Professional video upscaling powered by Topaz Labs. Precision models (Proteus, Artemis, Iris, Dione, Theia, Gaia, Rhea) enhance footage up to 4x while staying faithful to the source. Best for clean, natural upscales of real-world footage.

topaz/upscale/video/precision

Learn more about Upscale

Inference

Commercial use

Partner

Schema

LLMs

Playground API Examples

topaz/upscale/video/precision

Schema

topaz/upscale/video/precision

Learn more about Upscale

Inference

Commercial use

Partner

Schema

LLMs

Playground API Examples

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Topaz Precision Video Upscale

Classic (non-generative) upscaling and enhancement that stays faithful to the source.

Models

Proteus — the default choice for most real-world footage.
Artemis HQ / MQ / LQ — denoise and sharpen, for progressively more degraded sources.
Gaia HQ / CG — refinement for high-quality footage and CG renders.
Gaia 2 — frame-by-frame 2x upscaling for animation and motion graphics (billed at half price).
Rhea — maximum fine detail via an internal 4x pass.

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/precision", {
  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/precision", {
  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/precision", {
  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/precision", {
  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#

video_url string* required

URL of the video to upscale

model ModelEnum

Precision (non-generative) enhancement model. Proteus fits most real-world footage; Proteus Natural is a softer variant; Iris recovers faces; Dione deinterlaces legacy/interlaced sources; Artemis denoises and sharpens degraded footage; Gaia refines high-quality footage and CG (Gaia 2 upscales animation at 2x); Rhea maximizes fine detail via an internal 4x pass; Theia gives manual detail/fidelity control. Default value: "Proteus"

Possible enum values: Proteus, Proteus Natural, Iris, Iris Low Quality, Dione DV, Dione TV, Dione Robust, Dione Dehalo, Dione Robust Dehalo, Artemis High Quality, Artemis Medium Quality, Artemis Low Quality, Artemis Strong Halo, Artemis Medium Halo, Artemis Aliasing & Moire, Gaia HQ, Gaia CG, Gaia 2, Rhea, Theia Fine Tune Detail, Theia Fine Tune Fidelity

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.

compression float

Compression artifact removal level (0.0-1.0). Default varies by model.

noise float

Noise reduction level (0.0-1.0). Default varies by model.

halo float

Halo reduction level (0.0-1.0). Default varies by model.

grain float

Film grain amount (0.0-0.1). Default varies by model.

recover_detail float

Recover original detail level (0.0-1.0). Higher values preserve more original detail.

H264_output boolean

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

{
  "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4",
  "model": "Proteus",
  "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

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Topaz Precision Video Upscale

Classic (non-generative) upscaling and enhancement that stays faithful to the source.

Models

Proteus — the default choice for most real-world footage.
Artemis HQ / MQ / LQ — denoise and sharpen, for progressively more degraded sources.
Gaia HQ / CG — refinement for high-quality footage and CG renders.
Gaia 2 — frame-by-frame 2x upscaling for animation and motion graphics (billed at half price).
Rhea — maximum fine detail via an internal 4x pass.

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/precision", {
  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/precision", {
  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/precision", {
  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/precision", {
  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#

video_url string* required

URL of the video to upscale

model ModelEnum

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.

compression float

Compression artifact removal level (0.0-1.0). Default varies by model.

noise float

Noise reduction level (0.0-1.0). Default varies by model.

halo float

Halo reduction level (0.0-1.0). Default varies by model.

grain float

Film grain amount (0.0-0.1). Default varies by model.

recover_detail float

Recover original detail level (0.0-1.0). Higher values preserve more original detail.

H264_output boolean

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

{
  "video_url": "https://v3.fal.media/files/kangaroo/y5-1YTGpun17eSeggZMzX_video-1733468228.mp4",
  "model": "Proteus",
  "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.

topaz/upscale/video/precision

Table of contents

Table of contents

topaz/upscale/video/precision

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

Topaz Precision Video Upscale

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

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

Topaz Precision Video Upscale

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