# Stable Diffusion XL Lightning

> Run SDXL at the speed of light


## Overview

- **Endpoint**: `https://fal.run/fal-ai/fast-lightning-sdxl`
- **Model ID**: `fal-ai/fast-lightning-sdxl`
- **Category**: text-to-image
- **Kind**: inference
**Tags**: diffusion, lightning, real-time



## Pricing

- **Price**: $0 per compute seconds

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 to use for generating the image. Be as descriptive as possible for best results.
  - Examples: "photo of a girl smiling during a sunset, with lightnings in the background"

- **`num_inference_steps`** (`NumInferenceStepsEnum`, _optional_):
  The number of inference steps to perform. Default value: `"4"`
  - Default: `4`
  - Options: `"1"`, `"2"`, `"4"`, `"8"`

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

- **`expand_prompt`** (`boolean`, _optional_):
  If set to true, the prompt will be expanded with additional prompts.
  - Default: `false`

- **`enable_safety_checker`** (`boolean`, _optional_):
  If set to true, the safety checker will be enabled. Default value: `true`
  - Default: `true`

- **`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`

- **`seed`** (`integer`, _optional_):
  The same seed and the same prompt given to the same version of Stable Diffusion
  will output the same image every time.
  - Default: `null`

- **`embeddings`** (`list<Embedding>`, _optional_):
  The list of embeddings to use.
  - Default: `[]`
  - Array of Embedding

- **`image_size`** (`ImageSize | Enum`, _optional_):
  The size of the generated image. Default value: `square_hd`
  - Default: `"square_hd"`
  - One of: ImageSize | Enum

- **`safety_checker_version`** (`SafetyCheckerVersionEnum`, _optional_):
  The version of the safety checker to use. v1 is the default CompVis safety checker. v2 uses a custom ViT model. Default value: `"v1"`
  - Default: `"v1"`
  - Options: `"v1"`, `"v2"`

- **`format`** (`FormatEnum`, _optional_):
  The format of the generated image. Default value: `"jpeg"`
  - Default: `"jpeg"`
  - Options: `"jpeg"`, `"png"`

- **`request_id`** (`string`, _optional_):
  An id bound to a request, can be used with response to identify the request
  itself. Default value: `""`
  - Default: `""`



**Required Parameters Example**:

```json
{
  "prompt": "photo of a girl smiling during a sunset, with lightnings in the background"
}
```

**Full Example**:

```json
{
  "prompt": "photo of a girl smiling during a sunset, with lightnings in the background",
  "num_inference_steps": 4,
  "num_images": 1,
  "enable_safety_checker": true,
  "embeddings": [],
  "image_size": "square_hd",
  "safety_checker_version": "v1",
  "format": "jpeg"
}
```


### Output Schema

The API returns the following output format:

- **`images`** (`list<Image>`, _required_):
  The generated image files info.
  - Array of Image

- **`timings`** (`Timings`, _required_)

- **`seed`** (`integer`, _required_):
  Seed of the generated Image. It will be the same value of the one passed in the
  input or the randomly generated that was used in case none was passed.

- **`has_nsfw_concepts`** (`list<boolean>`, _required_):
  Whether the generated images contain NSFW concepts.
  - Array of boolean

- **`prompt`** (`string`, _required_):
  The prompt used for generating the image.



**Example Response**:

```json
{
  "images": [
    {
      "url": "",
      "content_type": "image/jpeg"
    }
  ],
  "prompt": ""
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/fast-lightning-sdxl \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "photo of a girl smiling during a sunset, with lightnings in the background"
   }'
```

### 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/fast-lightning-sdxl",
    arguments={
        "prompt": "photo of a girl smiling during a sunset, with lightnings in the background"
    },
    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/fast-lightning-sdxl", {
  input: {
    prompt: "photo of a girl smiling during a sunset, with lightnings in the background"
  },
  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/fast-lightning-sdxl)
- [API Documentation](https://fal.ai/models/fal-ai/fast-lightning-sdxl/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/fast-lightning-sdxl)
- [GitHub Repository](https://huggingface.co/ByteDance/SDXL-Lightning/blob/main/LICENSE.md)

### 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)