Best AI fashion model APIs in 2026: virtual model and on-model photo APIs compared

What each fashion model API generates, and what it costs per image

Listed alphabetically; the order is not a ranking. Prices are per generated image before volume discounts, at 2K where the vendor publishes a 2K rate, with the resolution and model stated wherever the vendor states them. Uwear rates vary by image model and resolution; the full table is on the models page.

Why per-image prices mislead

A headline price is usually the vendor's cheapest setting: the lowest resolution and the fastest model, so a 1K draft from one API sits next to a 2K catalog image from another, and most of these vendors do not say which model they run. None of the prices includes retakes, and none includes your team's time re-describing the model, fixing drift and checking images, which is what tooling saves: on Uwear, a saved model and a saved art direction, batch runs of up to 10,000 items, automations and the optional reviewer. Compare cost per approved image on your own garments, at the same resolution.

How each API fits into your pipeline: webhooks, checks, limits and SDKs

What to check before you choose a fashion image API

Who checks the output. An API reports whether a job finished, not whether the jacket has the right number of buttons. If the API has no check, your team or your code reviews every image, and that labor is part of the price.

Whether the model stays the same. A catalog reads as one shoot only if the face, the light and the framing repeat. Ask whether the model is a saved object you reference, or an image you resend with every call.

How jobs come back. Image generation takes seconds to minutes. Webhooks let a catalog run finish without your service holding a connection open; check how long result URLs live before you must copy the files.

The resolution and the model you are billed for. Some plans cap output at 1K and reserve 2K and 4K for enterprise contracts, and most vendors do not name the image model. Product pages usually need at least 2K, so compare prices there.

Which API fits which job

Each API sits under the job it fits best, in alphabetical order. None is ranked above another: the right one depends on who checks the output and how much of the pipeline your team wants to build.

Best for an app with human retouching, not an API: Botika

Botika is an app, not an API: we could not find a public one. Its pricing page and FAQ describe the web app, the Shopify app and the iOS app, with 1 credit a photo, 5 a video, retouch rounds and white-glove quality control on Enterprise, and mention no API; botika.com/api returns a not-found page. If you need Botika's output in a pipeline, ask its sales team. [32][33]

Best when on-model is one step in a longer image pipeline: Claid AI Fashion Models API

Claid's fashion endpoint takes up to five garment images and returns one to four on-model images, from its model library or from model photos you have the rights to, with eight preset poses and face swap for localized campaigns. The real draw is the rest of the API: more than 20 operations, such as background generation, upscaling and resizing, chainable in one request, with async jobs and HMAC-signed webhooks. [17][18][20][22][23]

AI fashion is 2 credits an image and self-serve API credits start at $59 for 1,000, about $0.12 an image; API and web credits are separate pools. Default limits are 4 requests a second and 120 a minute, with the fashion endpoint at one generation a second. Its workflow example includes an image-checks stage, and the Enterprise API adds custom SLAs, higher limits and forward-deployed engineers. [18][19][21][23][24]

Watch for: Claid is a general ecommerce image platform; a saved art direction that a whole range reuses is not documented, and the fashion endpoint's own page does not state an output resolution. Uwear vs Claid

Best for developers who want low-cost fashion endpoints: FASHN

FASHN is built for developers. Its API covers Product to Model (flat lay or ghost mannequin in), Try-On Max (up to 4K), Model Create, Model Swap, Face to Model, Edit, Reframe, Background Remove and Image to Video, with official Python and TypeScript SDKs and an installable skill that teaches coding agents the API. [6][11]

Pricing is unusually clear: $0.075 a credit on demand with a $7.50 minimum, image endpoints from 1 to 5 credits by mode and resolution (1K to 4K), commitment tiers down to $0.0488 a credit, and failed predictions cost nothing. Note that the $0.10 a credit on FASHN's main pricing page is the app top-up, not the API rate. Jobs are async with polling or webhooks, under default limits of 50 run requests a minute and six at once. Default output links expire after three days. [7][8][9]

Watch for: Product to Model takes one product image and returns one to four images per request; model identity is a face reference resent per request at 3 extra credits an image. No automatic visual check is documented, so a wrong button counts as a successful prediction. The catalog logic, review and retries are yours to build. [10] Uwear vs FASHN

Best for API access and 4K output on a small plan: Modelia

Modelia's REST API has Flatlay to Model, Mannequin to Model and Model to Model endpoints plus background removal, outpainting and upscaling, as async tasks with webhooks, up to 4K. API access starts on the $30 Creator plan; a standard image is 3 credits, and credit packs run from $30 for 150 to $150 for 1,000, so $0.45 to $0.60 an image at 2K or 4K. [27][28]

Watch for: no video endpoint on the API page, and no published rate limits or saved-model feature.

