Gemini 2.5 Flash Image (Nano Banana) Stable Release
Date: 2025-10-09
Summary
Google Gemini has released the stable version of their state-of-the-art image generation model, gemini-2.5-flash-image (Nano Banana). This model replaces the preview version and provides enhanced stability and performance for production use. The preview version (gemini-2.5-flash-image-preview) will be deprecated in the coming weeks.
Details
Stable Model Release
We announce the availability of gemini-2.5-flash-image, the stable production-ready version of Google's advanced image generation and editing model from the Gemini 2.5 family. This release marks the transition from the preview phase to a fully supported, production-grade model.
Google
- gemini-2.5-flash-image: Google's stable state-of-the-art image generation model featuring top-rated image generation and editing capabilities with support for both text-to-image and image-to-image transformations. Documentation
Key Features:
- State-of-the-art image generation - Create high-quality, photorealistic images from detailed text prompts
- Advanced image editing - Transform existing images with natural language instructions
- Character consistency - Maintain consistent appearance of subjects across multiple generations
- Multi-image fusion - Combine multiple input images into cohesive compositions
- Conversational editing - Iterative refinement through natural dialogue
- Production stability - Enhanced reliability and consistent performance for production workloads
- Context Window: 32,768 tokens for handling extensive conversations
- Dual Output: Supports both image and text outputs
- Endpoint Support: Available on
v1/chat/completionswith modalities parameter
Pricing Details:
| Model | Input | Output (Text) | Output (Image) |
|---|---|---|---|
| gemini-2.5-flash-image | $0.30/1M tokens | $2.50/1M tokens | $30.00/1M tokens |
Migration from Preview Version
If you are currently using gemini-2.5-flash-image-preview, we recommend migrating to the stable gemini-2.5-flash-image model. The preview version will be deprecated soon. Migration is seamless - simply update the model name in your API calls:
diff
- model="gemini-2.5-flash-image-preview"
+ model="gemini-2.5-flash-image"All features and capabilities remain the same, with improved stability and performance in the stable release.
Usage Example
bash
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gemini-2.5-flash-image",
"messages": [
{
"role": "user",
"content": "A photorealistic image of a mountain landscape with a lake reflecting the sunset"
}
],
"modalities": ["image", "text"]
}'python
from openai import OpenAI
import base64
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",
messages=[
{
"role": "user",
"content": "A photorealistic image of a mountain landscape with a lake reflecting the sunset",
}
],
modalities=["image", "text"],
)
# Image is 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]
# Decode and save image
image_bytes = base64.b64decode(base64_data)
filename = f"generated_image.{ext}"
with open(filename, "wb") as f:
f.write(image_bytes)
print(f"✅ Image saved as {filename}")javascript
import { OpenAI } from "openai";
import fs from 'fs';
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",
messages: [{
role: "user",
content: "A photorealistic image of a mountain landscape with a lake reflecting the sunset"
}],
modalities: ["image", "text"],
});
// Image is 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];
// Decode and save image
const imageBytes = Buffer.from(base64Data, 'base64');
const filename = `generated_image.${ext}`;
fs.writeFileSync(filename, imageBytes);
console.log(`✅ Image saved as ${filename}`);Image-to-Image Editing Example
bash
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gemini-2.5-flash-image",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Transform this image into a Studio Ghibli anime style"
},
{
"type": "image_url",
"image_url": {
"url": "https://example.com/your-image.jpg"
}
}
]
}
],
"modalities": ["image", "text"]
}'python
# Image to image transformation
prompt = "Transform this image into a Studio Ghibli anime style"
image_url = "https://example.com/your-image.jpg"
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": prompt},
{"type": "image_url", "image_url": {"url": image_url}},
],
}
]
response = client.chat.completions.create(
model="gemini-2.5-flash-image",
messages=messages,
modalities=["image", "text"],
)
# Process the response the same way as text-to-image
image_url = response.choices[0].message.images[0]["image_url"]["url"]javascript
// Image to image transformation
const prompt = "Transform this image into a Studio Ghibli anime style";
const imageUrl = "https://example.com/your-image.jpg";
const messages = [
{
role: "user",
content: [
{ type: "text", text: prompt },
{ type: "image_url", image_url: { url: imageUrl } },
],
}
];
const response = await client.chat.completions.create({
model: "gemini-2.5-flash-image",
messages: messages,
modalities: ["image", "text"],
});
// Process the response
const resultImageUrl = response.choices[0].message.images[0].image_url.url;