Architecture · REPRODUCIBLE GUIDE

Multi-Model AI API: Routing, Fallbacks, and Evaluation

Design one integration boundary while keeping model choice, fallbacks, and benchmark records explicit.

One API gateway for multiple AI models.

APIMart is a multi-model AI API gateway with an OpenAI-compatible endpoint. Use one account to access supported image models, compare current pricing, and choose a cost-efficient option for each workload.

Create an APIMart account ↗
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WHY THIS GUIDE EXISTS

Test the workflow,
not the marketing claim.

For teams that want to compare and route across image models without coupling application code to every provider.

Ecommerce

Ceramic skincare hero

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.
Clean premium product hero1:1
Design

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.
Dense editorial interface16:10
Characters

Retro space mechanic

Full-body retro-futurist spacecraft mechanic, orange utility suit with modular pockets, grease marks, transparent helmet carried under one arm, practical silhouette, 1970s industrial science-fiction mood.
Full-body character concept2:3
Architecture

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.
Exterior visualization16:9
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,
)
REVIEW CHECKLIST

Before you publish a result