Best if you already use Photoroom's editing API: Photoroom Virtual Model API

Virtual Model is a parameter set on Photoroom's image editing endpoint: send a flat lay or ghost-mannequin photo and pick from 16 preset models, 23 scenes and 12 poses, or pass your own brand model and scene images. It sits beside background removal, ghost mannequin, product staging and virtual try-on in one API, and Photoroom offers an MCP connector for Claude that includes Virtual Model. [12][13][16]

The Plus plan is $0.10 an image, billed monthly, with watermarked sandbox calls for testing. Output is 1K on Plus; 2K and 4K are Enterprise only. Enterprise is an annual commitment with a 200K-image minimum and adds Visual QA, Image to Video and the Enterprise Guarantee. Calls are synchronous, one image per call, at 60 images a minute by default. [13][14][15]

Watch for: the resolution most product pages need, and the quality tooling, sit behind the 200K-image Enterprise commitment. We found no webhooks in its API docs. Uwear vs Photoroom

Best for low cost per image with high request limits: The New Black

The New Black's AI Fashion Models API takes up to three product images, a described or uploaded model and a scene, and returns an ecommerce photo asynchronously, with polling or a webhook. It costs 1 credit for standard, 3 for pro and 7 for ultra at 4K; the $15 Starter plan has 200 credits, about $0.075 a standard image at a resolution it does not state. Every plan includes API access, from 30 calls a minute on Starter to 300 on Enterprise, and it lists an MCP server for Claude. [25][26]

Watch for: results are kept for 48 hours, and no check or retry step is documented.

Best for catalog pipelines that need checked images back: Uwear

The Uwear REST API runs at api.uwear.ai with a Bearer key. You create a clothing item for each garment, then send one generation request per garment, shot or variant, with up to five images each. The request names the image model, the camera, the resolution, a saved model (avatar_id) and a saved art direction (art_direction_id), so every call in a range reuses the same person and the same set. Edits, upscales and video use the same route, with an approved result as the source. [1][2]

The difference from the other APIs here, on their published docs, is the check. Set QA on the request (do_qa) with a retry count (max_qa_retries, 0 to 5, default 0), and an AI reviewer compares each image with each garment's photo, the saved model and the prompt, records the reason for a rejection and retries. The verdict comes back on the result record as qa_status and qa_decision, next to your SKU metadata. The reviewer is 1 credit a photo and each retry is billed as a new generation. [1][3]

Jobs are async: poll the generation, or receive a signed webhook on completion or failure. Result URLs are temporary, so copy approved files to your own storage when they arrive. Credits are $0.10, and the request names the image model, so the price follows the model. The default and recommended model is Gemini 2.1 (Nano Banana 2.1), the most recent and best-performing model Uwear offers, at 5 credits ($0.50) for 2K; GPT Image 2.5 (High) is 6 credits ($0.60). The budget option is GPT Image 2 (low) at 2 credits ($0.20) for 1K or 2K. We recommend paying more for the recent models: they tend to hold garment detail, prints and logos better and need fewer retakes, so the cost per approved image can end up close. Test both on your own garments. A 5-second Kling 3 Pro clip from an approved still is 23 credits. [1][2][4]

For agents, Uwear runs a remote MCP server, the connector that lets ChatGPT, Claude or Codex plan a shoot, show a costed brief and run it after you approve. For code, UWEAR.md is a single reference file a coding agent can load. The same results reach your store through the integration guides, and a published automation can start itself when a garment, tag or outfit arrives. [2][5]

