GPT Image 2, OpenAI's latest image model, is capable of making fine-grained, detailed edits to images.

openai/gpt-image-2/edit

GPT Image 2, OpenAI's latest image model, is capable of making fine-grained, detailed edits to images.

Learn more about GPT Image 2

Inference

Commercial use

Streaming

Partner

Schema

LLMs

Playground API Examples

SandboxOpen in Sandbox

Input

Prompt*

Additional Settings

Customize your input with more control.

Result

Idle

What would you like to do next?

openai/gpt-image-2/edit

Schema

LLMs

Input

Prompt*

Additional Settings

Customize your input with more control.

Result

Idle

What would you like to do next?

Input

Prompt*

Type # to reference inputs.

Image URLs*

Hint: Drag and drop files from your computer, images from web pages, paste from clipboard (Ctrl/Cmd+V), or provide a URL.

2 images added

Quality

Additional Settings

Customize your input with more control.

Text tokens (per 1M): $5.00 input, $1.25 cached, $10.00 output. Image tokens (per 1M): $8.00 input, $2.00 cached, $30.00 output. Changing the quality parameter significantly affects cost; by default we use high. Adjust it to your preference. See the description at the bottom of this page for more details on how much canonical image sizes cost. Total cost is rounded up to the closest hundredth of a cent ($0.0001).

Streaming

Result

Idle

What would you like to do next?

Download

{
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/0aa63806/_c_w_VstGoLPd--0o8PA3_S8dhxehk.jpg",
      "content_type": "image/jpeg",
      "file_name": "_c_w_VstGoLPd--0o8PA3_S8dhxehk.jpg",
      "file_size": null,
      "width": null,
      "height": null
    }
  ]
}

Input

Prompt*

Additional Settings

Customize your input with more control.

Result

Idle

What would you like to do next?

Input

Prompt*

Type # to reference inputs.

Image URLs*

Hint: Drag and drop files from your computer, images from web pages, paste from clipboard (Ctrl/Cmd+V), or provide a URL.

2 images added

Quality

Additional Settings

Customize your input with more control.

Streaming

Result

Idle

What would you like to do next?

Download

{
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/0aa63806/_c_w_VstGoLPd--0o8PA3_S8dhxehk.jpg",
      "content_type": "image/jpeg",
      "file_name": "_c_w_VstGoLPd--0o8PA3_S8dhxehk.jpg",
      "file_size": null,
      "width": null,
      "height": null
    }
  ]
}

Run GPT Image 2 AI Image Editor API on fal

Official GPT Image 2 Landing Page

OpenAI's next-generation image model, now available as an image editing API via fal. Make fine-grained, detailed edits to existing images using natural language prompts and optional mask control.

Overview

openai/gpt-image-2/edit exposes GPT Image 2 as an image-to-image editing endpoint. Provide one or more reference images alongside a text prompt and the model will apply targeted edits while preserving the parts of the image you did not ask to change. For precise control over which region gets edited, pass an optional mask image to constrain the generation area.

This is the same underlying model as fal-ai/gpt-image-2/, optimized specifically for editing workflows rather than generation from scratch.

Streaming supported. This endpoint supports real-time streaming, so you can display partial results as they arrive rather than waiting for the full generation to complete.

Pricing

The following table shows the pricing of ChatGPT Images 2.0 from a technical standpoint, including one input image.

Size	Low Quality	Medium Quality	High Quality
1024 x 768	$0.011	$0.043	$0.151
1024 x 1024	$0.015	$0.061	$0.219
1024 x 1536	$0.018	$0.054	$0.178
1920 x 1080	$0.017	$0.053	$0.158
2560 x 1440	$0.019	$0.068	$0.234
3840 x 2160	$0.024	$0.113	$0.413

This implies the following: Longer prompts increase the cost, more complex requests (involving use of world knowledge, etc.) cost more, and larger images cost more.

