Wan-2.1 Pro is a premium text-to-video model that generates high-quality 1080p videos at 30fps with up to 6 seconds duration, delivering exceptional visual quality and motion diversity from text prompts

fal-ai/wan-pro/text-to-video

Inference

Commercial use

Schema

LLMs

Playground API

SandboxOpen in Sandbox

Loading API documentation…

fal-ai/wan-pro/text-to-video

Schema

LLMs

Loading API documentation…

SandboxOpen in Sandbox

fal-ai/wan-pro/text-to-video

Inference

Commercial use

Schema

LLMs

Playground API

SandboxOpen in Sandbox

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Generate a 6-second 1080p video (at 30 FPS) from text using an enhanced version of Wan 2.1.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/wan-pro/text-to-video", {
  input: {
    prompt: "A lone astronaut in a detailed NASA spacesuit performs an exuberant dance on the lunar surface, arms outstretched in joyful abandon against the stark moonscape. The Earth hangs dramatically in the black sky, appearing to streak past due to the motion of the dance, creating a sense of dynamic movement. The scene captures extreme contrasts between the brilliant white of the spacesuit reflecting harsh sunlight and the deep shadows of the lunar craters. Every detail is rendered with photorealistic precision: the texture of the regolith disturbed by the astronaut's boots, the reflections on the helmet visor."
  },
  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);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.

3. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/wan-pro/text-to-video", {
  input: {
    prompt: "A lone astronaut in a detailed NASA spacesuit performs an exuberant dance on the lunar surface, arms outstretched in joyful abandon against the stark moonscape. The Earth hangs dramatically in the black sky, appearing to streak past due to the motion of the dance, creating a sense of dynamic movement. The scene captures extreme contrasts between the brilliant white of the spacesuit reflecting harsh sunlight and the deep shadows of the lunar craters. Every detail is rendered with photorealistic precision: the texture of the regolith disturbed by the astronaut's boots, the reflections on the helmet visor."
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/wan-pro/text-to-video", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/wan-pro/text-to-video", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

The prompt to generate the video

seed integer

Random seed for reproducibility. If None, a random seed is chosen.

enable_safety_checker boolean

Whether to enable the safety checker Default value: true

{
  "prompt": "A lone astronaut in a detailed NASA spacesuit performs an exuberant dance on the lunar surface, arms outstretched in joyful abandon against the stark moonscape. The Earth hangs dramatically in the black sky, appearing to streak past due to the motion of the dance, creating a sense of dynamic movement. The scene captures extreme contrasts between the brilliant white of the spacesuit reflecting harsh sunlight and the deep shadows of the lunar craters. Every detail is rendered with photorealistic precision: the texture of the regolith disturbed by the astronaut's boots, the reflections on the helmet visor.",
  "enable_safety_checker": true
}

Output#

video File* required

The generated video

{
  "video": {
    "url": "https://fal.media/files/panda/YxRLson-aETxeBK1DI4VW.mp4"
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

Related Models

Loading API documentation…

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Generate a 6-second 1080p video (at 30 FPS) from text using an enhanced version of Wan 2.1.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/wan-pro/text-to-video", {
  input: {
    prompt: "A lone astronaut in a detailed NASA spacesuit performs an exuberant dance on the lunar surface, arms outstretched in joyful abandon against the stark moonscape. The Earth hangs dramatically in the black sky, appearing to streak past due to the motion of the dance, creating a sense of dynamic movement. The scene captures extreme contrasts between the brilliant white of the spacesuit reflecting harsh sunlight and the deep shadows of the lunar craters. Every detail is rendered with photorealistic precision: the texture of the regolith disturbed by the astronaut's boots, the reflections on the helmet visor."
  },
  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);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/wan-pro/text-to-video", {
  input: {
    prompt: "A lone astronaut in a detailed NASA spacesuit performs an exuberant dance on the lunar surface, arms outstretched in joyful abandon against the stark moonscape. The Earth hangs dramatically in the black sky, appearing to streak past due to the motion of the dance, creating a sense of dynamic movement. The scene captures extreme contrasts between the brilliant white of the spacesuit reflecting harsh sunlight and the deep shadows of the lunar craters. Every detail is rendered with photorealistic precision: the texture of the regolith disturbed by the astronaut's boots, the reflections on the helmet visor."
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/wan-pro/text-to-video", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/wan-pro/text-to-video", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

The prompt to generate the video

seed integer

Random seed for reproducibility. If None, a random seed is chosen.

enable_safety_checker boolean

Whether to enable the safety checker Default value: true

{
  "prompt": "A lone astronaut in a detailed NASA spacesuit performs an exuberant dance on the lunar surface, arms outstretched in joyful abandon against the stark moonscape. The Earth hangs dramatically in the black sky, appearing to streak past due to the motion of the dance, creating a sense of dynamic movement. The scene captures extreme contrasts between the brilliant white of the spacesuit reflecting harsh sunlight and the deep shadows of the lunar craters. Every detail is rendered with photorealistic precision: the texture of the regolith disturbed by the astronaut's boots, the reflections on the helmet visor.",
  "enable_safety_checker": true
}

Output#

video File* required

The generated video

{
  "video": {
    "url": "https://fal.media/files/panda/YxRLson-aETxeBK1DI4VW.mp4"
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

fal-ai/wan-pro/text-to-video

fal-ai/wan-pro/text-to-video

fal-ai/wan-pro/text-to-video

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

File#

Related Models

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

File#

Related Models