Perplexity Sonar Models Now Available
Date: 2025-10-26
Summary
AvalAI now supports 5 new Perplexity Sonar models with advanced web search capabilities and reasoning features. These models provide real-time web search integration, Chain-of-Thought reasoning, and comprehensive research capabilities through our unified API with support for multiple endpoints including v1/chat/completions, v1/completions, v1/messages, and v1/responses.
Details
Perplexity
We introduce 5 new models from Perplexity that combine AI-powered text generation with real-time web search and reasoning capabilities:
sonar: Fast answers with reliable search results. A lightweight, cost-effective search model optimized for quick, grounded answers with real-time web search. 128K context length.
sonar-pro: Advanced search with enhanced search results. An advanced search model designed for complex queries, delivering 2x more search results than standard Sonar. 200K context length.
sonar-reasoning: Quick reasoning with real-time search. A reasoning-focused model that applies Chain-of-Thought (CoT) reasoning for structured analysis with web search. 128K context length.
sonar-reasoning-pro: Advanced reasoning with comprehensive search. Enhanced Chain-of-Thought reasoning with 2x more search results for complex multi-step analysis. 128K context length.
sonar-deep-research: Exhaustive research across hundreds of sources. Expert-level subject analysis with detailed report generation and citation support. 128K context length.
Key Features:
- Real-Time Web Search: All models integrate live web search with citations and search results metadata
- Chain-of-Thought Reasoning: Reasoning models support structured problem-solving with detailed thinking processes
- Flexible Context Windows: 128K-200K context lengths for handling extensive documents
- Multiple API Endpoints: Full support for v1/chat/completions and v1/completions; partial support for v1/messages and v1/responses
- Citation Support: Automatic citation generation with source URLs and search result metadata
- Cost-Effective Options: Various pricing tiers from free input tokens to premium deep research capabilities
Pricing Details:
| Model | Input | Cached Input | Output | Special Pricing |
|---|---|---|---|---|
| sonar | $1.00/1M tokens | $0.50/1M tokens | $1.00/1M tokens | $5-$12 per 1K requests (search context) |
| sonar-pro | $3.00/1M tokens | $1.50/1M tokens | $15.00/1M tokens | $6-$14 per 1K requests (search context) |
| sonar-reasoning | $1.00/1M tokens | $0.50/1M tokens | $5.00/1M tokens | $5-$12 per 1K requests (search context) |
| sonar-reasoning-pro | $2.00/1M tokens | $1.00/1M tokens | $8.00/1M tokens | $6-$14 per 1K requests (search context) |
| sonar-deep-research | $2.00/1M tokens | $1.00/1M tokens | $8.00/1M tokens | $3.00/1M reasoning tokens, $2.00/1M citation tokens, $0.005 per search query |
Note: Search context pricing varies based on query complexity (low/medium/high) and is charged per 1K requests.
API Request/Response Examples
Example Request - Sonar
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "sonar",
"messages": [
{
"role": "user",
"content": "What is the latest news in AI research?"
}
]
}'Example Response - Sonar
{
"id": "80cff570-614d-4344-8cd4-9f78af816a3d",
"created": 1761492286,
"model": "sonar",
"object": "chat.completion",
"system_fingerprint": null,
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": "The latest news in AI research for 2025 highlights several groundbreaking advances...",
"role": "assistant",
"annotations": []
}
}
],
"usage": {
"completion_tokens": 592,
"prompt_tokens": 9,
"total_tokens": 601,
"completion_tokens_details": null,
"prompt_tokens_details": null,
"cost": {
"input_tokens_cost": 0.0,
"output_tokens_cost": 0.001,
"request_cost": 0.005,
"total_cost": 0.006
},
"search_context_size": "low"
},
"citations": [
"https://news.microsoft.com/source/features/ai/6-ai-trends-youll-see-more-of-in-2025/",
"https://news.stanford.edu/artificial-intelligence",
"https://www.artificialintelligence-news.com"
],
"search_results": [
{
"title": "6 AI trends you'll see more of in 2025 - Microsoft Source",
"url": "https://news.microsoft.com/source/features/ai/6-ai-trends-youll-see-more-of-in-2025/",
"date": "2024-12-05",
"last_updated": "2025-10-26",
"snippet": "In 2025, AI will evolve from a tool for work and home to an integral part of both...",
"source": "web"
}
],
"estimated_cost": {
"unit": "0.0006010000",
"irt": 65.03,
"exchange_rate": 108200
}
}Example Request - Sonar Reasoning
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "sonar-reasoning",
"messages": [
{
"role": "user",
"content": "Design a comprehensive digital marketing strategy for a tech startup"
}
]
}'SDK Usage Examples
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "sonar",
"messages": [
{
"role": "user",
"content": "What are the latest developments in quantum computing?"
}
]
}'from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
completion = client.chat.completions.create(
model="sonar",
messages=[
{
"role": "user",
"content": "What are the latest developments in quantum computing?",
}
],
)
print(completion.choices[0].message.content)
# Access citations and search results
print(completion.citations)
print(completion.search_results)import { OpenAI } from "openai";
const client = new OpenAI({
apiKey: process.env.AVALAI_API_KEY,
baseURL: "https://api.avalai.ir/v1",
});
const completion = await client.chat.completions.create({
model: "sonar",
messages: [
{
role: "user",
content: "What are the latest developments in quantum computing?",
},
],
});
console.log(completion.choices[0].message.content);
// Access citations and search results
console.log(completion.citations);
console.log(completion.search_results);Reasoning Model Usage
For reasoning models like sonar-reasoning and sonar-reasoning-pro, the model shows its thinking process:
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "sonar-reasoning",
"messages": [
{
"role": "user",
"content": "Analyze the competitive landscape of AI search engines"
}
],
"max_tokens": 2048
}'response = client.chat.completions.create(
model="sonar-reasoning",
messages=[
{
"role": "user",
"content": "Analyze the competitive landscape of AI search engines",
}
],
max_tokens=2048,
)
# The model will show its Chain-of-Thought reasoning process
print(response.choices[0].message.content)const response = await client.chat.completions.create({
model: "sonar-reasoning",
messages: [
{
role: "user",
content: "Analyze the competitive landscape of AI search engines",
},
],
max_tokens: 2048,
});
// The model will show its Chain-of-Thought reasoning process
console.log(response.choices[0].message.content);API Endpoint Support
Full Support:
v1/chat/completions: Complete support for all Perplexity Sonar models with streamingv1/completions: Text completion format support
Partial Support:
v1/messages: Anthropic-style messages APIv1/responses: Alternative response format
Use Cases by Model
Sonar: Quick searches, fact-checking, news summaries, straightforward Q&A
Sonar Pro: Complex research questions, comparative analysis, information synthesis
Sonar Reasoning: Multi-step problem solving, logical analysis, strategic planning
Sonar Reasoning Pro: Advanced multi-step analysis, deep reasoning tasks, comprehensive decision making
Sonar Deep Research: Academic research, market analysis, due diligence, investigative research
Sonar Medium Chat: Interactive conversations, balanced cost-performance for search tasks
Sonar Medium Online: High-volume applications where token costs need to be minimized