# Stable Diffusion v3.5 Large

{% columns %}
{% column width="66.66666666666666%" %}
{% hint style="info" %}
This documentation is valid for the following list of our models:

* `stable-diffusion-v35-large`
  {% endhint %}
  {% endcolumn %}

{% column width="33.33333333333334%" %} <a href="https://aimlapi.com/app/stable-diffusion-v35-large" class="button primary">Try in Playground</a>
{% endcolumn %}
{% endcolumns %}

## 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](https://docs.aimlapi.com/quickstart/setting-up).

## API Schema

## POST /v1/images/generations

>

```json
{"openapi":"3.0.0","info":{"title":"AIML API","version":"1.0.0"},"servers":[{"url":"https://api.aimlapi.com"}],"paths":{"/v1/images/generations":{"post":{"operationId":"_v1_images_generations","requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","properties":{"model":{"type":"string","enum":["stable-diffusion-v35-large"]},"prompt":{"type":"string","maxLength":4000,"description":"The text prompt describing the content, style, or composition of the image to be generated."},"num_images":{"type":"number","minimum":1,"maximum":4,"default":1,"description":"The number of images to generate."},"seed":{"type":"integer","minimum":1,"description":"The same seed and the same prompt given to the same version of the model will output the same image every time."},"image_size":{"anyOf":[{"type":"object","properties":{"width":{"type":"integer","minimum":64,"maximum":1536,"default":1024},"height":{"type":"integer","minimum":64,"maximum":1536,"default":768}},"description":"For both height and width, the value must be a multiple of 32."},{"type":"string","enum":["square_hd","square","portrait_4_3","portrait_16_9","landscape_4_3","landscape_16_9"],"description":"The size of the generated image."}],"default":"square_hd"},"negative_prompt":{"type":"string","description":"The description of elements to avoid in the generated image."},"guidance_scale":{"type":"number","minimum":1,"maximum":20,"description":"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_steps":{"type":"integer","minimum":1,"maximum":50,"default":50,"description":"The number of inference steps to perform."},"enable_safety_checker":{"type":"boolean","default":true,"description":"If set to True, the safety checker will be enabled."},"output_format":{"type":"string","enum":["jpeg","png"],"default":"jpeg","description":"The format of the generated image."}},"required":["model","prompt"],"title":"stable-diffusion-v35-large"}}}},"responses":{"200":{"content":{"application/json":{"schema":{"type":"object","properties":{"data":{"type":"array","nullable":true,"items":{"type":"object","properties":{"url":{"type":"string","nullable":true,"description":"The URL where the file can be downloaded from."},"b64_json":{"type":"string","nullable":true,"description":"The base64-encoded JSON of the generated image."}}},"description":"The list of generated images."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"credits_used":{"type":"number","description":"The number of tokens consumed during generation."}},"required":["credits_used"]}},"description":"Additional details about the generation."}}}}}}}}}}}
```

## Quick Example

Let's generate an image using a simple prompt.

{% tabs %}
{% tab title="Python" %}
{% code overflow="wrap" %}

```python
import requests
import json

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,
        }
    )

    data = response.json()
    print(json.dumps(data, indent=2, ensure_ascii=False))

if __name__ == "__main__":
    main()
```

{% endcode %}
{% endtab %}

{% tab title="JS" %}
{% code overflow="wrap" %}

```javascript
async function main() {
  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({
      model: 'stable-diffusion-v35-large',
      prompt: 'A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses. Realistic photo.',
      image_size: 'landscape_16_9',
      num_inference_steps: 40,
    }),
  });

  const data = await response.json();
  console.log(data);
}

main();
```

{% endcode %}
{% endtab %}
{% endtabs %}

<details>

<summary>Response</summary>

{% code overflow="wrap" %}

```json5
{
  images: [
    {
      url: 'https://cdn.aimlapi.com/eagle/files/elephant/4vP0cAmlTNsadiYaMFE30.jpeg',
      width: 1024,
      height: 576,
      content_type: 'image/jpeg'
    }
  ],
  timings: { inference: 4.855678029009141 },
  seed: 6199662706750842000,
  has_nsfw_concepts: [ false ],
  prompt: 'A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses.'
}
```

{% endcode %}

</details>

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

<figure><img src="https://3927338786-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FROMd1X5PuqtikJ48n2N9%2Fuploads%2Fgit-blob-9c24f80266d7521e0841a56695d52c939a8ccc48%2Fj_c4eu3gJwADYRTb7_3M1.jpeg?alt=media" alt=""><figcaption><p><code>"A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses."</code></p></figcaption></figure>

<details>

<summary>Extra pictures</summary>

<figure><img src="https://3927338786-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FROMd1X5PuqtikJ48n2N9%2Fuploads%2Fgit-blob-4f06608c798013e1d38bc2bd59a67263e7f70bb1%2F4Y0_aIaOmYmtz2mqVxaPU-1.jpeg?alt=media" alt=""><figcaption><p><code>"A highly detailed T-Rex relaxing on a sunny beach, lying on a wooden sun lounger and wearing stylish sunglasses. Its skin is covered in realistic, finely textured scales with natural color variations — rough and weathered like that of large reptiles. Sunlight reflects subtly off the individual scales. The background includes palm trees, gentle waves, and soft sand partially covering the T-Rex's feet. The scene is rendered with cinematic lighting and a natural color palette."</code><br><code>"num_inference_steps": 40</code></p></figcaption></figure>

<figure><img src="https://3927338786-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FROMd1X5PuqtikJ48n2N9%2Fuploads%2Fgit-blob-eaf047b2db5364963b7e0d328748afd974af59e7%2FpxbrdyW0RCvPtTLh-y8ej.jpeg?alt=media" alt=""><figcaption><p><code>"Racoon eating ice-cream"</code></p></figcaption></figure>

<figure><img src="https://3927338786-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FROMd1X5PuqtikJ48n2N9%2Fuploads%2Fgit-blob-5099265cc27c7f81d95c39b71a70f95a36f94268%2FCz4d2s4FvejqwpoS4_i0C.jpeg?alt=media" alt=""><figcaption><p><code>"A T-Rex relaxing on a beach, lying on a sun lounger and wearing sunglasses. Vector illustration style. Top-down view, with visible palm trees, seagulls, and a strip of water."</code><br><code>"num_inference_steps": 40</code></p></figcaption></figure>

</details>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aimlapi.com/api-references/image-models/stability-ai/stable-diffusion-v35-large.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.