flux-pro

This documentation is valid for the following list of our models:

• flux-pro

Try in Playground

Model Overview

This is first version of Flux Pro, but it generates images of unmatched quality, outperforming popular models like Midjourney v6.0, DALL·E 3 (HD), and SD3-Ultra.

You can also view a detailed comparison of this model on our main website.

Model	Properties of Generated Images
flux-pro	Format: JPEG, PNG Min size: 256x256 Max size: 1440x1440 Default size: 1024x768 For both height and width, the value must be a multiple of 32.

Setup your API Key

If you don’t have an API key for the AI/ML API yet, feel free to use our Quickstart guide.

API Schema

post

Body

application/json

modelstring · enumRequiredPossible values:

promptstring · max: 4000Required

The text prompt describing the content, style, or composition of the image to be generated.

num_imagesnumber · min: 1 · max: 4Optional

The number of images to generate.

Default: 1

seedinteger · min: 1Optional

The same seed and the same prompt given to the same version of the model will output the same image every time.

image_sizeany ofOptionalDefault: landscape_4_3

or

string · enumOptional

The size of the generated image.

Possible values:

num_inference_stepsinteger · min: 1 · max: 50Optional

The number of inference steps to perform.

guidance_scalenumber · min: 1 · max: 20Optional

The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you.

safety_tolerancestring · enumOptional

The safety tolerance level for the generated image. 1 being the most strict and 5 being the most permissive.

Default: 2Possible values:

output_formatstring · enumOptional

The format of the generated image.

Default: jpegPossible values:

Responses

200Success

application/json

post

/v1/images/generations

JavaScriptPythoncURLHTTP

async function main() {
  const response = await fetch('https://api.aimlapi.com/v1/images/generations', {
    method: 'POST',
    headers: {
      'Authorization': 'Bearer <YOUR_AIMLAPI_KEY>',
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'flux-pro',
      prompt: 'A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses.',
    }),
  });

  const data = await response.json();
  console.log(JSON.stringify(data, null, 2));
}

main();

200Success

{
  "data": [
    {
      "url": "https://cdn.aimlapi.com/generations/hedgehog/1749730923700-29fe35d2-4aef-4bc5-a911-6c39884d16a8.png",
      "b64_json": null
    }
  ],
  "meta": {
    "usage": {
      "tokens_used": 120000
    }
  }
}

Quick Example

Let's generate an image of the specified size using a simple prompt.

The maximum value for both width and height is 1440, and the minimum is 256. The value must be a multiple of 32.

Python

import requests
import json  # for getting a structured output with indentation

def main():
    response = requests.post(
        "https://api.aimlapi.com/v1/images/generations",
        headers={
            # Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
            "Authorization": "Bearer <YOUR_AIMLAPI_KEY>",
            "Content-Type": "application/json"
        },
        json={
            "prompt": "A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses.",
            "model": "flux-pro",
            "image_size": {
                "width": 1024,
                "height": 320 
            }
        }
    )
    
    data = response.json()
    print(json.dumps(data, indent=2, ensure_ascii=False))

if __name__ == "__main__": 
    main()   

JS

Response

{
  images: [
    {
      url: 'https://cdn.aimlapi.com/squirrel/files/elephant/G1UYumZngIkBozNrfiztZ_8d758419045c4c16b563511d6f5f3966.jpg',
      width: 1024,
      height: 320,
      content_type: 'image/jpeg'
    }
  ],
  timings: {},
  seed: 711728385,
  has_nsfw_concepts: [ false ],
  prompt: 'A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses.'
}

We obtained the following nice 1024x320 image by running this code example:

"A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses."