Imagen 4 Ultra | Text to Image

fal-ai/imagen4/preview/ultra

Google’s highest quality image generation model

Inference

Commercial use

Partner

Schema

Playground API

About

Generate images using Google's Imagen 4 Ultra model.

Imagen 4 Ultra is designed to generate high-quality images with enhanced detail, richer lighting, and fewer artifacts. The model excels at:

Capturing fine details and textures
Rendering diverse art styles from photorealism to animation
Understanding natural language prompts
Maintaining high visual quality and composition

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. Please check the migration guide for more information.

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/imagen4/preview/ultra", {
  input: {
    prompt: "This four-panel comic strip uses a charming, deliberately pixelated art style reminiscent of classic 8-bit video games, featuring simple shapes and a limited, bright color palette dominated by greens, blues, browns, and the dinosaur's iconic grey/black. The setting is a stylized pixel beach. Panel one shows the familiar Google Chrome T-Rex dinosaur, complete with its characteristic pixelated form, wearing tiny pixel sunglasses and lounging on a pixelated beach towel under a blocky yellow sun. Pixelated palm trees sway gently in the background against a blue pixel sky. A caption box with pixelated font reads, \"Even error messages need a vacation.\" Panel two is a close-up of the T-Rex attempting to build a pixel sandcastle. It awkwardly pats a mound of brown pixels with its tiny pixel arms, looking focused. Small pixelated shells dot the sand around it. Panel three depicts the T-Rex joyfully hopping over a series of pixelated cacti planted near the beach, mimicking its game obstacle avoidance. Small \"Boing! Boing!\" sound effect text appears in a blocky font above each jump. A pixelated crab watches from the side, waving its pixel claw. The final panel shows the T-Rex floating peacefully on its back in the blocky blue pixel water, sunglasses still on, with a contented expression. A small thought bubble above it contains pixelated \"Zzz...\" indicating relaxation."
  },
  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 case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.

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/imagen4/preview/ultra", {
  input: {
    prompt: "This four-panel comic strip uses a charming, deliberately pixelated art style reminiscent of classic 8-bit video games, featuring simple shapes and a limited, bright color palette dominated by greens, blues, browns, and the dinosaur's iconic grey/black. The setting is a stylized pixel beach. Panel one shows the familiar Google Chrome T-Rex dinosaur, complete with its characteristic pixelated form, wearing tiny pixel sunglasses and lounging on a pixelated beach towel under a blocky yellow sun. Pixelated palm trees sway gently in the background against a blue pixel sky. A caption box with pixelated font reads, \"Even error messages need a vacation.\" Panel two is a close-up of the T-Rex attempting to build a pixel sandcastle. It awkwardly pats a mound of brown pixels with its tiny pixel arms, looking focused. Small pixelated shells dot the sand around it. Panel three depicts the T-Rex joyfully hopping over a series of pixelated cacti planted near the beach, mimicking its game obstacle avoidance. Small \"Boing! Boing!\" sound effect text appears in a blocky font above each jump. A pixelated crab watches from the side, waving its pixel claw. The final panel shows the T-Rex floating peacefully on its back in the blocky blue pixel water, sunglasses still on, with a contented expression. A small thought bubble above it contains pixelated \"Zzz...\" indicating relaxation."
  },
  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/imagen4/preview/ultra", {
  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/imagen4/preview/ultra", {
  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 text prompt describing what you want to see

negative_prompt string

A description of what to discourage in the generated images Default value: ""

aspect_ratio AspectRatioEnum

The aspect ratio of the generated image Default value: "1:1"

Possible enum values: 1:1, 16:9, 9:16, 3:4, 4:3

num_images integer

Number of images to generate (1-4) Default value: 1

seed integer

Random seed for reproducible generation

{
  "prompt": "This four-panel comic strip uses a charming, deliberately pixelated art style reminiscent of classic 8-bit video games, featuring simple shapes and a limited, bright color palette dominated by greens, blues, browns, and the dinosaur's iconic grey/black. The setting is a stylized pixel beach. Panel one shows the familiar Google Chrome T-Rex dinosaur, complete with its characteristic pixelated form, wearing tiny pixel sunglasses and lounging on a pixelated beach towel under a blocky yellow sun. Pixelated palm trees sway gently in the background against a blue pixel sky. A caption box with pixelated font reads, \"Even error messages need a vacation.\" Panel two is a close-up of the T-Rex attempting to build a pixel sandcastle. It awkwardly pats a mound of brown pixels with its tiny pixel arms, looking focused. Small pixelated shells dot the sand around it. Panel three depicts the T-Rex joyfully hopping over a series of pixelated cacti planted near the beach, mimicking its game obstacle avoidance. Small \"Boing! Boing!\" sound effect text appears in a blocky font above each jump. A pixelated crab watches from the side, waving its pixel claw. The final panel shows the T-Rex floating peacefully on its back in the blocky blue pixel water, sunglasses still on, with a contented expression. A small thought bubble above it contains pixelated \"Zzz...\" indicating relaxation.",
  "aspect_ratio": "1:1",
  "num_images": 1
}

Output#

images list<File>* required

seed integer* required

Seed used for generation

{
  "images": [
    {
      "url": "https://v3.fal.media/files/panda/uzopSU5Me5PUENW-IXMXD_output.png"
    }
  ],
  "seed": 42
}

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.

file_data string

File data

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

Imagen 4 Ultra Text to Image

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