Perplexity

Sonar Pro

Sonar Pro is a search-augmented text generation model developed by Perplexity, designed to handle complex research queries that require thorough source attribution and multi-step reasoning. It operates with a 200,000-token context window, allowing it to process large volumes of information within a single session. The model supports both text and image inputs and can produce up to 8,192 output tokens per response. It also includes function calling, structured output generation, and a reasoning mode for analytical tasks. Sonar Pro is Perplexity's premium tier offering within the Sonar model family, delivering approximately twice the citations and search results compared to the standard Sonar model. This makes it particularly well-suited for enterprise applications, professional research workflows, and use cases that demand comprehensive source coverage and reliable multi-step query handling. The model's training data extends through March 2025, and its live web search integration means responses can draw on current information beyond that date. It is available via API for developers building research-intensive or knowledge-heavy applications.

Mar 07, 2025 200K context 8,000 tokens output
Web Search Integration Large Context Window Multi-Step Reasoning Vision Input Structured Output Content Moderation

Model Overview

High-signal model metadata in a structured two-column overview table.

Provider

The entity that provides this model.

Perplexity

Model ID

The routed model identifier exposed by upstream providers.

perplexity/sonar-pro

Input Context Window

The number of tokens supported by the input context window.

200K tokens

Maximum Output Tokens

The number of tokens that can be generated by the model in a single request.

8,000 tokens tokens

Open Source

Whether the model's code is available for public use.

No

Release Date

When the model was first released.

Mar 07, 2025 1 year ago

Knowledge Cut-off Date

When the model's knowledge was last updated.

Unknown

API Providers

The providers that offer this model. This is not an exhaustive list.

Perplexity

Modalities

Types of data this model can process.

Text Image

What is Sonar Pro

A fuller summary of positioning, capabilities, and source-specific details for Sonar Pro.

Sonar Pro is a search-augmented text generation model developed by Perplexity, designed to handle complex research queries that require thorough source attribution and multi-step reasoning. It operates with a 200,000-token context window, allowing it to process large volumes of information within a single session. The model supports both text and image inputs and can produce up to 8,192 output tokens per response. It also includes function calling, structured output generation, and a reasoning mode for analytical tasks.

Sonar Pro is Perplexity's premium tier offering within the Sonar model family, delivering approximately twice the citations and search results compared to the standard Sonar model. This makes it particularly well-suited for enterprise applications, professional research workflows, and use cases that demand comprehensive source coverage and reliable multi-step query handling. The model's training data extends through March 2025, and its live web search integration means responses can draw on current information beyond that date. It is available via API for developers building research-intensive or knowledge-heavy applications.

Capabilities

What Sonar Pro supports

AI

Web Search Integration

Retrieves live web results at inference time, providing grounded answers with citations. Delivers approximately 2x more citations per response compared to the standard Sonar model.

CTX

Large Context Window

Supports a 200,000-token context window, enabling processing of lengthy documents or extended multi-turn conversations in a single session.

RN

Multi-Step Reasoning

Includes a reasoning mode that breaks down complex queries into sub-tasks, gathers information from multiple angles, and synthesizes a coherent response.

AI

Vision Input

Accepts image inputs alongside text, allowing the model to interpret and reason over visual content as part of a query.

JSON

Structured Output

Supports structured output generation and function calling, making it suitable for integration into programmatic workflows and agent pipelines.

AI

Content Moderation

Includes built-in content moderation support to help filter and manage outputs in safety-sensitive deployment contexts.

Pricing for Sonar Pro

Primary API pricing shown in the same “quick compare” spirit as the reference page.

Price Comparison

Additional usage-cost dimensions synced into the project for this model.

Web search $5000.00
maxTemperature 1.9
maxResponseSize 8,000 tokens

API Access & Providers

Places where this model is available, based on the synced detail-page metadata.

Perplexity

Provider Endpoints

Endpoint-level provider data currently available for this model.

