New Image Generation and Editing Capabilities: Gemini 2.5 Flash Image Preview and Expanded Edit Endpoint Support
Date: 2025-08-26 / (1404-06-05)
Update (2025-10-09): The preview model has been replaced by the stable version
gemini-2.5-flash-image. The preview model (gemini-2.5-flash-image-preview) will be deprecated soon. Please migrate to the stable version for production use.
Summary
AvalAI now supports Google's latest state-of-the-art image generation model, Gemini 2.5 Flash Image Preview, alongside expanded image editing capabilities through the v1/images/edits endpoint for seven additional models including Stability AI and Imagen models.
Details
We're excited to announce two major enhancements to our image generation and editing capabilities that provide developers with more powerful and flexible options for their AI-powered applications.
Google Gemini 2.5 Flash Image Preview
Google
- gemini-2.5-flash-image-preview (deprecated - use gemini-2.5-flash-image): Google's latest state-of-the-art image generation model from the Gemini 2.5 family, featuring top-rated image generation and editing capabilities with support for both text-to-image and image-to-image transformations. Documentation
Key Features:
- Input/Output Token Limits: 32,768 tokens each
- Supported Data Types: Images and text input/output
- Capabilities: Image generation, structured outputs, caching
- Knowledge Cutoff: June 2025
- API Access: Available via both
v1/chat/completionsand nativev1betaendpoints
python
from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
# Text to image generation
response = client.chat.completions.create(
model="gemini-2.5-flash-image-preview",
messages=[
{
"role": "user",
"content": "A strange character on a colorful galaxy background, with lots of stars and planets.",
}
],
modalities=["image", "text"],
)
# Image is now available in the response
image_url = response.choices[0].message.images[0]["image_url"]["url"]
content = (
response.choices[0].message.content.strip()
if response.choices[0].message.content
else None
)
# Process the returned image data
header, base64_data = image_url.split(",", 1)
ext = header.split(";")[0].split("/")[1]
import base64
image_bytes = base64.b64decode(base64_data)
with open(f"generated_image.{ext}", "wb") as f:
f.write(image_bytes)
print(f"✅ Image saved as generated_image.{ext}")
# Print any text response that came with the image
if content:
print(f"Model response: {content}")javascript
import { OpenAI } from "openai";
const client = new OpenAI({
apiKey: process.env.AVALAI_API_KEY,
baseURL: "https://api.avalai.ir/v1",
});
// Text to image generation
const response = await client.chat.completions.create({
model: "gemini-2.5-flash-image-preview",
messages: [{
role: "user",
content: "A strange character on a colorful galaxy background, with lots of stars and planets."
}],
modalities: ["image", "text"],
});
// Image is now available in the response
const imageUrl = response.choices[0].message.images[0].image_url.url;
const content = response.choices[0].message.content ? response.choices[0].message.content.trim() : null;
// Process the returned image data
const [header, base64Data] = imageUrl.split(",", 2);
const ext = header.split(";")[0].split("/")[1];
const imageBytes = Buffer.from(base64Data, 'base64');
require('fs').writeFileSync(`generated_image.${ext}`, imageBytes);
console.log(`✅ Image saved as generated_image.${ext}`);
// Print any text response that came with the image
if (content) {
console.log(`Model response: ${content}`);
}Expanded Image Edit Endpoint Support
We've significantly expanded the v1/images/edits endpoint to support seven additional powerful models for image editing capabilities:
Stability AI
- stability.sd3-large-v1:0: Advanced Stable Diffusion 3 model for high-quality image editing
- stability.sd3-5-large-v1:0: Latest Stable Diffusion 3.5 model with enhanced editing capabilities
Google
- imagen-3.0-generate-001: Google's Imagen 3.0 model for sophisticated image editing and generation
python
import requests
from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
# Edit existing image
with open("input_image.png", "rb") as image_file:
response = client.images.edit(
model="stability.sd3-5-large-v1:0",
image=image_file,
prompt="Add a rainbow in the sky above the mountains",
size="1024x1024",
n=1,
response_format="url", # or b64_json
)
# Save edited image
edited_image_url = response.data[0].url
edited_image = requests.get(edited_image_url)
with open("edited_image.png", "wb") as f:
f.write(edited_image.content)
print("✅ Image edited and saved as edited_image.png")javascript
import fs from 'fs';
import { OpenAI } from "openai";
const client = new OpenAI({
apiKey: process.env.AVALAI_API_KEY,
baseURL: "https://api.avalai.ir/v1",
});
// Edit existing image
const imageFile = fs.createReadStream("input_image.png");
const response = await client.images.edit({
model: "stability.sd3-5-large-v1:0",
image: imageFile,
prompt: "Add a rainbow in the sky above the mountains",
size: "1024x1024",
n: 1,
response_format: "url", // or b64_json
});
// Save edited image
const editedImageUrl = response.data[0].url;
const imageResponse = await fetch(editedImageUrl);
const imageBuffer = await imageResponse.arrayBuffer();
fs.writeFileSync("edited_image.png", Buffer.from(imageBuffer));
console.log("✅ Image edited and saved as edited_image.png");