FASHN alternative for fashion brands

Compare FASHN and Uwear for fashion production.

Updated October 30, 2026

FASHN gives developers clean try-on and on-model endpoints. Uwear gives fashion teams the production line above them: direction, catalog runs, automatic QA, and agent-operated delivery.

Start generating Explore Uwear pricing

Which one to choose

Start from the job you actually have.

Choose Uwear

Choose Uwear when you shoot whole collections or a 40-piece drop. Your cast and art direction carry across every photo, each one is checked in seconds before it reaches you, and you pay only for what you make: no subscription, no plan tiers, no paid tier for parallel runs. Virtual try-on is also available through the Uwear API on request. Mid-market retailers in the UK, Europe and Latin America came to Uwear on their own.

Choose FASHN

FASHN is built for developers adding virtual try-on to their own product: documented try-on endpoints, SDKs and per-output pricing.[2][3]

Five differences

Where the two tools part ways.

Not a feature checklist. Each row follows the work through both tools, and every FASHN claim cites a page read on the access date.

Production axis	Uwear	FASHN
Art-directed production	Saved models and art directions reused by every run; up to 16 reference images per photo (14 on Gemini 2.1); 1K, 2K or 4K output; up to 15 aspect ratios.	Documents reusable model identities, inspiration and background references, prompts, and fixed seeds; public docs show no single direction object that bundles direction and acceptance criteria.[6][5]
Full-catalog volume	10,000 photos per batch in the app, 100,000 per API batch. No paid tier for parallel runs. About 100,000 images and videos generated in June 2026, and up to 6,600 in a single day.	Processes one product image per request with one to four outputs, at default limits of 50 requests per minute and six concurrent predictions; catalog orchestration is customer-built.[5][4]
On-model fashion video	10 video models, clips from 2 to 30 seconds, up to 4K, made from photos you approved.	Offers an Experimental image-to-video endpoint: one still becomes a 5- or 10-second clip at up to 1080p, chainable after a try-on or product-to-model step.[8][7]
In-loop automatic QA	Every photo checked against its product photo during the run, in about 6 seconds, at no credit cost, with the reason recorded for every rejection.	Documents user-led review: the Agent chains tools and iterates on request, and the API reports success or failure; no automatic acceptance criteria or visual retry policy is published.[7][4]
Price and access	70 credits ($7) minimum, $0.10 a credit, credits never expire. A 2K photo is 2 credits ($0.20) on GPT Image 2 (low), 3 credits ($0.30) on GPT Image 2.5 (Low) or 5 credits ($0.50) on Gemini 2.1, our default. No subscription, no feature tiers.	Publishes exact per-output credit tables at $0.075 per on-demand credit, with failed predictions free; agent access is an installable coding skill over REST, not a remote MCP server.[3][9]

Save the look once, reuse it on every run.

On Uwear the art direction, meaning the model, the set, the light, the framing and the rules the reviewer checks, is saved once. The next run, the next drop and the API all reuse it without anyone choosing it again.

FASHN gives developers reusable inputs: saved model identities, inspiration and background references, prompts, and fixed seeds for reproducibility. What its public docs do not show is one governed direction object that carries casting, framing, styling rules, and acceptance criteria together across a collection. Choose Uwear when direction must govern the run, not parameterize a request.[6][5]

Coordinate the full catalog, not just an endpoint.

A run on Uwear takes the product photos in, applies the saved look, checks and retries each photo, queues the approvals and delivers, up to 10,000 images, priced before it starts. Results arrive by download, through the REST API with webhooks, or over MCP from ChatGPT, Claude or Codex.

FASHN markets bringing a full catalog to life, and its API is automatable: async jobs, polling, webhooks, SDKs. But the public unit of work is one product image per request with one to four outputs, under default limits of 50 requests per minute and six concurrent predictions. The catalog logic (sequencing, QA, retries, delivery) is yours to build. Choose Uwear when you want the production system, not just the endpoint.[5][4][2]

Make the clip from the photo you approved.

The 5-second clip starts from an approved on-model photo, so it shows the same person and the same garment as the listing next to it, 23 credits with Kling 3 Pro.

FASHN also chains stills into video: its Experimental image-to-video endpoint produces 5- or 10-second clips at up to 1080p, and its Agent can run create-then-animate sequences. Choose Uwear when video must inherit an approved still inside the same QA-governed production job.[8][7]

Every photo checked during the run, automatically.

