Model Create

Model Create enables you to generate realistic fashion models with simple, intuitive prompts or reference images.

Lifecycle: Experimental · Released: August 11, 2025

Request body

Every call uses the universal POST /v1/run request body:

Field	Type	Required	Description
`model_name`	string	Yes	Must be `model-create`.
`inputs`	object	Yes	Contains the endpoint-specific parameters documented under Input parameters.

Place all endpoint parameters inside inputs; they are not top-level request fields.

Request

Generate fashion models by submitting your prompt and optional reference assets to the universal /v1/run endpoint:

POST`https://api.fashn.ai/v1/run`

Request examples

curl -X POST https://api.fashn.ai/v1/run \
     -H "Content-Type: application/json" \
     -H "Authorization: Bearer YOUR_API_KEY" \
     -d '{
           "model_name": "model-create",
           "inputs": {
             "prompt": "Full body shot, woman wearing a white t-shirt and dark blue biker shorts"
           }
         }'

Response

Returns a prediction ID for status polling:

{
  "id": "123a87r9-4129-4bb3-be18-9c9fb5bd7fc1-u1",
  "error": null
}

Input parameters

`prompt`
Required
string

Prompt for the model image generation. Describes the desired fashion model, clothing, pose, and scene.

`image_reference`image URL | data URI

Optional image to guide composition and pose. The AI won't copy the exact details from the image, but will use it as inspiration.

You can control whether to copy just the pose or the exact silhouette using the prompt parameter with natural language.

`aspect_ratio`string

Defines the width-to-height ratio of the generated image.

When image_reference is provided, the output inherits the reference image's aspect ratio. Supply an explicit aspect_ratio to override that default.

Supported ratios: "21:9", "16:9", "9:16", "4:3", "3:4", "3:2", "2:3", "4:5", "5:4", "1:1".

Default: 1:1

`face_reference`image URL | data URI

Optional portrait image that locks in a specific identity across generations.

When face_reference is used, output resolution is capped at 2K regardless of the requested resolution tier.
Adds 3 credits per image.
Typically adds around 20 seconds of processing time.

Use this to achieve model consistency across generations without training a custom checkpoint.

`face_reference_mode`'match_base' | 'match_reference'

Controls how the provided face_reference shapes pose and expression.

-match_base prioritizes the prompt and base generation, keeping the original pose while adapting the reference face to those instructions.

-match_reference aligns the generated model closely with the reference face’s pose, gaze, and expression for maximum resemblance.

Default: match_reference

`resolution`'1k' | '2k' | '4k'

Output resolution tier. '1k' produces ~1 megapixel output, '2k' ~4 megapixels, and '4k' ~16 megapixels. Exact output dimensions depend on this tier and the image aspect ratio.

Default: 1k

`generation_mode`'fast' | 'balanced' | 'quality'

Sets the generation quality level. 'quality' produces the most detailed and realistic output but takes longer to process and costs more credits. 'fast' prioritizes speed and lower cost. If omitted, FASHN selects generation_mode automatically. For model-create, omitted generation_mode is currently billed as 'fast' at 1k and as 'balanced' at 2k or 4k.

`seed`integer

Sets random operations to a fixed state. Use the same seed to reproduce results with the same inputs, or different seed to force different results.

Default: 42 · Range: 0 to 2^32 - 1

`num_images`integer

Number of images to generate per request. Must be between 1 and 4. Additional images consume more compute (and credits) and can increase processing time.

Default: 1

`output_format`'png' | 'jpeg'

Specifies the desired output image format.

-png: Delivers the highest quality image, ideal for use cases such as content creation where quality is paramount.

-jpeg: Provides a faster response with a slightly compressed image, more suitable for real-time applications.

Default: png

`return_base64`boolean

When set to true, the API returns the generated image as a base64 string instead of a CDN URL. The base64 output is prefixed according to output_format (e.g., data:image/png;base64,... or data:image/jpeg;base64,...).

Privacy benefit: Outputs are available for up to 60 minutes instead of the standard three-day window. Request history contains only a <base64> placeholder.

Default: false

Technical limitations

Requirement	Limit
Image file size	30 MiB per image
Minimum dimensions	15 × 15 px
Aspect ratio	1:16 to 16:1

Inputs outside these limits fail with InputValidationError. The output resolution does not change the input limits.

Credit cost

`generation_mode` \ `resolution`	`1k`	`2k`	`4k`
`fast`	1	2	3
`balanced`	2	3	4
`quality`	3	4	5

Additional pricing rules:

face_reference adds +3 credits per output image.
num_images multiplies the total cost by the number of outputs requested.
If generation_mode is omitted, automatic pricing applies.

Processing time

Processing time depends on both resolution and generation_mode. The fastest configuration (fast + 1k) typically completes in around 10 seconds, balanced at 2k finishes in around 25 seconds, and the most intensive combination (quality + 4k) typically takes around 55 seconds. Using face_reference typically adds around 20 seconds on top of any configuration. Actual latency may vary with current server load.

Response polling

After submitting your request, poll the status endpoint using the returned prediction ID. See API Fundamentals for complete polling details.

Successful response

When your model creation completes successfully, the status endpoint will return:

{
  "id": "123a87r9-4129-4bb3-be18-9c9fb5bd7fc1-u1",
  "status": "completed",
  "output": [
    "https://cdn.fashn.ai/123a87r9-4129-4bb3-be18-9c9fb5bd7fc1-u1/output_0.png"
  ],
  "error": null
}

The output array contains URLs to your generated fashion model images based on your prompt and optional reference parameters.

Runtime errors

Runtime errors for Model Create use the shared set in Error Handling.

For detailed implementation guidance and best practices:

Image Preprocessing Best Practices - Optimize your reference images

Model Create

POSThttps://api.fashn.ai/v1/run

Response

promptRequiredstring

image_referenceimage URL | data URI

aspect_ratiostring

face_referenceimage URL | data URI

face_reference_mode'match_base' | 'match_reference'

resolution'1k' | '2k' | '4k'

generation_mode'fast' | 'balanced' | 'quality'

seedinteger

num_imagesinteger

output_format'png' | 'jpeg'

return_base64boolean

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