Reve 2.1 Remix API Documentation

Reve 2.1 Remix API Documentation

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Reve 2.1 Image Remix combines one or more reference images with a text prompt to create new image compositions, blending visual references while preserving layout intelligence, visual consistency, and fine image details for posters, ads, product visuals, and creative design workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Reve 2.1 Remix creates a new image from one or more reference images and a text prompt. It is designed for multi-reference composition, style transfer, subject blending, and controlled visual remixing across creative and production workflows.


Why Choose This?

  • Multi-reference image remixing
    Combine one or more reference images into a new generated image.

  • Prompt-guided composition
    Describe how the references should be combined, transformed, or reinterpreted.

  • Flexible creative control
    Blend subjects, styles, layouts, and visual elements into a new composition.

  • Reference-aware generation
    Use image position tags in the prompt when you need to assign a specific role to a specific reference image.

  • Flexible output formats
    Export remixed images as png, jpeg, or webp.


Parameters

ParameterRequiredDescription
promptYesInstructions for combining or transforming the reference images.
imagesYesRefer to them in the prompt with zero-based frame tags.
aspect_ratioNoOutput aspect ratio, including several supported ratio presets.
output_formatNoOutput format: png, jpeg, or webp.

How to Use

  1. Upload reference images — Provide one to eight images for the remix.
  2. Write your prompt — Describe the desired composition and how the references should be used.
  3. Choose aspect ratio — Select an aspect ratio to let the model choose the best layout.
  4. Choose output format — Select png, jpeg, or webp.
  5. Submit — Generate the remixed image and retrieve the output URL.

Pricing

OutputPrice
One image$0.28

Best Use Cases

  • Multi-reference creative composition — Combine multiple visual sources into a new image.
  • Style exploration — Transfer or blend visual direction from one or more references.
  • Product and campaign concepting — Build concept images from product, branding, or lifestyle references.
  • Character and subject blending — Mix subjects, outfits, scenes, or visual identities into a new composition.
  • Creative development — Explore new visual directions from a controlled set of references.

Pro Tips

  • Keep each reference image clear and relevant to the requested composition.
  • Explicitly describe how each frame should contribute to the result.
  • Use frame tags when the prompt refers to a specific reference image.
  • Keep the composition request focused when using many reference images.
  • Use png for high-quality general output, jpeg for smaller files, and webp for web-friendly images.

## Authentication

For authentication details, please refer to the [Authentication Guide](/api-authentication).

## API Endpoints

### Submit Task & Query Result

<ApiTabs submitUrl={model.submitUrl} resultUrl={model.resultUrl} payload={model.defaultValues} />

## Parameters

### Task Submission Parameters

#### Request Parameters

<RequestParams params={model.params} />

#### Response Parameters

<SubmitResponse />

#### Result Request Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| id | string | Yes | - | Task ID |

#### Result Response Parameters

| Parameter | Type | Description |
|-----------|------|-------------|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., "success") |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array&lt;string \| object&gt; | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to poll for the prediction result |
| data.status | string | Status: `created`, `processing`, `completed`, or `failed` |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
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