Uwear’s AI reviewer checks each photo against the product photo and the saved model while the run is still going, before anything reaches you, in seconds. It records a pass or fail with the reason, and with automatic retries on, it re-shoots what fails in the same run. The check costs no credits and needs no ticket, no plan tier and no wait. A photo that still fails is marked rejected, and a person can approve or override it in Studio.

FASHN documents user-led review: generate, look, refine, repeat, with an Agent that follows instructions and an API that reports success or failure. No automatic garment-fidelity scoring, acceptance thresholds, or visual retry policy is published. At catalog volume, that review labor is the hidden line item. Compare who checks the work: your team per output, or the production loop itself.[7][4]

Pay for the photos you make. No subscription.

A credit is $0.10. There is no subscription, no seat fee and no monthly minimum, so a quiet month costs nothing and a launch week costs only what it uses. The rate per photo and per clip is published for each image model, and every run shows its estimate before you approve it, including the most it can cost with one retry on every photo. The check costs no credits, and a retake costs the same as a new photo. From 2 credits ($0.20) on GPT Image 2 (low) or 3 credits ($0.30) on GPT Image 2.5 (Low) per 2K photo; 5 credits ($0.50) on Gemini 2.1, our default. A 40-piece drop with 3 photos each is 360 credits ($36) on GPT Image 2.5 (Low) or 600 credits ($60) on Gemini 2.1, and nothing to pay between drops. Start with 70 credits ($7); credits never expire. The same run can be started from ChatGPT, Claude or Codex through the Uwear MCP server. Enterprise terms for volume and invoicing are quoted separately.

FASHN publishes per-output API prices: $0.075 a credit on demand, $7.50 minimum, failed predictions not charged. A 2K Product-to-Model image is 2 to 4 credits, and keeping one face across the drop adds 3 credits an image with Face Reference, so a 40-piece drop with 3 photos each is about $45 to $63 of API credits, with the sequencing, QA and delivery left for your team to build. The difference is what the credits operate and who drives them. Uwear credits pay for the run around each generation, with the saved direction, the reviewer and the retries attached, and an assistant can run it through the MCP server with a priced plan you approve before generation. FASHN offers a coding skill for developers to build against REST.[3][9]

Decision guide

Choose the workflow that matches your team.

Choose Uwear for self-serve production at scale.

Shoot on anyone, anywhere: generate a model or bring your own, add any location or reference image, then reuse that cast and art direction across up to 10,000 images.
Every photo checked in seconds against its product photo, inside the run, with the reason on each rejection.
A 5-second clip made from the photo you approved.
From 2 credits ($0.20) per 2K photo at $0.10 a credit, no subscription, a shared credit balance per team, with a team for each client if you’re an agency, and runs you can start from ChatGPT, Claude or Codex.
No concurrency tiers: every account generates photos in parallel, at the same price per photo.
No feature tiers: the smallest credit pack gets the same models, locations, 4K output, team workspace and API as an enterprise account.

For agencies: one team per client.

Create a team for each client inside one Uwear account. Each team has its own credit balance, members, cast and art direction, so every client gets its own budget. The team usage dashboard shows what each team made and spent, with CSV export.

Choose FASHN for developer primitives.

Documented REST endpoints with official Python and TypeScript SDKs and webhook delivery.
Exact per-output pricing from a $7.50 minimum, with failed predictions free of charge.
A fixed one-credit try-on endpoint for cost-sensitive or real-time product experiences.
Open Apache-2.0 VTON model weights for teams that want local inspection or deployment.

[2][3][4][10]

One direction, four garments

This is what reusable art direction produces.

Four different garments, one saved art direction, the same model and camera. Uwear generated all four; nothing else changed between shots. That consistency, held across a full catalog, is the production difference these pages compare.

Suede jacket
Striped knit top
Denim midi skirt
Wide-leg pants

Ask the practical questions.

The answers come from both tools’ published pages, read on the access date.

Yes, when the need is operated production rather than API primitives. FASHN gives developers documented try-on and on-model endpoints with exact unit costs. Uwear runs the production system above that layer: reusable art direction, coordinated catalog runs, automatic QA with retries, approvals, and delivery, operable by teams in Studio or by agents over MCP. See sources 2 and 3.

Endpoints versus a production line. FASHN sells per-request generation a developer orchestrates; the catalog logic, QA, and delivery are customer-built. Uwear keeps those steps inside one governed run. See sources 4 and 5.

Yes. FASHN publishes endpoint schemas, official Python and TypeScript SDKs, webhooks, per-output pricing with failed predictions not charged, and open VTON model weights. It is built for developers integrating try-on into an app. Uwear targets the different job of operating full catalog production. See sources 2, 3, 4, and 10.

