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FASHN vs MODA AI for Shopify Fashion Catalogs
One run on FASHN returns one photograph. One run on MODA returns nine.
Updated August 2, 2026 · Verified against FASHN’s free plan, pricing page and API docs · 9 min read
A very good image generator, pointed at a different job
FASHN calls itself an AI Fashion Studio for Brands & Creatives, and what it is genuinely known for is virtual try on. It trained that model in house and sells it as a developer API with TypeScript and Python SDKs, which is why you keep finding FASHN underneath other people’s try on features. The web app wraps the same engine in a studio: Product to Model, Try-On, Model Swap, Packshot, Face Swap, Edit, Reframe, Image Upscale, Image to Video. You load a picture, describe what you want, and press Run.
We gave both tools the same real product: a two piece bleached denim set, peace print shirt and cut off shorts, photographed flat on the floor at home, front and back. FASHN’s picture came back good. Better than we expected, and we will show it at full size.
Picture, singular. That is the whole of this comparison, and it is not a criticism of the rendering. It is the shape of the tool.
The difference in one screen
One run in. One photograph out.
In FASHN’s Studio you get one image slot, one prompt box and a Run button. Press it and one picture comes back, and one credit comes off. Across our session the counter went from 10 down to 7. Want a second angle? That is a second run, a second prompt and a second credit, and the model, the light and the setting are all rolled again. On the API you can raise num_images to 4, but those are variations on the same sentence, not a spread of angles you asked for.
MODA asks for more up front and then does the whole job at once. A front flat lay, a back flat lay, a face reference. A setting. Then a shot list, where you pick the camera angle and the pose for every frame. One run. Nine pictures, on one model, in one studio. Ten is the standard set; we ran nine here to keep the test tidy.
Here they are like for like. One run each, same garment, same money.
FASHN
One run, one credit
FASHN output, August 2026, reproduced for comparison. Prompt: white shoes, chic female french 21 year old model.
MODA AI
One run, one credit
MODA output from the same two floor photographs plus a face reference. Front facing, full length.
Call that a draw. Both cost about the same, too: the FASHN picture is roughly a dollar of credit at 2K quality with a face reference, and the MODA run is one credit, between 83 cents and a dollar twenty five.
The difference is that FASHN has now finished, and MODA has not. The same run returned these eight as well.
Back view, over the shoulder
Three quarter, top focus
Seated on a stool
Walking, mid stride
Movement, arms open
Side profile, full length
Movement, low angle
Seated, top focus
Same model, same studio, same garment. Every angle picked from a dropdown before anything was generated. On FASHN these would be eight more runs, eight more prompts, and eight more rolls of the dice on the model.
What went in
Two photographs, taken on a floor
No studio, no lightbox, no steamer. This is what a small brand actually has: a flat lay, shot from above on the floor, once from the front and once from the back. Both tools got the same two files. Worth a close look at the shorts in the second one, because that is where this comparison ends up.
Front
Back
Asking for the second picture
So we went back for the back view
Every product page needs one, and for a co-ord it carries the pocket, the yoke and the waistband. It is also one of the shots a listing is expected to have. On FASHN that means another run. Here is where the one image slot stops being a detail about the interface and starts being a problem with the picture.
The product-to-model endpoint takes a single product_image. One slot, no second one for the back of the same piece. So the only route to a back view in the Studio is to send FASHN’s own front render into Edit and ask it to turn the model around. You can see it below: the source panel is labelled Image, and the thumbnail is the render, not the garment. Our back photograph is not in the job at all.
FASHN Studio, August 2026. The back view is generated from the front output. Click to expand.
Here is what came back, against the photograph it never saw.
The real back
The second photograph we uploaded
A shirred elastic waistband, right across. One patch pocket.
What FASHN returned
A different pair of shorts
FASHN output, August 2026, reproduced for comparison. A rigid belt looped waistband. Two pockets.
The elastic is gone, replaced by the stiff belt looped waistband you would find on a pair of jeans. The single pocket has become a symmetrical pair. A shopper reading that image is being told the shorts fit in a way they do not.
The shirt changed length between the two runs as well. In the first render it hangs long and untucked, past the waistband. In the second it stops at the natural waist, cropped, with the whole waistband exposed below it. Same tool, same session, same product photo. They cannot both be this shirt, and the real one is long.
First run
Shirt long and untucked, waistband hidden
Second run
Shirt cropped at the waist, waistband exposed
None of this is FASHN having a bad day. Asked to draw a back it has never seen, from a picture of a front, a rigid waistband and a matched pair of pockets are perfectly sensible guesses. The problem is that nobody showed it the photograph that was sitting right there.
The front waistband, close up
Where it could see, it did well
Worth being precise, because the front is a fair fight. The real shorts have a shirred elastic waistband, a drawstring, a shank button and an open zip fly. FASHN got the shirring and the drawstring right. It left out the button and the fly.
The real garment
Shirred waist, drawstring, shank button, open zip fly
FASHN
Shirring and drawstring right. No button, no fly.
MODA AI
Shirring, drawstring, button and fly all held
A missing button is a small thing. It is only worth showing because of the contrast: given the photograph, both tools got most of it. Given no photograph, one of them invented a waistband.
How you drive each one
A prompt box, or a shot list
FASHN gives you a text field and a Run button. Type the model, the shoes, the mood. There are Face Reference, Image Prompt and Background buttons alongside, and they work, but the framing of the picture comes out of your sentence. There is no camera angle parameter anywhere in the product or the API. Ask for a side profile in words and hope.
FASHN Studio, free plan, August 2026. One image slot, one prompt, one output. Click to expand.
MODA makes you build the shot list before it generates anything. The setting comes from preset menus you can edit, or from a background you upload. Accessories are chosen for tops, bottoms or one piece.
Setting, accessories and model, from presets or your own references. Click to expand.
Four presets, each prefilling ten shots you can reorder or edit. Click to expand.
Then every shot in the set gets its own camera angle and its own pose, from dropdowns. Front facing, three quarter, side profile, seated, top focus. That list is the reason nine pictures come back looking like one shoot.
Camera angle and pose, chosen per shot, up to ten. Click to expand.
That is the difference in one line. FASHN is a very good camera with no tripod head. MODA is a shot list that happens to have a camera attached.
Which tool
Choose FASHN if / Choose MODA if
Choose FASHN if
- You want virtual try on. It is what FASHN built, and MODA does not offer it.
- You have engineers and want generation inside your own product rather than someone else’s app.
- You want one strong hero image, not a full product page set.
- You need the wider toolkit: model swap, face swap, packshot, reframe, image to video.
Choose MODA if
- You need a whole product page set, not one picture at a time.
- You photographed the back and you want it read rather than guessed.
- You want to name the angles: front, back, three quarter, side, seated, detail.
- You sell on Shopify and want it inside Admin, billed through Shopify, with no subscription.
Real world scenario
Thirty co-ords, on the same model, by Friday
A summer drop. Thirty two piece sets, each photographed front and back on the floor as flat lays. You want one house model across all of them and a product page set for each, the way a wholesale line sheet runs. That is 270 pictures.
| Step | MODA AI | FASHN |
|---|---|---|
| Runs to launch | 30, one per product | 270, one per picture |
| Use the back photo | Second input on the same run | No slot for it; the back is inferred |
| Get the angles you need | Chosen per shot before generating | Described in a prompt, one run at a time |
| Hold one model across 30 SKUs | Face reference, included | Face Reference, +2 credits an image, Agency plan |
| Getting it onto Shopify | Runs in Admin, publishes to the product | Download, or build on the API |
Flip it. One campaign image, art directed, for a lookbook cover. FASHN gets there faster and the result may well be prettier.
The eight differences that matter for a Shopify catalog
From FASHN’s studio on the free plan, its published pricing, and its API reference, checked August 2026.
| MODA AI | FASHN | |
|---|---|---|
| Pictures per run | A 10 shot set, angles decided before you start | One in the Studio; up to 4 on the API, all one prompt |
| Garment images per run | Front and back of the same product | One product_image; no slot for the back |
| Camera angle control | Picked per shot: front, 3/4, side, seated, top focus | No angle parameter; prompt and image_prompt only |
| Locking the model | Face reference included, held across the set | Face Reference: +2 credits per image, Agency plan only |
| Setting and styling | Preset menus plus background and accessory references | Free text prompt, plus background and image references |
| Where it runs | Shopify Admin, billed through Shopify | Own web app, or your own build on their API |
| Virtual try on | Not offered | The core product, and an in house model |
| Developer API | No public API | REST API with TypeScript and Python SDKs |
What one product costs on each
A credit means a different thing on each tool, so the sticker prices do not line up. Below is the same job on both: nine catalog shots of one co-ord, on one model that stays the same across all nine.
FASHN, matching the nine
Product to Model at 2K quality, one model held
- Nine separate runs, nine prompts
- 2 credits an image at 2K quality, plus 2 for the Face Reference
- 4 credits an image, so 36 credits for the nine
- Face Reference is Agency only, so 99 dollars a month
- Roughly 2.38 dollars of credit for this one product
- Drop the face reference and it falls to 18 credits, but you get nine different women
- The back view still comes from the front render
MODA AI, one credit
Ten shots per credit. We used nine.
- One run, from 0.83 to 1.25 dollars depending on pack size
- Up to 10 catalog shots from that one run
- 2K hero and 1K supporting shots, with all 2K or all 4K available
- Face reference included, no surcharge and no plan gate
- Background reference holds the scene across the set
- A ten second video for one more credit
- No subscription, no expiry, billed through Shopify
MODA pricing at a glance
Free trial
2 credits
via the Shopify App Store
Starter
$1.25 / credit
10 shots plus video per credit
Growing
$0.91 / credit
$20 for 22 credits
Scaling
$0.83 / credit
$50 for 60 credits
No subscription. No expiry. Billed through Shopify.
FASHN’s own tiers are 10 free credits to start, then 19 dollars a month for 200, 49 for 750 plus 50 daily, and 99 for 1,500 plus 100 daily, with top ups at 0.10 a credit. On demand API access is 0.075 a credit with no subscription at all, which is a fair price for what it is. Current numbers are on fashn.ai/pricing; the plan gate on custom Face References is what their pricing page states in August 2026.
