# Fal Provider

[Fal AI](https://fal.ai/) provides a generative media platform for developers with lightning-fast inference capabilities. Their platform offers optimized performance for running diffusion models, with speeds up to 4x faster than alternatives.

## Setup

The Fal provider is available via the `@ai-sdk/fal` module. You can install it with

<Tabs items={['pnpm', 'npm', 'yarn']}>
  <Tab>
    <Snippet text="pnpm add @ai-sdk/fal" dark />
  </Tab>
  <Tab>
    <Snippet text="npm install @ai-sdk/fal" dark />
  </Tab>
  <Tab>
    <Snippet text="yarn add @ai-sdk/fal" dark />
  </Tab>
</Tabs>

## Provider Instance

You can import the default provider instance `fal` from `@ai-sdk/fal`:

```ts
import { fal } from '@ai-sdk/fal';
```

If you need a customized setup, you can import `createFal` and create a provider instance with your settings:

```ts
import { createFal } from '@ai-sdk/fal';

const fal = createFal({
  apiKey: 'your-api-key', // optional, defaults to FAL_API_KEY environment variable, falling back to FAL_KEY
  baseURL: 'custom-url', // optional
  headers: {
    /* custom headers */
  }, // optional
});
```

You can use the following optional settings to customize the Fal provider instance:

- **baseURL** _string_

  Use a different URL prefix for API calls, e.g. to use proxy servers.
  The default prefix is `https://fal.run`.

- **apiKey** _string_

  API key that is being sent using the `Authorization` header.
  It defaults to the `FAL_API_KEY` environment variable, falling back to `FAL_KEY`.

- **headers** _Record&lt;string,string&gt;_

  Custom headers to include in the requests.

- **fetch** _(input: RequestInfo, init?: RequestInit) => Promise&lt;Response&gt;_

  Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation.
  You can use it as a middleware to intercept requests,
  or to provide a custom fetch implementation for e.g. testing.

## Image Models

You can create Fal image models using the `.image()` factory method.
For more on image generation with the AI SDK see [generateImage()](/docs/reference/ai-sdk-core/generate-image).

### Basic Usage

```ts
import { fal } from '@ai-sdk/fal';
import { experimental_generateImage as generateImage } from 'ai';
import fs from 'fs';

const { image } = await generateImage({
  model: fal.image('fal-ai/fast-sdxl'),
  prompt: 'A serene mountain landscape at sunset',
});

const filename = `image-${Date.now()}.png`;
fs.writeFileSync(filename, image.uint8Array);
console.log(`Image saved to ${filename}`);
```

### Model Capabilities

Fal offers many models optimized for different use cases. Here are a few popular examples. For a full list of models, see the [Fal AI documentation](https://fal.ai/models).

| Model                               | Description                                                                                                                                                   |
| ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `fal-ai/fast-sdxl`                  | High-speed SDXL model optimized for quick inference with up to 4x faster speeds                                                                               |
| `fal-ai/flux-pro/kontext`           | FLUX.1 Kontext [pro] handles both text and reference images as inputs, seamlessly enabling targeted, local edits and complex transformations of entire scenes |
| `fal-ai/flux-pro/kontext/max`       | FLUX.1 Kontext [max] with greatly improved prompt adherence and typography generation, meeting premium consistency for editing without compromise on speed    |
| `fal-ai/flux-lora`                  | Super fast endpoint for the FLUX.1 [dev] model with LoRA support, enabling rapid and high-quality image generation using pre-trained LoRA adaptations.        |
| `fal-ai/flux-pro/v1.1-ultra`        | Professional-grade image generation with up to 2K resolution and enhanced photorealism                                                                        |
| `fal-ai/ideogram/v2`                | Specialized for high-quality posters and logos with exceptional typography handling                                                                           |
| `fal-ai/recraft-v3`                 | SOTA in image generation with vector art and brand style capabilities                                                                                         |
| `fal-ai/stable-diffusion-3.5-large` | Advanced MMDiT model with improved typography and complex prompt understanding                                                                                |
| `fal-ai/hyper-sdxl`                 | Performance-optimized SDXL variant with enhanced creative capabilities                                                                                        |

Fal models support the following aspect ratios:

- 1:1 (square HD)
- 16:9 (landscape)
- 9:16 (portrait)
- 4:3 (landscape)
- 3:4 (portrait)
- 16:10 (1280x800)
- 10:16 (800x1280)
- 21:9 (2560x1080)
- 9:21 (1080x2560)

Key features of Fal models include:

- Up to 4x faster inference speeds compared to alternatives
- Optimized by the Fal Inference Engine™
- Support for real-time infrastructure
- Cost-effective scaling with pay-per-use pricing
- LoRA training capabilities for model personalization

#### Modify Image

Transform existing images using text prompts.

```ts
// Example: Modify existing image
await generateImage({
  model: fal.image('fal-ai/flux-pro/kontext'),
  prompt: 'Put a donut next to the flour.',
  providerOptions: {
    fal: {
      image_url:
        'https://v3.fal.media/files/rabbit/rmgBxhwGYb2d3pl3x9sKf_output.png',
    },
  },
});
```

### Advanced Features

Fal's platform offers several advanced capabilities:

- **Private Model Inference**: Run your own diffusion transformer models with up to 50% faster inference
- **LoRA Training**: Train and personalize models in under 5 minutes
- **Real-time Infrastructure**: Enable new user experiences with fast inference times
- **Scalable Architecture**: Scale to thousands of GPUs when needed

For more details about Fal's capabilities and features, visit the [Fal AI documentation](https://fal.ai/docs).

## Transcription Models

You can create models that call the [Fal transcription API](https://docs.fal.ai/guides/convert-speech-to-text)
using the `.transcription()` factory method.

The first argument is the model id without the `fal-ai/` prefix e.g. `wizper`.

```ts
const model = fal.transcription('wizper');
```

You can also pass additional provider-specific options using the `providerOptions` argument. For example, supplying the `batchSize` option will increase the number of audio chunks processed in parallel.

```ts highlight="6"
import { experimental_transcribe as transcribe } from 'ai';
import { fal } from '@ai-sdk/fal';
import { readFile } from 'fs/promises';

const result = await transcribe({
  model: fal.transcription('wizper'),
  audio: await readFile('audio.mp3'),
  providerOptions: { fal: { batchSize: 10 } },
});
```

The following provider options are available:

- **language** _string_
  Language of the audio file. If set to null, the language will be automatically detected.
  Accepts ISO language codes like 'en', 'fr', 'zh', etc.
  Optional.

- **diarize** _boolean_
  Whether to diarize the audio file (identify different speakers).
  Defaults to true.
  Optional.

- **chunkLevel** _string_
  Level of the chunks to return. Either 'segment' or 'word'.
  Default value: "word"
  Optional.

- **version** _string_
  Version of the model to use. All models are Whisper large variants.
  Default value: "3"
  Optional.

- **batchSize** _number_
  Batch size for processing.
  Default value: 64
  Optional.

- **numSpeakers** _number_
  Number of speakers in the audio file. If not provided, the number of speakers will be automatically detected.
  Optional.

### Model Capabilities

| Model     | Transcription       | Duration            | Segments            | Language            |
| --------- | ------------------- | ------------------- | ------------------- | ------------------- |
| `whisper` | <Check size={18} /> | <Check size={18} /> | <Check size={18} /> | <Check size={18} /> |
| `wizper`  | <Check size={18} /> | <Check size={18} /> | <Check size={18} /> | <Check size={18} /> |


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