Stable Diffusion v3 Medium

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

• stable-diffusion-v3-medium

Model Overview

An advanced text-to-image generation model that utilizes a Multimodal Diffusion Transformer (MMDiT) architecture to produce high-quality images from textual descriptions.

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

Authorizations

access-token

Body

application/json

modelundefined · enumRequiredPossible values:

image_sizeany ofOptionalDefault: square_hd

or

string · enumOptional

The size of the generated image.

Possible values:

negative_promptstringOptional

The description of elements to avoid in the generated image.

prompt_expansionbooleanOptional

If set to True, prompt will be upsampled with more details.

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.

num_inference_stepsinteger · min: 1 · max: 50Optional

The number of inference steps to perform.

enable_safety_checkerbooleanOptional

If set to True, the safety checker will be enabled.

Default: true

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.

Responses

201

Successfully generated image

application/json

post

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: 'stable-diffusion-v3-medium',
      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();

201

Successfully generated image

{
  "status": "text",
  "prompt": [
    "text"
  ],
  "model": "text",
  "model_owner": "text",
  "tags": {
    "ANY_ADDITIONAL_PROPERTY": null
  },
  "num_returns": 1,
  "args": {
    "model": "text",
    "prompt": "text",
    "n": 1,
    "steps": 1,
    "size": "text"
  },
  "subjobs": [],
  "output": {
    "choices": [
      {
        "image_base64": "text"
      }
    ]
  }
}

Quick Example

Let's generate an image using a simple prompt.

Python

import requests


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": "stable-diffusion-v3-medium",
            "image_size": "landscape_16_9"
        }
    )

    response.raise_for_status()
    data = response.json()

    print("Generation:", data)


if __name__ == "__main__":
    main()

JS

async function main() {
  try {
    const response = await fetch('https://api.aimlapi.com/v1/images/generations', {
      method: 'POST',
      headers: {
        // Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
        'Authorization': 'Bearer <YOUR_AIMLAPI_KEY>',
        'Content-Type': 'application/json',
      },
      body: JSON.stringify({
        prompt: 'A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses.',
        model: 'stable-diffusion-v3-medium',
        image_size: 'landscape_16_9'
      }),
    });

    if (!response.ok) {
      throw new Error(`HTTP error! Status: ${response.status}`);
    }

    const data = await response.json();
    console.log('Generation:', data);

  } catch (error) {
    console.error('Error:', error);
  }
}

main();

Response

Generation: {'images': [{'url': 'https://cdn.aimlapi.com/squirrel/files/panda/RCbeYSssFwxdkEX2tWd6i.png', 'width': 1024, 'height': 576, 'content_type': 'image/jpeg'}], 'timings': {'inference': 1.174231035867706}, 'seed': 2587699048419330600, 'has_nsfw_concepts': [False], 'prompt': 'A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses.', 'num_images': 1}

We obtained the following 1024x576 image by running this code example:

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