Credit where it is due
Where FASHN is the better pick
- Virtual try on. This is their thing, the model is theirs, and MODA does not do it at all. If you want shoppers seeing your clothes on themselves, FASHN is the answer and we are not in the running.
- A real API. REST, with TypeScript and Python SDKs, on demand at 0.075 a credit. If you have engineers and want generation inside your own product, that is exactly the right shape. MODA has no public API.
- The picture itself. We prefer our own 2K frame to their base 1K trial shot, and the reasons are specific: at the waist ours holds the drawstring, the shank button and the zip fly, where theirs keeps the drawstring and drops the other two, and the even studio light reads truer on indigo than their warm plaster set. That is a preference, and a narrow one. Of every tool we have put this garment through, FASHN’s 1K trial output is the best of them.
- Range. Model Swap, Packshot, Face Swap, Reframe, Image Upscale, Image to Video, an agent, an iOS app. Great for multiproduct teams doing beauty, toys and bags alongside clothing. MODA AI is built specifically for garment bulk imagery.
- Not on Shopify. If you sell elsewhere, or on a marketplace, or you are an agency working across platforms, MODA’s Shopify wiring is no use to you and FASHN’s absence from the App Store is not in your way.
“Great app, handled our embroidered Indian outfits well, I was impressed. Service is great, and the team has been quick to answer all my questions.”
Bubber Couture
India · 3 months on MODA AI · Feb 23, 2026
Read all reviews on the Shopify App Store →Frequently asked questions
How many images does FASHN give you per run?
One, in the Studio. You load a garment image, type a prompt, press Run, and a single picture comes back for a single credit. Our free plan counter fell from 10 to 7 across the session. The API lets you set num_images up to 4, but those are variations on the same prompt rather than a set of different angles. MODA returns a 10 shot set from one run, with the camera angle chosen for each frame before you start.
Can FASHN use a back photo of the same garment?
Not as a garment input. The product-to-model endpoint takes a single product_image, and there is no second slot for the back of the same piece. In the Studio the only way to reach a back view is to send FASHN's own front render into Edit and ask it to turn the model around, which is what we did. It then draws the back from what it can infer, and your back photograph never enters the job.
Does FASHN let you pick a camera angle?
There is no camera angle parameter. Framing comes from the text prompt and from an optional image_prompt that guides pose, environment and lighting. You can steer it, but you cannot lay out front, three quarter, side profile, back and detail crop and get them back as a set.
Was FASHN accurate on the garment?
On the front, largely yes. It reproduced the print, the frayed hem, the shirred waistband and the drawstring correctly. It dropped the shank button and the zip fly, which are on the real shorts and which MODA kept. On the back, which it never saw, it replaced the shirred elastic waist with a rigid belt looped waistband and gave the shorts two back patch pockets where the real pair has one.
What does FASHN cost compared with MODA?
FASHN is a subscription: 10 free credits to start, then Basic at 19 dollars a month for 200 credits, Pro at 49 for 750 plus 50 daily, Agency at 99 for 1,500 plus 100 daily, with top ups at 0.10 a credit. Product to Model is 1 credit at 1K, 2 at 2K quality, 3 at 4K quality. A custom Face Reference adds 2 credits per image and is only available on the Agency plan. MODA charges per product: one credit is a 10 shot set, 0.83 to 1.25 dollars depending on pack size, no subscription and no expiry, billed through Shopify.
Is there a FASHN app on the Shopify App Store?
No. FASHN reaches Shopify through its API, which means a developer builds the integration, or through third party apps that use FASHN underneath. MODA installs from the Shopify App Store, runs inside Shopify Admin and bills through Shopify.
When is FASHN the better choice than MODA?
If you want virtual try on, FASHN is the specialist and MODA does not offer it at all. If you have engineers and want image generation inside your own product or pipeline, its API and SDKs are the point. If you want one striking hero image rather than a product page set, or you need model swap, face swap, packshot or image to video, FASHN covers far more ground. MODA does one job: catalog sets for fashion, inside Shopify.
The verdict
FASHN makes one picture beautifully. A product page needs nine that agree with each other.
FASHN is a serious piece of engineering and the picture it gave us was better than we expected. It is built around try on, sold as an API, and driven by a prompt, and all three of those are good reasons to use it. They are also why a catalog is hard on it. One run returns one image, so nine angles means nine runs. One garment slot means the back gets invented rather than read. No camera angle means a shot list becomes a series of sentences. Holding one model steady costs two extra credits an image and the top plan. MODA asks for the front, the back and a face, lets you name every angle, and returns the set in one go, inside Shopify. Use FASHN for try on, for API work, and for the hero image. Use MODA for the eight pictures that have to look like the same shoot.
Where MODA wins
Where FASHN wins
One upload. The whole product page.
Install MODA AI from the Shopify App Store. Two free credits, commercial ready. A front photo, a back photo and a face reference in; ten catalog shots out. From one dollar a batch.
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