FASHN documents user-led review: the user or their code inspects each output and requests changes; no automatic acceptance criteria or visual retry policy is published. On Uwear, every photo is checked automatically during the run, in about 6 seconds, at no credit cost, and failed takes are held for retry or review. See sources 4 and 7.

FASHN charges $0.075 per on-demand API credit, with per-endpoint tables. Uwear has no subscription: from 2 credits ($0.20) on GPT Image 2 (low) or 3 credits ($0.30) on GPT Image 2.5 (Low) per 2K photo, or 5 credits ($0.50) on Gemini 2.1, our default, at $0.10 a credit across Studio, API and MCP. The difference is what the credits operate: FASHN credits buy endpoint outputs your systems orchestrate and review, while Uwear credits run inside a job with the reviewer and retries attached. Neither published price states cost per accepted output. See source 3.

FASHN ships an installable coding skill that teaches agents like Claude Code and Cursor to call its REST API: integration help for developers. Uwear ships a remote MCP server: ChatGPT, Claude, and Codex plan and run complete photoshoots directly, with a priced plan you approve before generation starts. See source 9.

Source notes

Review the published source material.

[1]
FASHN homepage
Accessed August 25, 2026
FASHN positions realistic images of your clothes worn by anyone, and reports thousands of brands and creators using the product.
[2]
FASHN API
Accessed August 25, 2026
Public REST endpoints cover try-on, product-to-model, model creation, model swap, editing, reframing, background removal, and image-to-video, with official Python and TypeScript SDKs.
[3]
FASHN API pricing
Accessed October 29, 2026
Publishes $0.075 per on-demand API credit, per-endpoint credit tables, commitment tiers from $19 to $1,249 per month, and the rule that failed predictions consume no credits. Re-checked on October 29, 2026: Product-to-Model at 2K costs 2 to 4 credits by mode (Fast, Balanced, Quality), Face Reference adds 3 credits an image, and Virtual Try-On v1.6 is 1 credit per output.
[4]
FASHN API fundamentals
Accessed August 25, 2026
Documents async jobs with polling or webhooks, default limits of 50 run requests per minute and six concurrent predictions, and a support contact path for higher limits.
[5]
FASHN Product-to-Model reference
Accessed August 25, 2026
The endpoint accepts one product image with prompt, inspiration, face, and background references plus a fixed seed, and returns one to four images per request.
[6]
FASHN Create Model guide
Accessed August 25, 2026
Create Model saves a reusable model identity with face and pose references for later generations across campaigns and product lines.
[7]
FASHN Agent guide
Accessed August 25, 2026
The FASHN Agent analyzes images, chains Studio tools, and iterates on results; the documented flow keeps the user reviewing and requesting changes.
[8]
FASHN image-to-video reference
Accessed August 25, 2026
Image-to-video turns one still into a 5- or 10-second clip at up to 1080p, returns one MP4 per request, and is marked Experimental.
[9]
FASHN coding-agent skill
Accessed August 25, 2026
FASHN ships an installable skill that teaches coding agents such as Claude Code and Cursor to call its REST API or SDKs; no remote MCP server is documented.
[10]
FASHN VTON v1.5 model card
Accessed August 25, 2026
FASHN publishes its VTON v1.5 model weights under an Apache-2.0 license, with documentation for local inference, architecture, and limitations.
[11]
FASHN Product to Model
Accessed October 28, 2026
Accepts flat-lay, ghost-mannequin, on-hanger and product-only photos; combines up to six inputs in one image and generates up to four variations at once.
[12]
FASHN help: app pricing
Accessed October 28, 2026
Face Reference adds 2 credits an image in the Studio and none in the Agent; unused monthly credits roll over while subscribed, capped at three times the plan allowance.
[13]
FASHN changelog
Accessed October 28, 2026
Android app released September 2, 2026, joining iOS; monthly app credits roll over from September 9, 2026; Face Reference with custom faces opened to every paid plan on October 14, 2026.

Alternatives

Which alternative fits the job?

Each comparison is sourced from the other vendor’s published pages. Pick the one that matches the work you are scoping, not the name you already know.

Want the full shortlist instead of one comparison? See FASHN alternatives, with Uwear as our pick for clothing brands shooting full collections and the tools that fit other jobs.

Bring one real range

Price your first run.

Bring the product photos you have, the look you want and where the results need to go. Every run shows its price before it starts, and you see the rejected takes as well as the approved ones. Start with 70 credits ($7); credits never expire.