Stable Diffusion v3.5 Large

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

stable-diffusion-v35-large

Model Overview

A state-of-the-art text-to-image generative model designed to create high-resolution images based on textual prompts. It excels in producing diverse and high-quality outputs, making it suitable for professional applications.

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

Body

modelundefined · enumRequiredPossible values:

image_sizeany ofOptionalDefault: square_hd

string · enumOptional

The size of the generated image.

Possible values:

negative_promptstringOptional

The description of elements to avoid in the generated image.

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.

output_formatstring · enumOptional

The format of the generated image.

Default: jpegPossible values:

Responses

201Success

post

POST /v1/images/generations HTTP/1.1
Host: api.aimlapi.com
Authorization: Bearer <YOUR_AIMLAPI_KEY>
Content-Type: application/json
Accept: */*
Content-Length: 223

{
  "model": "stable-diffusion-v35-large",
  "image_size": "square_hd",
  "negative_prompt": "text",
  "guidance_scale": 1,
  "num_inference_steps": 1,
  "enable_safety_checker": true,
  "prompt": "text",
  "num_images": 1,
  "seed": 1,
  "output_format": "jpeg"
}

201Success

No content

Quick Example

Let's generate an image using a simple prompt.

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-v35-large",
            "image_size": "landscape_16_9"
            "num_inference_steps": 40,
        }
    )

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

    print("Generation:", data)


if __name__ == "__main__":
    main()

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-v35-large',
        image_size: 'landscape_16_9',
        num_inference_steps: 40,
      }),
    });

    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/eagle/files/elephant/j_c4eu3gJwADYRTb7_3M1.jpeg', 'width': 1024, 'height': 576, 'content_type': 'image/jpeg'}], 'timings': {'inference': 4.801230997079983}, 'seed': 5821854872171531000, 'has_nsfw_concepts': [False], 'prompt': 'A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses.'}

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

Extra pictures

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Last updated 16 days ago

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