# GPT-Image 1.5

> GPT Image 1.5 generates high-fidelity images with strong prompt adherence, preserving composition, lighting, and fine-grained detail.


## Overview

- **Endpoint**: `https://fal.run/fal-ai/gpt-image-1.5`
- **Model ID**: `fal-ai/gpt-image-1.5`
- **Category**: text-to-image
- **Kind**: inference
**Tags**: openai, gpt-image, 



## Pricing

Your request will cost different amounts based on the number of images, quality, and size.

- You will be charged $0.005 per 1,000 input text tokens. One word is roughly 4 tokens.
-  You will be charged $0.010 per 1,000 output text tokens. The model will consume tokens reasoning about your prompt based on it's complexity.
- For **low** quality, you will be charged $0.009 for 1024x1024 or $0.013 for any other size *per image*. 
- For **medium** quality, you will be charged $0.034 for 1024x1024, $0.051 for 1024x1536 and $0.050 for 1536x1024 *per image*.
- For **high** quality, you will be charged $0.133 for 1024x1024, $0.200 for 1024x1536 or $0.199 for 1536x1024 *per image*.

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 prompt for image generation
  - Examples: "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"

- **`image_size`** (`ImageSizeEnum`, _optional_):
  Aspect ratio for the generated image Default value: `"1024x1024"`
  - Default: `"1024x1024"`
  - Options: `"1024x1024"`, `"1536x1024"`, `"1024x1536"`

- **`background`** (`BackgroundEnum`, _optional_):
  Background for the generated image Default value: `"auto"`
  - Default: `"auto"`
  - Options: `"auto"`, `"transparent"`, `"opaque"`

- **`quality`** (`QualityEnum`, _optional_):
  Quality for the generated image Default value: `"high"`
  - Default: `"high"`
  - Options: `"low"`, `"medium"`, `"high"`

- **`num_images`** (`integer`, _optional_):
  Number of images to generate Default value: `1`
  - Default: `1`
  - Range: `1` to `4`
  - Examples: 1

- **`output_format`** (`OutputFormatEnum`, _optional_):
  Output format for the images Default value: `"png"`
  - Default: `"png"`
  - Options: `"jpeg"`, `"png"`, `"webp"`

- **`sync_mode`** (`boolean`, _optional_):
  If `True`, the media will be returned as a data URI and the output data won't be available in the request history.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "prompt": "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"
}
```

**Full Example**:

```json
{
  "prompt": "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912",
  "image_size": "1024x1024",
  "background": "auto",
  "quality": "high",
  "num_images": 1,
  "output_format": "png"
}
```


### Output Schema

The API returns the following output format:

- **`images`** (`list<ImageFile>`, _required_):
  The generated images.
  - Array of ImageFile
  - Examples: [{"url":"https://v3b.fal.media/files/b/0a869129/EnWrO3XWjPE0nxBDpaQrj.png","content_type":"image/png","height":1024,"file_name":"EnWrO3XWjPE0nxBDpaQrj.png","width":1024}]



**Example Response**:

```json
{
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/0a869129/EnWrO3XWjPE0nxBDpaQrj.png",
      "content_type": "image/png",
      "height": 1024,
      "file_name": "EnWrO3XWjPE0nxBDpaQrj.png",
      "width": 1024
    }
  ]
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/gpt-image-1.5 \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"
   }'
```

### 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(
    "fal-ai/gpt-image-1.5",
    arguments={
        "prompt": "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"
    },
    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("fal-ai/gpt-image-1.5", {
  input: {
    prompt: "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"
  },
  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/fal-ai/gpt-image-1.5)
- [API Documentation](https://fal.ai/models/fal-ai/gpt-image-1.5/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/gpt-image-1.5)

### fal.ai Platform

- [Platform Documentation](https://docs.fal.ai)
- [Python Client](https://docs.fal.ai/clients/python)
- [JavaScript Client](https://docs.fal.ai/clients/javascript)