Developer Dashboard

New Models Added: OpenAI Research Models and Google Imagen 4.0

Date: 2025-07-08

Summary

We've expanded our model offerings with powerful new OpenAI research models and Google's latest Imagen 4.0 image generation models. These additions include advanced deep research capabilities and state-of-the-art image generation tools to enhance your AI applications.


Details

OpenAI Research Models

We're excited to announce the addition of OpenAI's latest research models, designed for complex reasoning and deep research tasks:

  • o3-pro: OpenAI's most advanced reasoning model for complex problem-solving and analysis
  • o3-deep-research: Our most powerful deep research model capable of tackling complex, multi-step research tasks with internet search capabilities
  • o4-mini-deep-research: A faster, more affordable deep research model ideal for complex research tasks with excellent cost-performance balance

Important Usage Notes for Research Models

All research models (o3-deep-research, o4-mini-deep-research, and computer-use-preview) are only accessible through the v1/responses endpoint and require tools to be selected. When using search_context_size, it should be set to at least "medium" for optimal performance.

Google Imagen 4.0 Models

Google's latest image generation models are now available, offering enhanced quality and speed:

  • imagen-4.0-ultra-generate-preview-06-06: Ultra-high quality image generation with exceptional detail and realism
  • imagen-4.0-generate-preview-06-06: High-quality image generation for professional applications
  • imagen-4.0-fast-generate-preview-06-06: Fast image generation optimized for speed while maintaining quality

Usage Examples

Research Models (v1/responses endpoint)

python
import requests

url = "https://api.avalai.ir/v1/responses"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $AVALAI_API_KEY",
}

data = {
    "model": "o3-deep-research",
    "tools": [{"type": "web_search", "search_context_size": "medium"}],
    "input": "Research the latest developments in quantum computing",
}

response = requests.post(url, headers=headers, json=data)
print(response.json())
javascript
const response = await fetch('https://api.avalai.ir/v1/responses', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer $AVALAI_API_KEY'
  },
  body: JSON.stringify({
    model: 'o3-deep-research',
    tools: [{ type: 'web_search_preview', search_context_size: 'medium' }],
    input: 'Research the latest developments in quantum computing'
  })
});

const result = await response.json();
console.log(result);
bash
curl -i https://api.avalai.ir/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
 "model": "o3-deep-research",
 "tools": [{ "type": "web_search", "search_context_size": "medium"}],
 "input": "Research the latest developments in quantum computing"
 }'

Google Imagen Models (Standard Chat Completions)

python
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="imagen-4.0-generate-preview-06-06",
    messages=[
        {
            "role": "user",
            "content": "Generate a beautiful landscape with mountains and a lake at sunset",
        }
    ],
)

print(response.choices[0].message.content)
javascript
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: "imagen-4.0-generate-preview-06-06",
  messages: [
    {
      role: "user",
      content:
        "Generate a beautiful landscape with mountains and a lake at sunset",
    },
  ],
});

console.log(response.choices[0].message.content);