# Ideogram V4.5 Text to Image

> Generate high-quality images, posters, and logos with Ideogram 4.5, with accurate text rendering and low, medium, or high quality tiers.


## Overview

- **Endpoint**: `https://fal.run/ideogram/v4.5`
- **Model ID**: `ideogram/v4.5`
- **Category**: text-to-image
- **Kind**: inference
**Description**: Ideogram 4.5 text-to-image. Generate posters, logos, and designs with accurate typography. Quality: low, medium (default), or high; price does not depend on size. Output sizes: fal presets (square_hd by default, 4:3, 16:9) or one of 36 supported exact sizes. Up to 8 images per request. Prompt expansion is on by default.

**Tags**: realism, typography, stylized



## Pricing

Your request will cost **$0.03** per image with Low, **$0.06** with Medium, and **$0.22** with High quality. The image size does not change the price.

For more details, see [fal.ai pricing](https://fal.ai/pricing).

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:


- **`prompt`** (`string`, _required_):
  The generation or editing prompt.
  - Examples: "A colorful storefront with a sign reading hello"

- **`image_size`** (`ImageSize | Enum`, _optional_):
  Output size. square is promoted to square_hd (1024x1024). 4:3 presets use 1152x864 or 864x1152; 16:9 presets use 1280x720 or 720x1280. Explicit dimensions must match a supported size: 1024x1024, 1024x3072, 1120x896, 1152x2944, 1152x864, 1248x3328, 1248x832, 1280x3072, 1280x720, 1280x800, 1296x3168, 1440x2560, 1440x2880, 1440x720, 1600x2560, 1664x2496, 1728x2304, 1792x2240, 2048x2048, 2240x1792, 2304x1728, 2496x1664, 2560x1440, 2560x1600, 2880x1440, 2944x1152, 3072x1024, 3072x1280, 3168x1296, 3328x1248, 720x1280, 720x1440, 800x1280, 832x1248, 864x1152, 896x1120 Default value: `square_hd`
  - Default: `"square_hd"`
  - One of: ImageSize | Enum

- **`quality`** (`QualityEnum`, _optional_):
  Text-to-image quality. Default value: `"medium"`
  - Default: `"medium"`
  - Options: `"low"`, `"medium"`, `"high"`

- **`enable_prompt_expansion`** (`boolean`, _optional_):
  Enable partner prompt expansion. Default value: `true`
  - Default: `true`

- **`num_images`** (`integer`, _optional_):
  Number of images to generate. Default value: `1`
  - Default: `1`
  - Range: `1` to `8`

- **`seed`** (`integer`, _optional_):
  Random seed. Omit to choose automatically.

- **`sync_mode`** (`boolean`, _optional_):
  Return image data directly in the response.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "prompt": "A colorful storefront with a sign reading hello"
}
```

**Full Example**:

```json
{
  "prompt": "A colorful storefront with a sign reading hello",
  "image_size": "square_hd",
  "quality": "medium",
  "enable_prompt_expansion": true,
  "num_images": 1
}
```


### Output Schema

The API returns the following output format:

- **`images`** (`list<File>`, _required_)
  - Array of File
  - Examples: [{"url":"https://v3.fal.media/files/penguin/lHdRabS80guysb8Zw1kul_image.png"}]

- **`seed`** (`integer`, _required_):
  Seed used for the random number generator
  - Examples: 123456



**Example Response**:

```json
{
  "images": [
    {
      "url": "https://v3.fal.media/files/penguin/lHdRabS80guysb8Zw1kul_image.png"
    }
  ],
  "seed": 123456
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/ideogram/v4.5 \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "A colorful storefront with a sign reading hello"
   }'
```

### Python

Ensure you have the Python client installed:

```bash
pip install fal-client
```

Then use the API client to make requests:

```python
import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "ideogram/v4.5",
    arguments={
        "prompt": "A colorful storefront with a sign reading hello"
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)
```

### JavaScript

Ensure you have the JavaScript client installed:

```bash
npm install --save @fal-ai/client
```

Then use the API client to make requests:

```javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("ideogram/v4.5", {
  input: {
    prompt: "A colorful storefront with a sign reading hello"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);
```


## Additional Resources

### Documentation

- [Model Playground](https://fal.ai/models/ideogram/v4.5)
- [API Documentation](https://fal.ai/models/ideogram/v4.5/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=ideogram/v4.5)

### fal.ai Platform

- [Platform Documentation](https://fal.ai/docs/documentation)
- [Python Client](https://fal.ai/docs/api-reference/client-libraries/python)
- [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript)

### Other agent-readable surfaces

This file covers one model. To find anything else:

- [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs
- [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page
- [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined
- Any other model: `https://fal.ai/models/<endpoint-id>/llms.txt`