AI image generation with OpenAI API

OpenAI exposes image generation through the npm package wraps it as client.images.generate. This post walks through the main request parameters and how to save generated images from Node.js.

The examples use gpt-image-2, OpenAI's latest GPT Image model. GPT Image models always return base64-encoded image data in data[].b64_json. Use output_format for the on-disk file type and put artistic direction in the prompt.

For text generation with the same package, see the posts. Image generation is also available through Responses API tools, but this post focuses on the dedicated Image API endpoint.

The running scenario: generate marketing hero images for a fictional todo app.

Prerequisites

• OpenAI account


• Generated API key


• Enabled billing


• Node.js version 26


• 
  openai package installed (npm i openai)

Client setup

Create a client with your API key (read from the environment in production).

import OpenAI from 'openai';



const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

The same SDK can target other hosts that implement a compatible API by setting baseURL and apiKey:

const client = new OpenAI({

  apiKey: process.env.LLM_API_KEY,

  baseURL: 'https://your-gateway.example/v1',

});

.

const result = await client.images.generate({

  model: 'gpt-image-2',

  prompt:

    'Minimal flat illustration of a todo app dashboard, portrait orientation, soft pastel colors',

  size: '1024x1536',

});

Quality

Set rendering quality with quality. Use low for fast drafts and iterations, then medium or high for final assets. Default is auto.

const draft = await client.images.generate({

  model: 'gpt-image-2',

  prompt:

    'Minimal flat illustration of a todo app dashboard, soft pastel colors',

  quality: 'low',

});



const final = await client.images.generate({

  model: 'gpt-image-2',

  prompt:

    'Minimal flat illustration of a todo app dashboard, soft pastel colors, polished details',

  quality: 'high',

  size: '1024x1536',

});

Output format

GPT Image models return base64 in the JSON response. Use output_format to control the encoded file type: png (default), jpeg, or webp.

import { writeFile } from 'node:fs/promises';



const result = await client.images.generate({

  model: 'gpt-image-2',

  prompt:

    'Minimal flat illustration of a todo app dashboard, soft pastel colors',

  output_format: 'jpeg',

});



await writeFile('hero.jpg', Buffer.from(result.data[0].b64_json, 'base64'));

Compression

When output_format is jpeg or webp, set output_compression from 0 to 100 to trade file size for quality. JPEG is often faster than PNG when latency matters.

const result = await client.images.generate({

  model: 'gpt-image-2',

  prompt:

    'Minimal flat illustration of a todo app dashboard, soft pastel colors',

  output_format: 'webp',

  output_compression: 50,

});

Background

Use background: 'transparent' with png or webp on models that support it when you need a cutout asset. gpt-image-2 does not support transparent backgrounds; use gpt-image-1.5 or an earlier GPT Image model for that workflow, or bake the background into the prompt.

const result = await client.images.generate({

  model: 'gpt-image-1.5',

  prompt: 'Flat icon of a checkmark, no background, centered',

  output_format: 'png',

  background: 'transparent',

});

Production notes

• 
  Cost scales with quality and size. See .
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