Professional generative video upscaling powered by Topaz Labs. Starlight models rebuild detail that is not in the source, with Fast variants at half the price. Best for low-quality, compressed or archive footage.

topaz/upscale/video/generative

Learn more about Upscale

Inference

Commercial use

Partner

Schema

Playground API Examples

SandboxOpen in Sandbox

topaz/upscale/video/generative

Schema

SandboxOpen in Sandbox

topaz/upscale/video/generative

Learn more about Upscale

Inference

Commercial use

Partner

Schema

Playground API Examples

SandboxOpen in Sandbox

About

Topaz Generative Video Upscale (Starlight)

Diffusion-based restoration and upscaling that regenerates detail the source no longer has.

Models

Starlight Precise 2.6 — realism pass for AI-generated video.
Starlight HQ — maximum quality on high-resolution sources.
Starlight Mini — diffusion restoration for archival footage.
Starlight Sharp — fast restoration with sharper detail.
Starlight Fast 2 — the fastest, cheapest diffusion upscaler.

Videos are limited to 5 minutes. target_fps enables Apollo frame interpolation only when it differs from the source FPS.

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("topaz/upscale/video/generative", {
  input: {
    video_url: "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
  },
  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("topaz/upscale/video/generative", {
  input: {
    video_url: "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
  },
  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("topaz/upscale/video/generative", {
  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("topaz/upscale/video/generative", {
  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#

enable_safety_checker boolean

Default value: true

video_url string* required

URL of the video to upscale

model ModelEnum

Generative diffusion enhancement model. Starlight Precise 2.6 adds realism to AI-generated video; Starlight HQ maximizes quality on high-resolution sources; Starlight Mini restores archival footage; Starlight Sharp is fast restoration with sharper detail; Starlight Fast 2 is the fastest, cheapest diffusion upscaler. Default value: "Starlight Precise 2.6"

Possible enum values: Starlight Precise 2.6, Starlight HQ, Starlight Mini, Starlight Sharp, Starlight Fast 2

upscale_factor float

Factor to upscale the video by (e.g. 2.0 doubles width and height) Default value: 2

target_fps integer

Target FPS for the output. Frame interpolation is enabled only when this differs from the source FPS.

softness float

How much softening the model applies to the output, from 1 (sharpest) to 5 (softest). Starlight Precise 2.6 only; leave unset for Topaz's default.

H264_output boolean

Whether to use H264 codec for output video. Default is H265.

{
  "enable_safety_checker": true,
  "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4",
  "model": "Starlight Precise 2.6",
  "upscale_factor": 2
}

Output#

video File* required

The upscaled video file

{
  "video": {
    "url": "https://v3.fal.media/files/penguin/ztj_LB4gQlW6HIfVs8zX4_upscaled.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

About

Topaz Generative Video Upscale (Starlight)

Diffusion-based restoration and upscaling that regenerates detail the source no longer has.

Models

Starlight Precise 2.6 — realism pass for AI-generated video.
Starlight HQ — maximum quality on high-resolution sources.
Starlight Mini — diffusion restoration for archival footage.
Starlight Sharp — fast restoration with sharper detail.
Starlight Fast 2 — the fastest, cheapest diffusion upscaler.

Videos are limited to 5 minutes. target_fps enables Apollo frame interpolation only when it differs from the source FPS.

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("topaz/upscale/video/generative", {
  input: {
    video_url: "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
  },
  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("topaz/upscale/video/generative", {
  input: {
    video_url: "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4"
  },
  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("topaz/upscale/video/generative", {
  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("topaz/upscale/video/generative", {
  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#

enable_safety_checker boolean

Default value: true

video_url string* required

URL of the video to upscale

model ModelEnum

Possible enum values: Starlight Precise 2.6, Starlight HQ, Starlight Mini, Starlight Sharp, Starlight Fast 2

upscale_factor float

Factor to upscale the video by (e.g. 2.0 doubles width and height) Default value: 2

target_fps integer

Target FPS for the output. Frame interpolation is enabled only when this differs from the source FPS.

softness float

How much softening the model applies to the output, from 1 (sharpest) to 5 (softest). Starlight Precise 2.6 only; leave unset for Topaz's default.

H264_output boolean

Whether to use H264 codec for output video. Default is H265.

{
  "enable_safety_checker": true,
  "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4",
  "model": "Starlight Precise 2.6",
  "upscale_factor": 2
}

Output#

video File* required

The upscaled video file

{
  "video": {
    "url": "https://v3.fal.media/files/penguin/ztj_LB4gQlW6HIfVs8zX4_upscaled.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

Topaz Upscale Video Generative Video to Video API Docs | fal

topaz/upscale/video/generative

Table of contents

Table of contents

topaz/upscale/video/generative

About

Topaz Generative Video Upscale (Starlight)

Models

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

About

Topaz Generative Video Upscale (Starlight)

Models

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