# Imagen3 Fast

> Imagen3 Fast is a high-quality text-to-image model that generates realistic images from text prompts.


## Overview

- **Endpoint**: `https://fal.run/fal-ai/imagen3/fast`
- **Model ID**: `fal-ai/imagen3/fast`
- **Category**: text-to-image
- **Kind**: inference


## Pricing

- **Price**: $0.025 per images

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 text prompt describing what you want to see
  - Examples: "A serene landscape with mountains reflected in a crystal clear lake at sunset"

- **`negative_prompt`** (`string`, _optional_):
  A description of what to discourage in the generated images Default value: `""`
  - Default: `""`

- **`aspect_ratio`** (`AspectRatioEnum`, _optional_):
  The aspect ratio of the generated image Default value: `"1:1"`
  - Default: `"1:1"`
  - Options: `"1:1"`, `"16:9"`, `"9:16"`, `"3:4"`, `"4:3"`

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

- **`seed`** (`integer`, _optional_):
  Random seed for reproducible generation



**Required Parameters Example**:

```json
{
  "prompt": "A serene landscape with mountains reflected in a crystal clear lake at sunset"
}
```

**Full Example**:

```json
{
  "prompt": "A serene landscape with mountains reflected in a crystal clear lake at sunset",
  "aspect_ratio": "1:1",
  "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/kangaroo/c0RfXzCisqX6YRkIF7apw_output.png"}]

- **`seed`** (`integer`, _required_):
  Seed used for generation
  - Examples: 42



**Example Response**:

```json
{
  "images": [
    {
      "url": "https://v3.fal.media/files/kangaroo/c0RfXzCisqX6YRkIF7apw_output.png"
    }
  ],
  "seed": 42
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/imagen3/fast \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "A serene landscape with mountains reflected in a crystal clear lake at sunset"
   }'
```

### 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/imagen3/fast",
    arguments={
        "prompt": "A serene landscape with mountains reflected in a crystal clear lake at sunset"
    },
    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/imagen3/fast", {
  input: {
    prompt: "A serene landscape with mountains reflected in a crystal clear lake at sunset"
  },
  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/imagen3/fast)
- [API Documentation](https://fal.ai/models/fal-ai/imagen3/fast/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/imagen3/fast)

### 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)