Image Generation

Generate and edit images on Nebula Block with Nano Banana and Seedream through the OpenAI-compatible images API.

Generate images from a text prompt, or edit an existing image, through the OpenAI-compatible images endpoint.

Models available

Model

Model ID

Does

Nano-Banana-2

gemini/gemini-3.1-flash-image-preview

Text-to-image, up to 14 reference images

Nano-Banana-Pro

gemini/gemini-3-pro-image-preview

Text-to-image, highest quality

Nano-Banana-Pro-Edit

gemini/gemini-3-pro-image-edit

Image editing

Nano-Banana-Edit

gemini/gemini-2.5-flash-image-edit

Image editing

Bytedance-Seedream-3.0

Bytedance/seedream-3-0-t2i-250415

Bilingual text-to-image, native 2K

See the Model Catalog for the current list.

Generate an image

Using cURL

curl -X POST "https://inference.nebulablock.com/v1/images/generations" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $NEBULA_API_KEY" \
    --data-raw '{
        "model": "gemini/gemini-3.1-flash-image-preview",
        "prompt": "A snowy street in Old Montreal at dusk, warm window light, film photography",
        "size": "1536x1024"
    }'

Using Python

import base64
import os

from openai import OpenAI

client = OpenAI(
    base_url="https://inference.nebulablock.com/v1",
    api_key=os.environ["NEBULA_API_KEY"],
)

result = client.images.generate(
    model="gemini/gemini-3.1-flash-image-preview",
    prompt="A snowy street in Old Montreal at dusk, warm window light, film photography",
    size="1536x1024",
)

with open("output.png", "wb") as f:
    f.write(base64.b64decode(result.data[0].b64_json))

Using JavaScript

import fs from "node:fs";
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://inference.nebulablock.com/v1",
  apiKey: process.env.NEBULA_API_KEY,
});

const result = await client.images.generate({
  model: "gemini/gemini-3.1-flash-image-preview",
  prompt: "A snowy street in Old Montreal at dusk, warm window light, film photography",
  size: "1536x1024",
});

fs.writeFileSync("output.png", Buffer.from(result.data[0].b64_json, "base64"));

The response follows the OpenAI shape — a created timestamp and a data array whose entries carry b64_json.

Controlling the output

size takes a WxH string and is mapped to the nearest aspect ratio the model supports: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9, 4:5, and 5:4.

For anything a model supports beyond the OpenAI fields, use provider_options:

Option

Description

aspect_ratio

Set the ratio directly instead of via size

image_size

Output resolution, where the model supports multiple

image_urls

Reference images to condition the generation on

person_generation

The model's policy for generating people

output_mime_type

Output format, such as image/png or image/jpeg

compression_quality

Compression quality for lossy formats

thinking_level

How much the model reasons before generating

curl -X POST "https://inference.nebulablock.com/v1/images/generations" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $NEBULA_API_KEY" \
    --data-raw '{
        "model": "gemini/gemini-3.1-flash-image-preview",
        "prompt": "Same scene, but in summer",
        "provider_options": {
            "aspect_ratio": "16:9",
            "output_mime_type": "image/png"
        }
    }'

Edit an image

Editing takes a multipart upload rather than JSON, and needs one of the edit models:

curl -X POST "https://inference.nebulablock.com/v1/images/edits" \
    -H "Authorization: Bearer $NEBULA_API_KEY" \
    -F 'model=gemini/gemini-2.5-flash-image-edit' \
    -F 'prompt=Replace the sky with an aurora' \
    -F 'size=1024x1024' \
    -F 'image=@./input.png'

Accepted input formats are PNG, JPEG, WebP, and GIF.

Through the console

Every image model has a playground under Serverless — useful for finding a prompt and a model before you write any code.

Cost

Image models are billed per generation, and prices carry promotional rates from time to time. Check the pricing page or the model's card in the console for the current rate.