What it can do

Fine-Grained Edits from Natural Language

Describe the change you want in plain text and the model applies it with precision. Style, lighting, objects, clothing, text overlays, and scene details can all be targeted through the prompt alone, without any masking required.

Mask-Based Inpainting

For surgical edits, pass a mask_image_url alongside your reference image. The white regions of the mask indicate the areas to edit; everything outside remains pixel-perfect. This is ideal for product photography touch-ups, background replacements, and UI asset updates.

Multi-Image Reference

The image_urls field accepts a list of images. This allows the model to draw context from multiple sources, useful for style transfer, composition blending, or editing images that require cross-reference context.

Auto Size Inference

When image_size is set to auto (the default for this endpoint), the model infers the output dimensions from the input image. This avoids accidental cropping or rescaling when editing existing assets.

Real-Time Streaming

Stream the result token by token as it is generated. Useful for interactive editing tools where responsiveness matters more than waiting for a polished final output.

Quick Start

Install the client

bash
npm install --save @fal-ai/client

Set your API key

bash
export FAL_KEY="YOUR_API_KEY"

Basic image edit

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

const result = await fal.subscribe("openai/gpt-image-2/edit", {
  input: {
    prompt: "Change the background to a rainy Tokyo street at night",
    image_urls: ["https://your-image-url.com/photo.png"],
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});

console.log(result.data.images[0].url);

Edit with a mask

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

const result = await fal.subscribe("openai/gpt-image-2/edit", {
  input: {
    prompt: "Replace the sky with a dramatic sunset",
    image_urls: ["https://your-image-url.com/photo.png"],
    mask_image_url: "https://your-image-url.com/sky-mask.png",
    quality: "high",
    output_format: "png",
  },
});

console.log(result.data.images[0].url);

Streaming

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

const stream = await fal.stream("openai/gpt-image-2/edit", {
  input: {
    prompt: "Change the lighting to golden hour",
    image_urls: ["https://your-image-url.com/photo.png"],
  },
});

for await (const event of stream) {
  console.log(event);
}

const result = await stream.done();

API Reference

Input

Parameter	Type	Default	Description
`prompt`	string	required	Text description of the edit to apply
`image_urls`	list of strings	required	One or more reference image URLs to edit
`image_size`	enum or object	`auto`	Output size. `auto` infers from input image. Pass `{ width, height }` for custom dims
`quality`	enum	`high`	`low`, `medium`, or `high`
`num_images`	integer	`1`	Number of edited images to generate
`output_format`	enum	`png`	`jpeg`, `png`, or `webp`
`sync_mode`	boolean	`false`	Returns images as data URIs directly; output excluded from request history
`mask_image_url`	string	optional	URL of a mask image. White regions indicate areas to edit
`openai_api_key`	string	optional	Your OpenAI API key for BYOK usage

Image size presets

Preset	Dimensions
`auto`	Inferred from input image (default for this endpoint)
`square_hd`	1024 x 1024
`square`	512 x 512
`portrait_4_3`	768 x 1024
`portrait_16_9`	576 x 1024
`landscape_4_3`	1024 x 768
`landscape_16_9`	1024 x 576

Custom dimensions are also supported. Both edges must be multiples of 16:

json
"image_size": {
  "width": 1920,
  "height": 1080
}

Output

json
{
  "images": [
    {
      "url": "https://v3b.fal.media/files/...",
      "content_type": "image/png",
      "file_name": "output.png",
      "width": 1024,
      "height": 1024
    }
  ]
}

Using the Queue API

For production workloads or longer-running edits, submit requests asynchronously and retrieve results via webhook or polling.

javascript
// Submit
const { request_id } = await fal.queue.submit("openai/gpt-image-2/edit", {
  input: {
    prompt: "...",
    image_urls: ["https://your-image-url.com/photo.png"],
  },
  webhookUrl: "https://your-server.com/webhook",
});

// Check status
const status = await fal.queue.status("openai/gpt-image-2/edit", {
  requestId: request_id,
  logs: true,
});

// Fetch result
const result = await fal.queue.result("openai/gpt-image-2/edit", {
  requestId: request_id,
});

File Inputs

The endpoint accepts image URLs or base64 data URIs. For images that are not publicly accessible, upload them first using the fal storage API:

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

const file = new File([imageBuffer], "photo.png", { type: "image/png" });
const url = await fal.storage.upload(file);

// Use the returned URL as image_urls[0] or mask_image_url

The client will also auto-upload binary objects (File, Blob, Buffer) if you pass them directly.

