New Models Added: Gemini 3 Pro Image, Gemini 3.1 Flash Image Stable, and Qwen3-Max
Date: 2026-06-05 / (1405-03-15)
Summary
We announce the addition of three new models. Google's gemini-3-pro-image (Nano Banana Pro) and gemini-3.1-flash-image (Nano Banana 2) are now available as stable aliases, graduating from their preview releases with identical capabilities and pricing. Alibaba's qwen3-max flagship model is also available for complex reasoning and agentic workflows.
Details
Google (Gemini)
Gemini 3 Pro Image (Nano Banana Pro) — Stable Release
gemini-3-pro-image is the stable release of gemini-3-pro-image-preview, previously announced in our November 20, 2025 update. The stable alias delivers the same capabilities and pricing as the preview model, providing a reliable option for professional, production-grade image generation and editing. It remains the leading model for rendering Persian characters in images with near-perfect accuracy.
| Feature | Details |
|---|---|
| Model ID | gemini-3-pro-image |
| Alias | Nano Banana Pro |
| Max output | Images up to 4K resolution (4096x4096px), plus text responses |
| Inputs | Text prompts, reference images |
| Outputs | Images (1K-4K resolution) and text |
| Input pricing | $2.00 / 1M tokens (text), $2.00 / 1M tokens (image input, ~$0.067 per image) |
| Cached input pricing | $0.50 / 1M tokens |
| Output pricing | $12.00 / 1M tokens (text), $0.134 per 1K-2K image, $0.24 per 4K image |
| Supported endpoints | v1/chat/completions, v1beta/ |
Key Features:
- Advanced Text Rendering: Renders clear, legible text in images including Persian characters with near-perfect accuracy
- Studio-Quality Control: Fine control over composition, lighting, color grading, and aspect ratios
- Real-World Knowledge: Leverages Google Search for accurate, grounded image generation
- Resolution Support: Generate images up to 4K resolution (4096x4096px)
- Image Editing: Comprehensive editing including aspect ratio adjustments, lighting changes, and subject consistency
- Default "Thinking" Process: Refines composition before generation for optimal results
- Production-Ready: Stable alias suitable for long-term integrations
Gemini 3.1 Flash Image (Nano Banana 2) — Stable Release
gemini-3.1-flash-image is the stable release of gemini-3.1-flash-image-preview, previously announced in our February 27, 2026 update. The stable alias delivers high-fidelity image generation and advanced editing optimized for speed and high-volume developer workflows, serving as the high-efficiency counterpart to Gemini 3 Pro Image.
| Feature | Details |
|---|---|
| Model ID | gemini-3.1-flash-image |
| Alias | Nano Banana 2 |
| Max output | Images up to 4K resolution (4096x4096px), plus text responses |
| Inputs | Text prompts, reference images |
| Outputs | Images (512px-4K resolution) and text |
| Input pricing | $0.50 / 1M tokens (text), $0.50 / 1M tokens (image input) |
| Cached input pricing | $0.25 / 1M tokens |
| Output pricing | $3.00 / 1M tokens (text), $60.00 / 1M tokens (image output) |
| Per-image pricing | $0.0672 per 1K-2K image, $0.101 per 2K-4K image, $0.151 per 4K image |
| Supported endpoints | v1/chat/completions, v1beta/ |
Key Features:
- Improved World Knowledge: Leverages broad world knowledge with web search grounding for enhanced visuals
- Advanced Text Rendering: Reliable, crisp text rendering with in-image localization supporting multiple languages
- Greater Creative Control: Vibrant lighting, richer textures, sharper details with configurable thinking levels
- Native Aspect Ratios: Support for all existing ratios plus 4:1, 1:4, 8:1, and 1:8 ratios
- New 512px Resolution: Optimized for efficiency with minimal latency for rapid iterations
- Google Image Search Grounding: Generate images based on real-world image references
Understanding the Nano Banana Family
Nano Banana is the name for Gemini's native image generation capabilities. Gemini can generate and process images conversationally with text, images, or a combination of both:
- Nano Banana 2 (
gemini-3.1-flash-image): The high-efficiency counterpart to Gemini 3 Pro Image, optimized for speed and high-volume developer use cases - Nano Banana Pro (
gemini-3-pro-image): Designed for professional asset production with advanced reasoning ("Thinking") for complex instructions and high-fidelity text - Nano Banana (
gemini-2.5-flash-image): Designed for speed and efficiency, optimized for high-volume, low-latency tasks
Alibaba (Qwen)
Qwen3-Max
qwen3-max is Alibaba's flagship proprietary model from the Qwen3 Max series, designed for the most demanding applications. It offers superior reasoning, enhanced agent programming, and strong performance on complex multi-step problem-solving and tool-use workflows.
