# Image Generation

The IONOS AI Model Hub provides an OpenAI-compatible API that enables high-quality image generation using state-of-the-art foundation models. By inserting descriptive prompts, users can create detailed images directly through the API without the need for managing underlying hardware, or infrastructure.

## Supported Image Generation Models

AI Model Hub offers varied text-to-image models. For more information, see [<mark style="color:blue;">models list</mark>](/cloud/ai/ai-model-hub/models.md).

## Overview

In this guide, you will learn how to generate images using foundation models through the IONOS API. This guide is intended for developers with basic knowledge of:

* REST APIs
* A programming language for handling REST API endpoints (Python and Bash examples are provided)

By the end, you will be able to:

1. Retrieve a list of available image generation models in the IONOS AI Model Hub.
2. Use prompts to generate images with these models.

## Getting Started with Image Generation

To use image generation models, first set up your environment and authenticate using the OpenAI-compatible API endpoints.

Download the respective code files to easily access image generation-specific scripts and examples and generate the intended output:

{% tabs %}
{% tab title="Python Notebook" %}
Download this Python Notebook file to easily access image generation-specific scripts and examples and generate the intended output.

{% file src="/files/se4T2eGB9kmH0VZSI7qb" %}
{% endtab %}

{% tab title="Python Code" %}
Download this Python code file to easily access image generation-specific scripts and examples and generate the intended output.

{% file src="/files/jGajipCRV5t7jfeXjUmx" %}
{% endtab %}

{% tab title="Bash Code" %}
Download this Bash code file to easily access image generation-specific scripts and examples and generate the intended output.

{% file src="/files/NwOtVF9qnOFCO0AmMG2I" %}
{% endtab %}
{% endtabs %}

#### Step 1: Retrieve Available Models

Fetch a list of models to see which are available for your use case:

{% tabs %}
{% tab title="Python" %}

```python
# Python example to retrieve available models
import requests

IONOS_API_TOKEN = "[YOUR API TOKEN HERE]"

endpoint = "https://openai.inference.de-txl.ionos.com/v1/models"

header = {
    "Authorization": f"Bearer {IONOS_API_TOKEN}", 
    "Content-Type": "application/json"
}
requests.get(endpoint, headers=header).json()
```

{% endtab %}

{% tab title="Bash" %}

```bash
#!/bin/bash

IONOS_API_TOKEN=[YOUR API TOKEN HERE]

curl -H "Authorization: Bearer ${IONOS_API_TOKEN}" \
        --get https://openai.inference.de-txl.ionos.com/v1/models
```

{% endtab %}
{% endtabs %}

This query returns a JSON document listing each model's name, which you’ll use to specify a model for image generation in later steps.

#### Step 2: Generate an Image with Your Prompt

To generate an image, send a prompt to the `/images/generations` endpoint. Customize parameters like `size` for the resolution of the output image.

{% tabs %}
{% tab title="Python" %}

```python
# Python example for image generation
import requests

IONOS_API_TOKEN = "[YOUR API TOKEN HERE]"
MODEL_NAME = "[MODEL NAME HERE]"
PROMPT = "A futuristic cityscape at sunset, highly detailed"

endpoint = "https://openai.inference.de-txl.ionos.com/v1/images/generations"

header = {
    "Authorization": f"Bearer {IONOS_API_TOKEN}", 
    "Content-Type": "application/json"
}
body = {
    "model": MODEL_NAME,
    "prompt": PROMPT,
    "size": "1024x1024"
}
requests.post(endpoint, json=body, headers=header)
```

{% endtab %}

{% tab title="Bash" %}

```bash
#!/bin/bash

IONOS_API_TOKEN=[YOUR API TOKEN HERE]
MODEL_NAME=[MODEL NAME HERE]
PROMPT="A futuristic cityscape at sunset, highly detailed"

BODY="{ 
    \"model\": \"$MODEL_NAME\",
    \"prompt\": \"$PROMPT\",
    \"size\": \"1024x1024\"
}"

curl -H "Authorization: Bearer ${IONOS_API_TOKEN}" \
     -H "Content-Type: application/json" \
     -d "$BODY" \
     https://openai.inference.de-txl.ionos.com/v1/images/generations
```

{% endtab %}
{% endtabs %}

#### Step 3: Extract and Interpret the Result

The returned JSON includes several key fields, most importantly:

* **`data.[].b64_json`**: The generated image in base64 format.
* **`usage.prompt_tokens`**: Token count for the input prompt.
* **`usage.total_tokens`**: Token count for the entire process (usually zero for image generation, as billing is per image).

## Summary

In this guide, you learned how to:

1. Access available image generation models.
2. Use descriptive prompts to generate high-quality images, ideal for applications in design, creative work, and more.

For information on text generation, see our dedicated guide on [<mark style="color:blue;">Text Generation</mark>](/cloud/ai/ai-model-hub/how-tos/text-generation.md) models.


---

# 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.ionos.com/cloud/ai/ai-model-hub/how-tos/image-generation.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.