GPT Image 2 is OpenAI's next-generation image generation model (alpha). It supports flexible resolutions up to 4K and multiple model variants.
Use it as a text-to-image API through fal!
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @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.
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"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("openai/gpt-image-2", {
input: {
prompt: "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"
},
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);This model supports streaming requests. You can stream data directly to the model and get the result in real-time.
import { fal } from "@fal-ai/client";
const stream = await fal.stream("openai/gpt-image-2", {
input: {
prompt: "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"
}
});
for await (const event of stream) {
console.log(event);
}
const result = await stream.done();The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_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.
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("openai/gpt-image-2", {
input: {
prompt: "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912"
},
webhookUrl: "https://optional.webhook.url/for/results",
});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("openai/gpt-image-2", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});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("openai/gpt-image-2", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);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.
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.
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.
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);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.
prompt string* requiredThe prompt for image generation
The size of the generated image. Supports preset names, explicit {width, height}, or 'auto' to let the model pick the best size. Concrete sizes must have both dimensions as multiples of 16, max edge 3840px, aspect ratio <= 3:1, total pixels between 655,360 and 8,294,400. Default value: landscape_4_3
Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9, auto
Note: For custom image sizes, you can pass the width and height as an object:
"image_size": {
"width": 1280,
"height": 720
}background BackgroundEnumBackground for the generated image Default value: "auto"
Possible enum values: auto, transparent, opaque
quality QualityEnumQuality for the generated image. Use 'auto' to let the model pick the best quality for the prompt. Default value: "high"
Possible enum values: auto, low, medium, high
num_images integerNumber of images to generate Default value: 1
output_format OutputFormatEnumOutput format for the images Default value: "png"
Possible enum values: jpeg, png, webp
sync_mode booleanIf True, the media will be returned as a data URI and the output data won't be available in the request history.
{
"prompt": "create a realistic image taken with iphone at these coordinates 41°43′32″N 49°56′49″W 15 April 1912",
"image_size": "landscape_4_3",
"background": "auto",
"quality": "high",
"num_images": 1,
"output_format": "png"
}The generated images.
{
"images": [
{
"url": "https://v3b.fal.media/files/b/0a869129/EnWrO3XWjPE0nxBDpaQrj.png",
"width": 1024,
"content_type": "image/png",
"height": 1024,
"file_name": "EnWrO3XWjPE0nxBDpaQrj.png"
}
]
}width integerThe width of the generated image. Default value: 512
height integerThe height of the generated image. Default value: 512
url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.
width integerThe width of the image
height integerThe height of the image