| Feature | Details |
|---|---|
| Model ID | qwen3-max |
| Context window | 262,144 tokens |
| Max output | 32,768 tokens |
| Input pricing | $1.20 / 1M tokens |
| Cached input pricing | $0.10 / 1M tokens |
| Output pricing | $6.00 / 1M tokens |
| Tiered pricing | Above 32K: $2.40 / $12.00, Above 128K: $3.00 / $15.00 |
| Input modalities | Text |
| Output modalities | Text |
| Supported endpoints | v1/chat/completions, v1/responses (partial) |
Key Features:
- Enhanced Agent Programming: Optimized for agentic coding and complex tool-use scenarios
- Superior Reasoning: Strong performance on demanding reasoning and problem-solving tasks
- Large Context Window: 262,144 tokens for extensive conversations and documents
- Real-Time Web Search: Supports web search for up-to-date information (set search strategy to
agentfor international regions) - Hybrid Thinking: Optional reasoning mode via
enable_thinking(streaming only)
Pricing Summary
| Model | Input ($/1M tokens) | Cached Input ($/1M tokens) | Output ($/1M tokens) | Special Pricing |
|---|---|---|---|---|
gemini-3-pro-image | $2.00 (text), $2.00 (image) | $0.50 | $12.00 (text), $120.00 (image) | $0.134 per 1K-2K image, $0.24 per 4K image |
gemini-3.1-flash-image | $0.50 (text), $0.50 (image) | $0.25 | $3.00 (text), $60.00 (image) | $0.0672 (1K-2K), $0.101 (2K-4K), $0.151 (4K) per image |
qwen3-max | $1.20 | $0.10 | $6.00 | Above 32K: $2.40/$12.00, Above 128K: $3.00/$15.00 |
API Request/Response Examples
Gemini 3 Pro Image (OpenAI-Compatible)
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gemini-3-pro-image",
"messages": [
{
"role": "user",
"content": "Create a minimalist poster with Persian text that says \"هوش مصنوعی\" (Artificial Intelligence) in a modern, tech-inspired style with blue and white colors"
}
],
"modalities": ["image", "text"]
}' | jq '.choices[0].message.images[0].image_url.url |= (.[0:100] + "...[TRUNCATED]")'Response:
{
"id": "chatcmpl-xyz123",
"created": 1780000000,
"model": "gemini-3-pro-image",
"object": "chat.completion",
"system_fingerprint": null,
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": "I've created a minimalist tech-inspired poster featuring the Persian text \"هوش مصنوعی\" in a modern style with blue and white colors.",
"role": "assistant",
"images": [
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAAQACAIAAADwf7zU...[TRUNCATED]",
"detail": "auto"
},
"index": 0,
"type": "image_url"
}
],
"thinking_blocks": [],
"annotations": []
}
}
],
"usage": {
"completion_tokens": 1150,
"prompt_tokens": 32,
"total_tokens": 1182,
"completion_tokens_details": null,
"prompt_tokens_details": {
"audio_tokens": null,
"cached_tokens": null,
"text_tokens": 32,
"image_tokens": null
}
},
"estimated_cost": {
"unit": "0.1558000000",
"irt": 17864.68,
"exchange_rate": 114600
}
}Gemini 3 Pro Image (Native Gemini API)
You can also use the native Gemini API (v1beta) endpoint:
GEMINI_API_KEY="$AVALAI_API_KEY"
MODEL_ID="gemini-3-pro-image"
GENERATE_CONTENT_API="generateContent"
cat <<EOF >request.json
{
"contents": [
{
"role": "user",
"parts": [
{
"text": "a cat"
}
]
}
],
"generationConfig": {
"responseModalities": ["IMAGE", "TEXT"]
}
}
EOF
curl \
-X POST \
-H "Content-Type: application/json" \
"https://api.avalai.ir/v1beta/models/${MODEL_ID}:${GENERATE_CONTENT_API}?key=${GEMINI_API_KEY}" \
-d '@request.json' \
--output response.jsonGemini 3.1 Flash Image (Native Gemini API)
GEMINI_API_KEY="$AVALAI_API_KEY"
MODEL_ID="gemini-3.1-flash-image"
GENERATE_CONTENT_API="generateContent"
cat <<EOF >request.json
{
"contents": [
{
"role": "user",
"parts": [
{
"text": "a cat"
}
]
}
],
"generationConfig": {
"responseModalities": ["IMAGE", "TEXT"]
}
}
EOF
curl \
-X POST \
-H "Content-Type: application/json" \
"https://api.avalai.ir/v1beta/models/${MODEL_ID}:${GENERATE_CONTENT_API}?key=${GEMINI_API_KEY}" \
-d '@request.json' \
--output response.jsonQwen3-Max Example
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "qwen3-max",
"messages": [
{
"role": "user",
"content": "Design an intelligent agent system that can autonomously manage complex multi-step workflows with tool invocation capabilities."
