Test the workflow,
not the marketing claim.
Latency should be measured from the client boundary and interpreted with retries, requested size, workload type, and acceptance quality, because a fast unusable output can increase rather than reduce end-to-end production time.
Editorial product photograph of a matte ceramic skincare bottle on pale limestone, soft north-window light, delicate contact shadow, warm neutral palette, 85mm lens compression, no text, no logo.
Climate intelligence dashboard
Editorial analytics dashboard for a climate intelligence product, dense but legible information hierarchy, off-white canvas, dark graphite type, acid green data accents, modular card grid, desktop viewport.
Coastal house at dusk
Low modern coastal house at blue hour, weathered cedar and board-formed concrete, dune grasses moving in sea wind, warm interior light, realistic architectural photography, human-scale lens.
Exploded running shoe
Exploded technical view of a running shoe with upper, laces, foam midsole, plate and outsole separated vertically, clean off-white background, precise alignment, soft studio shadows, no labels.
PYTHON QUICKSTART
Keep the request reproducible.
Store credentials in the environment. Record the exact model identifier, dimensions, test date, and retry count with the resulting asset.
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["APIMART_API_KEY"],
base_url="https://api.apimart.ai/v1",
)
result = client.images.generate(
model="gpt-image-1-official",
prompt=PROMPT,
size="1024x1024",
n=1,
)Before you publish a result
- Record model ID, parameters, date, latency, and retry count.
- Review instruction following and protected attributes.
- Flag invented text, marks, anatomy, or unwanted objects.
- Keep the raw output linked to the original fixture.
- Do not claim a universal winner from one prompt.