# Z Image Base (LoRA)

> LoRA endpoint for Z-Image, the foundation model of the Z- Image family.


## Overview

- **Endpoint**: `https://fal.run/fal-ai/z-image/base/lora`
- **Model ID**: `fal-ai/z-image/base/lora`
- **Category**: text-to-image
- **Kind**: inference
**Tags**: z-image, base, lora



## Pricing

- **Price**: $0.012 per megapixels

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 generate an image from.
  - Examples: "Grandmother knitting by a window, an empty chair by her"

- **`image_size`** (`ImageSize | Enum`, _optional_):
  The size of the generated image. Default value: `landscape_4_3`
  - Default: `"landscape_4_3"`
  - One of: ImageSize | Enum

- **`num_inference_steps`** (`integer`, _optional_):
  The number of inference steps to perform. Default value: `28`
  - Default: `28`
  - Range: `1` to `50`

- **`guidance_scale`** (`float`, _optional_):
  The guidance scale to use for the image generation. Default value: `4`
  - Default: `4`
  - Range: `1` to `20`

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

- **`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`

- **`num_images`** (`integer`, _optional_):
  The number of images to generate. Default value: `1`
  - Default: `1`
  - Range: `1` to `4`

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

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

- **`acceleration`** (`AccelerationEnum`, _optional_):
  The acceleration level to use. Default value: `"regular"`
  - Default: `"regular"`
  - Options: `"none"`, `"regular"`, `"high"`

- **`negative_prompt`** (`string`, _optional_):
  The negative prompt to use for the image generation. Default value: `""`
  - Default: `""`

- **`loras`** (`list<LoRAInput>`, _optional_):
  List of LoRA weights to apply (maximum 3).
  - Default: `[]`
  - Array of LoRAInput



**Required Parameters Example**:

```json
{
  "prompt": "Grandmother knitting by a window, an empty chair by her"
}
```

**Full Example**:

```json
{
  "prompt": "Grandmother knitting by a window, an empty chair by her",
  "image_size": "landscape_4_3",
  "num_inference_steps": 28,
  "guidance_scale": 4,
  "num_images": 1,
  "enable_safety_checker": true,
  "output_format": "png",
  "acceleration": "regular",
  "loras": []
}
```


### Output Schema

The API returns the following output format:

- **`images`** (`list<ImageFile>`, _required_):
  The generated image files info.
  - Array of ImageFile
  - Examples: [{"height":768,"content_type":"image/png","url":"https://v3b.fal.media/files/b/0a8c18a5/1z0k9F1YLgz4qCr64jCBa_r2uqRyDg.png","width":1024}]

- **`timings`** (`Timings`, _required_):
  The timings of the generation process.

- **`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": [
    {
      "height": 768,
      "content_type": "image/png",
      "url": "https://v3b.fal.media/files/b/0a8c18a5/1z0k9F1YLgz4qCr64jCBa_r2uqRyDg.png",
      "width": 1024
    }
  ],
  "prompt": ""
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/z-image/base/lora \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "Grandmother knitting by a window, an empty chair by her"
   }'
```

### 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/z-image/base/lora",
    arguments={
        "prompt": "Grandmother knitting by a window, an empty chair by her"
    },
    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/z-image/base/lora", {
  input: {
    prompt: "Grandmother knitting by a window, an empty chair by her"
  },
  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/z-image/base/lora)
- [API Documentation](https://fal.ai/models/fal-ai/z-image/base/lora/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/z-image/base/lora)

### 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)