Image Generation

Generate images from a text prompt with Qubax's image generation endpoint. It mirrors the OpenAI Images API, so any client built for /v1/images/generations works unchanged when pointed at the Qubax base URL.

Endpoint

POST https://api.qubax.ai/v1/images/generations

All requests require an API key passed as a Bearer token in the Authorization header:

Authorization: Bearer qbx_live_...
Content-Type: application/json

Request Body

The request body is a JSON object with the parameters below.

Available Image Models

Qubax routes image generation through several state-of-the-art model families. The table below lists the most commonly used models (all available via /v1/models).

Python SDK Example

Using the OpenAI Python SDK pointed at the Qubax base URL:

from openai import OpenAI

client = OpenAI(
    api_key="qbx_live_...",
    base_url="https://api.qubax.ai/v1",
)

response = client.images.generate(
    model="flux-1.1-pro",
    prompt="a cat in space, photorealistic",
    n=1,
    size="1024x1024",
)

# Images are returned inline as base64 — decode and save
import base64
from pathlib import Path
Path("cat.png").write_bytes(base64.b64decode(response.data[0].b64_json))
print("Wrote cat.png")

cURL Example

curl https://api.qubax.ai/v1/images/generations \
  -H "Authorization: Bearer qbx_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "flux-1.1-pro",
    "prompt": "a cat in space, photorealistic",
    "n": 1,
    "size": "1024x1024"
  }'

Response Format

A successful request returns a JSON object with a data array. Each entry contains a b64_json field holding the base64-encoded PNG image (there is no URL mode — images always come back inline).

{
  "created": 1719792000,
  "data": [
    {
      "b64_json": "iVBORw0KGgoAAAANSUhEUgAA..."
    }
  ]
}

Saving the Image

Decode the base64 string and write the bytes to disk — in Python use base64.b64decode(response.data[0].b64_json), in shell pipe the JSON through jq -r '.data[0].b64_json' | base64 -d > image.png.