Use Cases

Product photo editing -- Swap backgrounds, adjust lighting, or update props in product photography without reshooting.

UI and design asset updates -- Edit screenshots, mockups, or design files by describing the change in plain text.

Portrait and photo retouching -- Adjust clothing, environment, or background details while keeping the subject untouched via masking.

Batch content variation -- Generate multiple edited variants of the same base image at different quality settings for A/B testing.

Interactive editing tools -- Use streaming mode to show real-time progress in editing UIs, reducing perceived wait time.

If you want to learn more visit our blog & our gpt image 2 page

How masks work

A mask image is a black-and-white PNG where:

White pixels indicate regions the model is allowed to edit
Black pixels indicate regions that must be preserved exactly

The mask must match the dimensions of the input image. If no mask is provided, the model decides which parts of the image to change based on the prompt alone.

Differences from the text-to-image endpoint

Feature	`openai/gpt-image-2/edit`	`fal-ai/gpt-image-2`
Input images	Required	Not used
Mask support	Yes	No
Default image size	`auto` (from input)	`landscape_4_3`
Streaming	Yes	No
Use case	Edit existing images	Generate from scratch

Run GPT Image 2 AI Image Editor API on fal

Official GPT Image 2 Landing Page

OpenAI's next-generation image model, now available as an image editing API via fal. Make fine-grained, detailed edits to existing images using natural language prompts and optional mask control.

Overview

This is the same underlying model as fal-ai/gpt-image-2/, optimized specifically for editing workflows rather than generation from scratch.

Streaming supported. This endpoint supports real-time streaming, so you can display partial results as they arrive rather than waiting for the full generation to complete.

Pricing

The following table shows the pricing of ChatGPT Images 2.0 from a technical standpoint, including one input image.

Size	Low Quality	Medium Quality	High Quality
1024 x 768	$0.011	$0.043	$0.151
1024 x 1024	$0.015	$0.061	$0.219
1024 x 1536	$0.018	$0.054	$0.178
1920 x 1080	$0.017	$0.053	$0.158
2560 x 1440	$0.019	$0.068	$0.234
3840 x 2160	$0.024	$0.113	$0.413

This implies the following: Longer prompts increase the cost, more complex requests (involving use of world knowledge, etc.) cost more, and larger images cost more.

What it can do

Fine-Grained Edits from Natural Language

Mask-Based Inpainting

Multi-Image Reference

Auto Size Inference

Real-Time Streaming

Stream the result token by token as it is generated. Useful for interactive editing tools where responsiveness matters more than waiting for a polished final output.

Quick Start

Install the client

bash
npm install --save @fal-ai/client

Set your API key

bash
export FAL_KEY="YOUR_API_KEY"

Basic image edit

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

const result = await fal.subscribe("openai/gpt-image-2/edit", {
  input: {
    prompt: "Change the background to a rainy Tokyo street at night",
    image_urls: ["https://your-image-url.com/photo.png"],
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});

console.log(result.data.images[0].url);

Edit with a mask

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

const result = await fal.subscribe("openai/gpt-image-2/edit", {
  input: {
    prompt: "Replace the sky with a dramatic sunset",
    image_urls: ["https://your-image-url.com/photo.png"],
    mask_image_url: "https://your-image-url.com/sky-mask.png",
    quality: "high",
    output_format: "png",
  },
});

console.log(result.data.images[0].url);

