradients."
5. Edit-style prompt: Upload your product photo from prompt 1 and ask: "Keep the mug exactly the same, change the table to dark walnut, and add a small green plant at the back right." Models without an edit mode will regenerate instead, which is itself a finding.

For prompt 5, use the same source photo for every model that supports image input. If one doesn't, mark it "n/a" rather than comparing apples to oranges.

The scoring rubric

Score every image from 0 to 2 on each of the first four criteria, then calculate cost separately. Keep it fast: under 15 seconds per image.

Criterion	What you're checking	0 / 1 / 2
Prompt adherence	Every named element is present (steam, left light, teal/coral palette)	Misses 2+ / misses 1 / all present
Text accuracy	Exact spelling, spacing, no phantom letters	Garbled / one error / perfect
Realism or style fit	Hands, skin, shadows, or consistent line weight for illustration	Obvious flaw / minor flaw / clean
Consistency	How many of the 4 attempts are acceptable, not just the best one	0-1 / 2 / 3-4 usable
Cost per usable image	Total spend ÷ number of images scoring 6+ out of 8	Calculated, not scored

A "usable" image is one you'd publish without another generation. I define that as at least 6 of 8 points. Adjust the threshold if your standards are stricter, but keep it identical across models.

What the public data already tells you

Before you spend credits, it helps to know what to expect. These are the verified data points I found, with their limits stated.

• Seedream 5.0 Pro vs Ideogram 4.0: Gradually's comparison lists arena pricing of $0.09 per image for Seedream 5.0 Pro and $0.06 for Ideogram 4.0 at 1,024 × 1,024. It gives Seedream the higher text-to-image arena score (1,078 vs 1,004 Elo) and a much stronger product photography result (70.1 vs 12.7 out of 100), while Ideogram scored higher on typography and layout (58.6 vs 48.3). Treat those as hints, since they come from a handful of samples.
• Recraft's pricing: Recraft's own comparison post lists plans from a free tier of 50 images per day up to $60/month for 8,400 images, which works out to roughly $0.007 per image on the top plan by simple division.
• Ideogram's reputation for text: The Ideogram v3.0 launch got attention on X, for example in this post by Brett Adcock, and typography is the claim the product is built around.

Be careful with vendor claims too. Recraft's blog says of its own model:

"The model guarantees flawless results with every prompt, a feature exclusive to Recraft." — Recraft comparison post

"Flawless with every prompt" is exactly the type of statement your prompt 2 is designed to test. I'd be surprised if any model hits it every time, which is why you run four attempts instead of one.

For community reality checks, I like browsing r/StableDiffusion, where people post failure cases and settings for open-weights models like Flux, and the Midjourney vs Flux vs Ideogram test video above, which shows the same side-by-side idea in motion.

Your scorecard template

Copy this into a spreadsheet. Fill the cells after you've run the prompts, one row per model per prompt.

Prompt	Flux	Seedream	Ideogram	Recraft
1. Product shot (usable of 4)	__ / 4	__ / 4	__ / 4	__ / 4
2. Text in image (usable of 4)	__ / 4	__ / 4	__ / 4	__ / 4
3. Portrait (usable of 4)	__ / 4	__ / 4	__ / 4	__ / 4
4. Illustration (usable of 4)	__ / 4	__ / 4	__ / 4	__ / 4
5. Edit-style (usable of 4)	__ / 4	__ / 4	__ / 4	__ / 4
Total usable (of 20)	__	__	__	__
Cost per usable image	$__	$__	$__	$__

The retry-cost math

This is the part that changes decisions. The sticker price per image isn't what you pay. What you pay is:

Cost per usable image = price per attempt ÷ share of attempts that are usable

Here's a worked example using the arena prices above and hypothetical hit rates, to show how the formula behaves. These hit rates are assumptions for illustration, not my measurements:

Scenario	Price per attempt	Usable rate (assumed)	Cost per usable image
Cheaper model, 1 in 2 usable	$0.06	50%	$0.12
Pricier model, 3 in 4 usable	$0.09	75%	$0.12
Pricier model, 1 in 2 usable	$0.09	50%	$0.18
Budget plan, 1 in 4 usable	$0.007	25%	$0.028

Two lessons from that table. First, a model that costs 50% more per attempt breaks even if it succeeds 50% more often. Second, a very cheap model can still win on cost per usable image even at a poor hit rate, as long as you don't count your own time. And you should count it: if reviewing and re-prompting takes a minute per attempt, at a $30/hour rate that's $0.50 of labor per attempt, which dwarfs every price in the table. For client work, hit rate beats sticker price almost every time.

Don't forget to compare against plan structure, too. If you're paying for credits separately at each vendor, that's another reason to run all four from one place. Check the Writingmate pricing page to see how image generation is covered on each plan (image generation is paid-only as of October 2026).

Which model to default to

I won't name a winner before you've scored your own batch, but here's how I'd read the results once you have them:

• If one model leads prompts 1 and 3 (product and portrait), make it your default for photo-style work.
• If one model leads prompt 2 (text), keep it for posters, thumbnails, packaging mockups and anything with a headline. Ideogram's positioning makes it the one to beat here, so if it doesn't win, that's worth knowing.
• If one model leads prompt 4 (illustration), that's your pick for decks, blog art and icon-style assets. Recraft is built around vector and brand-style output, so I'd watch for it here.
• If one model can edit (prompt 5) without regenerating the whole scene, give it the revision work, even if it ties on everything else.
• If results are within one usable image of each other, pick the cheaper cost per usable image and move on. Don't agonize.

In my own workflow I keep two defaults, one for photographic images and one for anything with text, rather than hunting for a single "best" model. If you want the by-job overview first, my earlier post on which generator wins per job covers that. This post is the evidence-gathering step that comes after.

Common mistakes that skew your results

• Tuning prompts for one model. If you rewrite the prompt for your favorite, you're testing yourself, not the model. Do a second round with per-model tuning only after round one.
• Judging the best image instead of the batch. Consistency is what you pay for.
• Ignoring resolution and aspect ratio. Different defaults change both quality and price.
• Testing only pretty prompts. Include one ugly, boring, specific brief like prompt 2. That's the work you'll really do.
• Never retesting. Models update. I rerun this test whenever a new version of my default ships.

The bottom line

Run the five prompts, score the batch of four, and divide your spend by usable images. That one number beats any ranking article, including mine. Start on the text-to-image page, put all four models side by side, and keep the spreadsheet.

See you in the next one!

Artem