> For the complete documentation index, see [llms.txt](https://docs.ionos.com/cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ionos.com/cloud/ai/ai-model-hub/how-tos/image-generation.md).

# Image Generation

The <code class="expression">space.vars.ionos\_cloud\_ai\_model\_hub</code> 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 <code class="expression">space.vars.ionos\_cloud</code> 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 <code class="expression">space.vars.ionos\_cloud\_ai\_model\_hub</code>.
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 use image generation-specific scripts and examples and generate the intended output:

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

{% file src="/files/oWHNU4q34VSp2Et0yLI4" %}
{% endtab %}

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

{% file src="/files/625DMkbhLiaXEEqYR3kD" %}
{% endtab %}

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

{% file src="/files/b5cEhKKctI9GPi4S2weF" %}
{% 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 using a prompt and FLUX.1-schnell

To generate an image, send a prompt to the `/images/generations` endpoint. Note the following parameter restrictions for FLUX.1-schnell:

* **`size`**: Must be one of `"1024x1024"`, `"1792x1024"`, or `"1024x1792"`.
* **`n`**: Defaults to `1`. Only `1` is accepted.

{% 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: Generate an image using a prompt and FLUX.2-klein-4B

To generate an image, send a prompt to the `/images/generations` endpoint. Note the following parameter restrictions for FLUX.2-klein-4B:

* **`size`**: A string specifying the dimensions in `widthxheight` format. Both dimensions must be between 64 and 2048 (inclusive) and are automatically rounded down to the nearest multiple of 16. **Default:** `1024x1024`. **Examples:** `1024x1024`, `1536x1024`, `1024x1536`, `2048x2048`, `2048x1152`.
* **`n`**: Number of images to generate. Defaults to `1`. Accepts values from `1` to `10` if the request produces at most 12,582,912 pixels in total (`n` × width × height), for example three `2048x2048` images or ten `1024x1024` images.
* **`output_format`**: Format of the returned image. Accepted values: `jpg`, `jpeg`, `png`, `webp`.

Requests that do not meet these limits are rejected with a `400 Bad Request` error detailing the exceeded limit.

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

```python
# Python example for image generation with FLUX.2-klein-4B
import requests

IONOS_API_TOKEN = "[YOUR API TOKEN HERE]"
MODEL_NAME = "black-forest-labs/FLUX.2-klein-4B"
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",
    "output_format": "png"
}
requests.post(endpoint, json=body, headers=header)
```

{% endtab %}

{% tab title="Bash" %}

```bash
#!/bin/bash

IONOS_API_TOKEN=[YOUR API TOKEN HERE]
MODEL_NAME="black-forest-labs/FLUX.2-klein-4B"
PROMPT="A futuristic cityscape at sunset, highly detailed"

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

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 4: Extract and interpret the result

The returned JSON includes several key fields, most importantly:

* **`data.[].b64_json`**: The generated image in base64 format.

## What you learned

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.


---

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