Watch for: on the default model, a higher price per 2K image than FASHN's Product to Model ($0.50 against $0.15 to $0.30 on demand; FASHN does not name its model); GPT Image 2 (low) at $0.20 sits inside FASHN's range. No rate limits are published (the reference tells integrators to queue conservatively and confirm account limits), there is no official SDK, and the API reference documents one job per garment or shot rather than a single bulk endpoint; the Studio takes a CSV of up to 10,000 items for batch runs. [2]

Best for a cheap garment-onto-person call: VModel Try-On

VModel's Try-On endpoint costs $0.12 per use: you send a garment image and a person image, and it returns the person wearing the garment. Tasks are async with a webhook URL or polling, at up to 600 task requests a minute. [29][30][31]

Watch for: you supply the person photo, so it suits try-on features in an app more than a catalog of on-model product photos.

Is the cheapest call the cheapest image?

Not always. Every API above prices the generation, and only some say what happens when the generation is wrong. On FASHN a failed prediction is free, but an image with the wrong collar is a success and costs full price; finding it is your team's job. On Uwear the reviewer adds 1 credit a photo and a retry is billed as a new generation, and the MCP brief shows the credit cost before generation, and the automation builder shows the worst case with QA re-shoots before you publish. The number to compare is the cost per approved image plus the hours your team spends getting there: a person at a screen, or a check in the loop.

How we compared these APIs

We read each vendor's API page, reference docs and pricing on October 7, 2026, and recorded only what they publish: endpoints, inputs, outputs per request, resolution, price per image at 2K where published, with the resolution and model behind each price, async and webhook support, documented checks, rate limits, SDKs and agent access. Where a vendor publishes nothing on a point, the table says so. We did not test the other APIs hands-on, and the APIs are grouped by the job they fit, not ranked. Uwear facts come from the Uwear API page, UWEAR.md and the models page. Prices change often; check the sources before you commit.

Sources

Each page was read on the access date. Vendor prices and limits change; the numbers in the tables refer to these pages.

1. [1] Uwear fashion image generation API. Accessed October 7, 2026.
2. [2] UWEAR.md, the Uwear API reference for agents. Accessed October 7, 2026.
3. [3] Uwear QA and retries. Accessed October 7, 2026.
4. [4] Uwear models and credit rates. Accessed October 7, 2026.
5. [5] Uwear MCP server. Accessed October 7, 2026.
6. [6] FASHN API. Accessed October 7, 2026.
7. [7] FASHN API pricing. Accessed October 7, 2026.
8. [8] FASHN app pricing. Accessed October 7, 2026.
9. [9] FASHN API fundamentals. Accessed October 7, 2026.
10. [10] FASHN Product to Model reference. Accessed October 7, 2026.
11. [11] FASHN agent skill for coding agents. Accessed October 7, 2026.
12. [12] Photoroom Virtual Model API. Accessed October 7, 2026.
13. [13] Photoroom Virtual Model documentation. Accessed October 7, 2026.
14. [14] Photoroom API pricing. Accessed October 7, 2026.
15. [15] Photoroom API FAQ. Accessed October 7, 2026.
16. [16] Photoroom MCP. Accessed October 7, 2026.
17. [17] Claid AI Fashion Models API. Accessed October 7, 2026.
18. [18] Claid AI Fashion Models I/O. Accessed October 7, 2026.
19. [19] Claid API pricing. Accessed October 7, 2026.
20. [20] Claid for Business. Accessed October 7, 2026.
21. [21] Claid async API reference. Accessed October 7, 2026.
22. [22] Claid API workflows. Accessed October 7, 2026.
23. [23] Claid Enterprise API. Accessed October 7, 2026.
24. [24] The New Black AI Fashion Models API. Accessed October 7, 2026.
25. [25] The New Black pricing. Accessed October 7, 2026.
26. [26] Modelia API. Accessed October 7, 2026.
27. [27] Modelia pricing. Accessed October 7, 2026.
28. [28] VModel Try-On. Accessed October 7, 2026.
29. [29] VModel API webhooks. Accessed October 7, 2026.
30. [30] VModel API rate limits. Accessed October 7, 2026.
31. [31] Botika pricing. Accessed October 7, 2026.
32. [32] Botika FAQ. Accessed October 7, 2026.