}
],
"max_tokens": 2000
}'Response:
{
"id": "chatcmpl-abc789",
"created": 1780000000,
"model": "qwen3-max",
"object": "chat.completion",
"system_fingerprint": null,
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": "Here's a comprehensive design for an intelligent agent system...",
"role": "assistant",
"tool_calls": null
}
}
],
"usage": {
"completion_tokens": 512,
"prompt_tokens": 24,
"total_tokens": 536,
"completion_tokens_details": null,
"prompt_tokens_details": {
"cached_tokens": 0
}
},
"estimated_cost": {
"unit": "0.0031008000",
"irt": 355.35,
"exchange_rate": 114600
}
}SDK Usage Examples
Gemini Image Generation
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gemini-3.1-flash-image",
"messages": [
{
"role": "user",
"content": "Create a modern logo for a tech company called \"AvalAI\" with clean typography and a minimalist design"
}
],
"modalities": ["image", "text"]
}'from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
response = client.chat.completions.create(
model="gemini-3.1-flash-image",
messages=[
{
"role": "user",
"content": 'Create a modern logo for a tech company called "AvalAI" with clean typography and a minimalist design',
}
],
extra_body={"modalities": ["image", "text"]},
)
# Access the generated image
if hasattr(response.choices[0].message, "images"):
images = getattr(response.choices[0].message, "images")
for img in images:
print(f"Image URL: {img.image_url.url[:100]}...")
print(response.choices[0].message.content)import { OpenAI } from "openai";
const client = new OpenAI({
apiKey: process.env.AVALAI_API_KEY,
baseURL: "https://api.avalai.ir/v1",
});
const response = await client.chat.completions.create({
model: "gemini-3.1-flash-image",
messages: [
{
role: "user",
content: "Create a modern logo for a tech company called \"AvalAI\" with clean typography and a minimalist design",
},
],
modalities: ["image", "text"],
});
// Access the generated image
if (response.choices[0].message.images) {
const images = response.choices[0].message.images;
images.forEach((img, idx) => {
console.log(`Image ${idx}: ${img.image_url.url.substring(0, 100)}...`);
});
}
console.log(response.choices[0].message.content);Qwen3-Max
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "qwen3-max",
"messages": [
{
"role": "user",
"content": "Perform a comprehensive analysis of quantum computing's potential impact on cryptography."
}
],
"max_tokens": 2000
}'from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
response = client.chat.completions.create(
model="qwen3-max",
messages=[
{
"role": "user",
"content": "Perform a comprehensive analysis of quantum computing's potential impact on cryptography.",
}
],
max_tokens=2000,
extra_body={"enable_thinking": False}, # Required for non-streaming requests
)
print(response.choices[0].message.content)import { OpenAI } from "openai";
const client = new OpenAI({
apiKey: process.env.AVALAI_API_KEY,
baseURL: "https://api.avalai.ir/v1",
});
const response = await client.chat.completions.create({
model: "qwen3-max",
messages: [
{
role: "user",
content: "Perform a comprehensive analysis of quantum computing's potential impact on cryptography.",
},
],
max_tokens: 2000,
});
console.log(response.choices[0].message.content);