Streaming

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

const stream = await fal.stream("openai/gpt-image-2/edit", {
  input: {
    prompt: "Change the lighting to golden hour",
    image_urls: ["https://your-image-url.com/photo.png"],
  },
});

for await (const event of stream) {
  console.log(event);
}

const result = await stream.done();

API Reference

Input

Parameter	Type	Default	Description
`prompt`	string	required	Text description of the edit to apply
`image_urls`	list of strings	required	One or more reference image URLs to edit
`image_size`	enum or object	`auto`	Output size. `auto` infers from input image. Pass `{ width, height }` for custom dims
`quality`	enum	`high`	`low`, `medium`, or `high`
`num_images`	integer	`1`	Number of edited images to generate
`output_format`	enum	`png`	`jpeg`, `png`, or `webp`
`sync_mode`	boolean	`false`	Returns images as data URIs directly; output excluded from request history
`mask_image_url`	string	optional	URL of a mask image. White regions indicate areas to edit
`openai_api_key`	string	optional	Your OpenAI API key for BYOK usage

Image size presets

Preset	Dimensions
`auto`	Inferred from input image (default for this endpoint)
`square_hd`	1024 x 1024
`square`	512 x 512
`portrait_4_3`	768 x 1024
`portrait_16_9`	576 x 1024
`landscape_4_3`	1024 x 768
`landscape_16_9`	1024 x 576

Custom dimensions are also supported. Both edges must be multiples of 16:

json
"image_size": {
  "width": 1920,
  "height": 1080
}

Output

json
{
  "images": [
    {
      "url": "https://v3b.fal.media/files/...",
      "content_type": "image/png",
      "file_name": "output.png",
      "width": 1024,
      "height": 1024
    }
  ]
}

Using the Queue API

For production workloads or longer-running edits, submit requests asynchronously and retrieve results via webhook or polling.

javascript
// Submit
const { request_id } = await fal.queue.submit("openai/gpt-image-2/edit", {
  input: {
    prompt: "...",
    image_urls: ["https://your-image-url.com/photo.png"],
  },
  webhookUrl: "https://your-server.com/webhook",
});

// Check status
const status = await fal.queue.status("openai/gpt-image-2/edit", {
  requestId: request_id,
  logs: true,
});

// Fetch result
const result = await fal.queue.result("openai/gpt-image-2/edit", {
  requestId: request_id,
});

File Inputs

The endpoint accepts image URLs or base64 data URIs. For images that are not publicly accessible, upload them first using the fal storage API:

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

const file = new File([imageBuffer], "photo.png", { type: "image/png" });
const url = await fal.storage.upload(file);

// Use the returned URL as image_urls[0] or mask_image_url

The client will also auto-upload binary objects (File, Blob, Buffer) if you pass them directly.

Use Cases

Product photo editing -- Swap backgrounds, adjust lighting, or update props in product photography without reshooting.

UI and design asset updates -- Edit screenshots, mockups, or design files by describing the change in plain text.

Portrait and photo retouching -- Adjust clothing, environment, or background details while keeping the subject untouched via masking.

Batch content variation -- Generate multiple edited variants of the same base image at different quality settings for A/B testing.

Interactive editing tools -- Use streaming mode to show real-time progress in editing UIs, reducing perceived wait time.

If you want to learn more visit our blog & our gpt image 2 page

How masks work

A mask image is a black-and-white PNG where:

White pixels indicate regions the model is allowed to edit
Black pixels indicate regions that must be preserved exactly

The mask must match the dimensions of the input image. If no mask is provided, the model decides which parts of the image to change based on the prompt alone.

Differences from the text-to-image endpoint

Feature	`openai/gpt-image-2/edit`	`fal-ai/gpt-image-2`
Input images	Required	Not used
Mask support	Yes	No
Default image size	`auto` (from input)	`landscape_4_3`
Streaming	Yes	No
Use case	Edit existing images	Generate from scratch