GPT Image 2 API: Production Guide to the gpt-image-2 Endpoint

What the GPT Image 2 API returns

A single call returns one or more image objects, each with a base64-encoded payload (or a signed URL when using the streamed variant), the resolved resolution, the seed, and a usage block with tokens_in, tokens_out, and the priced tier.

Authentication and SDK setup

npm install openai          # Node
pip install openai          # Python

from openai import OpenAI
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

Your first call to gpt-image-2

result = client.images.generate(
    model="gpt-image-2",
    prompt='A glass storefront with a neon sign reading "Open 24h", cinematic, 50mm',
    size="2048x2048",
    quality="high",
    n=1,
)
print(result.data[0].b64_json[:100])

The first call should return in 3–8 seconds for standard 2K. If you see >15 seconds, you have most likely enabled thinking mode by accident — check the reasoning parameter.

Image-to-image and multi-reference requests

result = client.images.edit(
    model="gpt-image-2",
    prompt="Keep the subject from ref 1, restyle with palette of ref 2.",
    image=[open("subject.png","rb"), open("palette.png","rb")],
    size="2048x2048",
)

Thinking mode via the API

result = client.images.generate(
    model="gpt-image-2",
    prompt="Marketing pack: hero, square, story, banner from this brief",
    reasoning="auto",     # or "force"
    n=4,
)

Use reasoning="auto" for cost-sensitive paths. Use "force" only when accuracy must beat latency (multi-panel comics, infographics with hard facts).

Rate limits, caching and cost control

1. Cache identical prompts: same prompt + seed = same image.
2. Default to standard quality. Reserve high and 4K for shipping assets.
3. Use thinking mode auto, never force in cron jobs.
4. Validate prompts client-side to avoid wasting credits on empty or banned input.

Migration: dall-e-3 to gpt-image-2

- model: "dall-e-3",
+ model: "gpt-image-2",
- size: "1024x1024",
+ size: "2048x2048",
- quality: "hd",
+ quality: "high",

Three behavioral differences to test in staging: GPT Image 2 is more literal, payloads are larger, and quoted strings for in-image text are honored. Full side-by-side breakdown on GPT Image 2 vs DALL-E 3.

Pricing detail on the pricing page; full walkthrough on how to use GPT Image 2.