GPT Image

curl --request POST \
  --url https://api.highwayapi.ai/openai/v1/images/generations

const options = {method: 'POST'};

fetch('https://api.highwayapi.ai/openai/v1/images/generations', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.highwayapi.ai/openai/v1/images/generations",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.highwayapi.ai/openai/v1/images/generations"

	req, _ := http.NewRequest("POST", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://api.highwayapi.ai/openai/v1/images/generations")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)

response = http.request(request)
puts response.read_body

POST

openai

images

generations

GPT Image

curl --request POST \
  --url https://api.highwayapi.ai/openai/v1/images/generations

const options = {method: 'POST'};

fetch('https://api.highwayapi.ai/openai/v1/images/generations', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.highwayapi.ai/openai/v1/images/generations",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.highwayapi.ai/openai/v1/images/generations"

	req, _ := http.NewRequest("POST", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://api.highwayapi.ai/openai/v1/images/generations")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)

response = http.request(request)
puts response.read_body

Parameters and usage are aligned with the official implementation. For detailed parameters, refer directly to the official documentation.

Endpoint

https://{api_domain}/openai/v1/images/generations
https://{api_domain}/openai/v1/images/edits

BaseURL:

https://{api_domain}/openai/v1

Supported Models

gpt-image-2
gpt-image-2-oai
gpt-image-2.5-sunburst-oai
gpt-image-2.5-flare-oai

Description

This endpoint is compatible with the OpenAI Image API and currently supports image generation and image editing. For detailed parameters, refer to the official OpenAI documentation:

OpenAI Official Image Generation Guide
Images generate
Images edit
Image generation requests use application/json.
Image editing supports multipart/form-data file uploads as well as application/json, with image references passed via the images array; a JSON example is provided below.
It is recommended to explicitly set size and quality to control image quality and cost. Fees are calculated based on actual Token usage and model pricing; usage can be viewed in the usage field of the response.

Models and Parameters

Use gpt-image-2.5-sunburst-oai for fine-grained image editing, or gpt-image-2.5-flare-oai for fast image generation. Use the full names listed above in the model field of your requests.
For 2.5, quality accepts low / medium / high / xhigh / max / auto, with a default of auto; GPT Image 2 does not support the newly added xhigh / max.
To generate images with a transparent background, set background="transparent" and use output_format="png" or "webp".
Set the image size via size, for example 1024x1024, 1536x1024, or 1024x1536. For constraints on custom sizes and the full parameter description, refer to the official documentation.

REST API

1. Image Generation

curl -X POST 'https://{api_domain}/openai/v1/images/generations' \
  -H 'Authorization: Bearer apikey' \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gpt-image-2.5-flare-oai",
    "prompt": "A product photo of a white ceramic mug on a wooden table",
    "size": "1024x1024",
    "quality": "high",
    "output_format": "png",
    "n": 1
  }' | jq -r '.data[0].b64_json' | base64 --decode > output.png

2. Image Editing

curl -X POST 'https://{api_domain}/openai/v1/images/edits' \
  -H 'Authorization: Bearer apikey' \
  -F 'model=gpt-image-2' \
  -F 'image[]=@input.png' \
  -F 'mask=@mask.png' \
  -F 'prompt=Replace the background with a clean studio backdrop' \
  -F 'size=1024x1024' \
  -F 'quality=high' \
  -F 'output_format=png' \
  | jq -r '.data[0].b64_json' | base64 --decode > edited.png

For multi-image reference editing, you can pass image[] multiple times:

curl -X POST 'https://{api_domain}/openai/v1/images/edits' \
  -H 'Authorization: Bearer apikey' \
  -F 'model=gpt-image-2' \
  -F 'image[]=@body-lotion.png' \
  -F 'image[]=@bath-bomb.png' \
  -F 'image[]=@soap.png' \
  -F 'prompt=Create a photorealistic gift basket using the reference products' \
  -F 'size=1024x1024' \
  -F 'quality=high'