Perplexity

Max output: 8,000 1d uptime: 100.0% Supported params: 7 Implicit caching: No

Configuration & Parameters

The configurable options currently documented for this model.

Return Citations

Select

Determines whether or not a request to an online model should return citations.

Default: false
No Yes

Return Images

Select

Determines whether or not a request to an online model should return images.

Default: false
No Yes

Supported Request Parameters

Parameters currently listed by OpenRouter or the local catalog for this model.

Return Citations Return Images

Model Performance

Benchmark scores synced from the current model source and normalized into the local catalog.

Benchmark Score
AIME 2024
American math olympiad problems
29.0%
GPQA Diamond
PhD-level science questions (biology, physics, chemistry)
57.8%
HLE
Questions that challenge frontier models across many domains
7.9%
LiveCodeBench
Real-world coding tasks from recent competitions
27.5%
MATH-500
Undergraduate and competition-level math problems
74.5%
MMLU-Pro
Expert knowledge across 14 academic disciplines
75.5%
SciCode
Scientific research coding and numerical methods
22.6%

Resources & Documentation

Official model cards, release notes, docs, and other references synced from the source page.

Community discussion

What people think about Sonar Pro

Sonar Pro discussions are most active in r/perplexity_ai, r/steelseries, r/mcp. The strongest match in this snapshot has 122 upvotes and 13 comments.

Hey `r/perplexity_ai`,

I've been working on a fun personal project called **MuseWeb**, a small Go server that generates entire web pages live using an AI model. My goal was to test how different models handle a complex, creative task: building a coherent and aesthetically pleasing website from just a set of text-based prompts.

After testing various local models, I connected it to the Perplexity API to try out the Sonar models. I have to say, I was genuinely blown away by the quality. The `sonar-pro` model, in particular, produces incredibly elegant, well-structured, and creative pages. It has a real knack for design and for following the detailed instructions in my system prompt.

Since this community appreciates the "how" behind the "what," I wanted to share the project and the prompts I'm using. I just pushed a new version (1.0.7) with a few bug fixes, so it's a great time to try it out.

**GitHub Repo:** [https://github.com/kekePower/museweb](https://github.com/kekePower/museweb)

---

### **The Recipe: How to Get Great Results with Sonar**

The magic is all in the prompts. I feed the model a very strict "brand guide" and then a simple instruction for each page. The server automatically maps a file like `about.txt` to the URL `/?prompt=about`.

**For those who want a deep dive into the entire prompt engineering process**—including the iterations, the bugs we fixed, and our findings—I've written up a detailed document here:
**[MuseWeb Prompt Engineering Deep Dive](https://github.com/kekePower/museweb/blob/main/museweb-prompt-engineering.md)**

For a quick look, here is a snippet of the core `system_prompt.txt` that defines the rules:
```
You are The Brand Custodian, a specialized AI front-end developer. Your sole purpose is to build and maintain the official website for a specific, predefined company. You must ensure that every piece of content, every design choice, and every interaction you create is perfectly aligned with the detailed brand identity and lore provided below. Your goal is consistency and faithful representation.

---
### 1. THE CLIENT: Terranexa (A Fictional Eco-Tech Company)
* **Mission:** To create self-sustaining ecosystems by harmonizing technology with nature.
* **Core Principles:** 1. Symbiotic Design, 2. Radical Transparency, 3. Long-Term Resilience.

---
### 2. MANDATORY STRUCTURAL RULES
* A single, fixed navigation bar at the top of the viewport.
* MUST contain these 5 links in order: Home, Our Technology, Sustainability, About Us, Contact. The `href` for these links must point to the prompt names, e.g., `<a href="/?prompt=home">Home</a>`, `<a href="/?prompt=technology">Our Technology</a>`, etc. The server automatically handles the root path `/` as the home page.
* If a footer exists, the copyright year MUST be **2025**.

---
### 3. TECHNICAL & CREATIVE DIRECTIVES
* Your entire response **MUST** be a single HTML file.
* You **MUST NOT** link to any external CSS or JS files. All styles MUST be in a `<style>` tag.
* You **MUST NOT** use any Markdown syntax. Use proper HTML tags for all formatting.
```

---

### **How to Try It Yourself with Perplexity**

MuseWeb is designed to be easy to run. You just need Go installed.

