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GPT Image 2.5 Flare

OpenAI GPT Image 2.5 Flare for fast everyday image generation, editing, and iteration

Category Image Model ID gpt-image-2.5-flare
Model TypeFast image generation and editing
Input / OutputText and image input, image output
API EndpointsSupports Image API generations and edits

Pricing & Specs

💰 Pricing

Input (Text)$5 / M tokens
Input (Image)$8 / M tokens
Price$30 / M image output tokens

⚙️ Specs

Model TypeFast image generation and editing
Input / OutputText and image input, image output
API EndpointsSupports Image API generations and edits
SizesSupports 1024x1024, 1024x1536, 2048x2048, 3840x2160, and more; max side 3840px, total pixels up to 8,294,400
Qualitylow / medium / high / xhigh / max / auto
Output FormatPNG by default, JPEG / WebP optional; Image API returns base64 images
BackgroundTransparent PNG/WebP output with background=transparent
Standard PricingText input $5 / 1M tokens ($1.25 cached), image input $8 / 1M tokens ($2 cached), image output $30 / 1M tokens
Model NotesPrioritizes generation speed for everyday creation, batch exploration, and rapid iteration
Doc StatusUpdated from OpenAI's official image generation guide and pricing page

API Examples

Python

from openai import OpenAI
import base64

client = OpenAI(
    base_url="https://api.zairouter.com/v1",
    api_key="your-api-key"
)

result = client.images.generate(
    model="gpt-image-2.5-flare",
    prompt="A vertical poster for a modern tea brand, glass cup, grapefruit slices, fresh white and green background",
    size="1024x1536",
    quality="high",
    output_format="png",
)

image_base64 = result.data[0].b64_json
with open("poster.png", "wb") as f:
    f.write(base64.b64decode(image_base64))

cURL

curl -s https://api.zairouter.com/v1/images/generations -H "Content-Type: application/json" -H "Authorization: Bearer YOUR_API_KEY" -d '{
    "model": "gpt-image-2.5-flare",
    "prompt": "A vertical poster for a modern tea brand, glass cup, grapefruit slices, fresh white and green background",
    "size": "1024x1536",
    "quality": "high",
    "output_format": "png"
  }' | jq -r '.data[0].b64_json' | base64 --decode > poster.png