Test the workflow,
not the marketing claim.
This guide turns a broad model question into repeatable task checks, focusing on literal prompt adherence, invented text, character consistency, material realism, latency, and reported cost without declaring a universal winner.
Technical running shoe frozen above a red clay track at impact, fine dust particles suspended in air, directional hard sunlight, visible outsole detail, energetic diagonal composition, commercial sports photography.
Music festival poster
Experimental electronic music festival poster, oversized condensed type placeholders, electric blue field, silver halftone sphere, asymmetric Swiss grid, high contrast screen-print texture, leave all wording blank.
Forest ranger character sheet
Character sheet for Mara, a forest ranger with cropped auburn hair, olive field jacket, brass compass and worn canvas backpack; front, profile and three-quarter views; neutral studio background; consistent facial features.
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.
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.