**1. Clone and Build:**
```bash
git clone https://github.com/kekePower/museweb.git
cd museweb
go build .
```

**2. Configure for Perplexity:**
Copy `config.example.yaml` to `config.yaml` and set it up for the Perplexity API.

```yaml
# config.yaml
server:
port: "8080"
prompts_dir: "./prompts"

model:
backend: "openai" # Perplexity uses an OpenAI-compatible API
name: "sonar-large-32k-chat" # Or "sonar-small-32k-online", etc.

openai:
api_key: "pplx-YOUR_PERPLEXITY_API_KEY" # Get one from your Perplexity account
api_base: "https://api.perplexity.ai"
```

**3. Run It!**
```bash
./museweb
```
Now open `http://localhost:8080` and see what Sonar creates!

I'm super impressed with how well Perplexity's models handle this task. It really shows off their creative and instruction-following capabilities beyond just being a great search/answer engine.

I'd love to hear your thoughts or if you give it a try with other Sonar models. Happy to answer any questions

Open Reddit thread
r/Fishing_Gear 1 upvotes 1 comments February 21, 2026
Deeper Smart Sonar PRO+ 2 Fishfinder

Just came across this. Has anyone ever used this sonar. I'm an avid pond hopper and have always wanted to see what's in those ponds. Yes I know it's expensive and that I'd have to get a subscription. Besides that, is it a good picture, good quality, stuff like that

Open Reddit thread
r/Polaroid 54 upvotes 12 comments June 29, 2025
SX-70 Sonar ProPack I-Wide!

This thing is definitely not ready for prime time but it’s starting to come along.

The thought behind all this is a SLR basically has two shutters but one is a moving mirror.

So why not mount the SX-70 Sonar shutter in front of another shutter and then sync them up like the moving mirror? I guess it works!

There’s another video in comments.

Open Reddit thread
r/steelseries 1 upvotes 3 comments November 20, 2025
Nova Pro Wireless with Wicked Crushins and Sonar Presets ?

Hey everyone,

I'd like to buy the WC Stealth Pads for my Nova Pro Wireless.

According to YouTube, you're supposed to adjust the EQ after changing the ear pads because the sound changes. That makes sense.

However, I also use Sonar with different profiles depending on the game (Battlefield, COD, Arc Raiders).

So, what do I do if I have the Stealth Pads and want to use a Sonar profile for a specific game?

Do I have to combine both EQ settings to get the best gaming experience? What's the correct way to do this?

I strongly suspect that the individual profiles in Sonar are designed for the original ear pads.

Open Reddit thread
View more discussions →
FAQ

Common questions about Sonar Pro

What is the context window size for Sonar Pro?

Sonar Pro supports a 200,000-token context window, allowing it to process large documents or long multi-turn conversations within a single session.

What is the maximum number of output tokens per response?

Sonar Pro can generate up to 8,192 output tokens per response.

What is the knowledge cutoff date for Sonar Pro?

The model's training data extends through March 2025. However, because Sonar Pro integrates live web search, it can also surface information published after that date.

Does Sonar Pro support image inputs?

Yes, Sonar Pro supports both text and image inputs, enabling the model to interpret visual content as part of a query.

How does Sonar Pro differ from the standard Sonar model?

Sonar Pro is Perplexity's premium tier and delivers approximately twice the citations and search results per response compared to the standard Sonar model. It also includes a reasoning mode and supports more complex, multi-step queries.

Does Sonar Pro support function calling?

Yes, Sonar Pro supports function calling and structured output generation, making it compatible with agent-based and programmatic integration workflows.

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