3. Image Editing (JSON)

Replace {base64_image} with the Base64 encoding of the input PNG image.

curl -X POST 'https://{api_domain}/openai/v1/images/edits' \
  -H 'Authorization: Bearer {your-api-key}' \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gpt-image-2.5-sunburst-oai",
    "images": [
      {"image_url": "data:image/png;base64,{base64_image}"}
    ],
    "prompt": "Change the shape to green. Preserve the simple composition.",
    "size": "1024x1024",
    "quality": "xhigh",
    "moderation": "low",
    "output_format": "png"
  }'

OpenAI SDK

Python

from openai import OpenAI
import base64

api_key = "{your-api-key}"

client = OpenAI(
    api_key=api_key,
    base_url="https://{api_domain}/openai/v1",
)

result = client.images.generate(
    model="gpt-image-2.5-flare-oai",
    prompt="A product photo of a white ceramic mug on a wooden table",
    size="1024x1024",
    quality="high",
)

image_base64 = result.data[0].b64_json
with open("output.png", "wb") as f:
    f.write(base64.b64decode(image_base64))

Image editing:

from openai import OpenAI
import base64

api_key = "{your-api-key}"

client = OpenAI(
    api_key=api_key,
    base_url="https://{api_domain}/openai/v1",
)

result = client.images.edit(
    model="gpt-image-2",
    image=open("input.png", "rb"),
    mask=open("mask.png", "rb"),
    prompt="Replace the background with a clean studio backdrop",
    size="1024x1024",
    quality="high",
)

image_base64 = result.data[0].b64_json
with open("edited.png", "wb") as f:
    f.write(base64.b64decode(image_base64))

Node.js

import OpenAI from "openai";
import fs from "fs";

const client = new OpenAI({
  apiKey: "{your-api-key}",
  baseURL: "https://{api_domain}/openai/v1",
});

const result = await client.images.generate({
  model: "gpt-image-2.5-flare-oai",
  prompt: "A product photo of a white ceramic mug on a wooden table",
  size: "1024x1024",
  quality: "high",
});

const imageBase64 = result.data[0].b64_json;
fs.writeFileSync("output.png", Buffer.from(imageBase64, "base64"));

Image editing:

import OpenAI, { toFile } from "openai";
import fs from "fs";

const client = new OpenAI({
  apiKey: "{your-api-key}",
  baseURL: "https://{api_domain}/openai/v1",
});

const result = await client.images.edit({
  model: "gpt-image-2",
  image: await toFile(fs.createReadStream("input.png"), null, {
    type: "image/png",
  }),
  mask: await toFile(fs.createReadStream("mask.png"), null, {
    type: "image/png",
  }),
  prompt: "Replace the background with a clean studio backdrop",
  size: "1024x1024",
  quality: "high",
});

const imageBase64 = result.data[0].b64_json;
fs.writeFileSync("edited.png", Buffer.from(imageBase64, "base64"));

Best Practices

moderation Parameter

moderation="auto" is the default standard filtering; moderation="low" indicates more lenient filtering.
moderation can be used in both image generation and image editing requests.

API Basics

Large Language Models

Images

Video

Audio

GPT Image

Endpoint

Supported Models

Description

Models and Parameters

REST API

1. Image Generation

2. Image Editing

3. Image Editing (JSON)

OpenAI SDK

Python

Node.js

Best Practices

moderation Parameter

​Endpoint

​Supported Models

​Description

​Models and Parameters

​REST API

​1. Image Generation

​2. Image Editing

​3. Image Editing (JSON)

​OpenAI SDK

​Python

​Node.js

​Best Practices

​moderation Parameter

Endpoint

Supported Models

Description

Models and Parameters

REST API

1. Image Generation

2. Image Editing

3. Image Editing (JSON)

OpenAI SDK

Python

Node.js

Best Practices

moderation Parameter