Perplexity

Perplexity API Pricing

AI-powered search with real-time web access and citations

5 paid models · 16 free · Price range: $1.00 - $3.00 /1M

About Perplexity

Perplexity combines large language models with real-time web search to provide accurate, cited answers. Their API enables developers to build applications with built-in web search capabilities, making it ideal for applications requiring current information with source attribution.

Key Highlights

  • Real-time web search integration
  • Automatic source citations
  • Sonar models for search-augmented generation
  • Current information access
  • Reduced hallucination through grounding
Why Choose: Best option for applications requiring real-time web information with citations. Reduces hallucination through grounding.
21
Total Models
$1.00
Lowest Input
200k
Max Context
4
Capabilities

Pricing Features

  • Pay-per-token billing
Pricing Notes:

Pricing includes web search costs. Competitive rates for search-augmented generation use cases.

API Features

StreamingWeb SearchCitationsGrounding

Common Use Cases

  • • Research Assistants
  • • Fact-Checking Applications
  • • News Analysis
  • • Knowledge Base Q&A
  • • Current Events

Perplexity API pricing guide

Focused notes for developers comparing official pricing, API docs, token billing, and model fit.

Perplexity API pricing for Sonar search models

Perplexity API pricing is most useful to evaluate as a search-augmented generation cost, not only as a raw LLM token cost. Sonar models are designed for answers that need fresh web context, source citations, or grounded research workflows, so compare both model price and the value of built-in web search before choosing an alternative.

  • Use Perplexity API pricing docs when you need current official model and search pricing.
  • Compare per-1M token prices here, then convert to per-1K tokens for small request budgets.
  • Choose Sonar-style models when citation quality and current information matter.
  • Use a cheaper non-search LLM when your prompt already contains all required context.

Per-1K and per-1M token planning

Most AI providers publish or compare pricing per 1M tokens, while developers often estimate product features per 1K tokens or per request. Divide a per-1M token price by 1000 to estimate per-1K token cost, then multiply by your expected input and output token mix.

  • A request with web search may justify a higher unit price when it replaces your own search pipeline.
  • Track input and output tokens separately because long cited answers can increase output cost.
  • Use the calculator link from this page to model monthly Perplexity API usage.

Related search terms

Perplexity API pricing docs Perplexity API pricing per 1k tokens 2026 Perplexity Sonar API pricing Perplexity search API pricing official Perplexity API token cost

📊 Perplexity Model Comparison

Compare all models side by side. Sorted by total price (input + output).

Model Tier Input /1M Output /1M Total /1M Context Best For
Sonar Budget $1.00 $1.00 $2.00 127k Image analysis
Sonar Deep Research Balanced $2.00 $8.00 $10.00 128k Complex reasoning, math
Sonar Reasoning Pro Balanced $2.00 $8.00 $10.00 128k Complex reasoning, math
Sonar Pro Search Flagship $3.00 $15.00 $18.00 200k Complex reasoning, math
Sonar Pro Flagship $3.00 $15.00 $18.00 200k Image analysis

🎯 Which Perplexity Model Should You Choose?

Quick recommendations based on your use case.

💰

Lowest Cost

Best value for budget-conscious projects.

Sonar
$2.00 total
💬

Chat / Customer Service

High volume, short responses.

Sonar
$2.00 total
🧠

Complex Reasoning

Math, logic, multi-step problems.

Sonar Deep Research
$10.00 total
👁️

Image Understanding

Analyze images and documents.

Sonar
$2.00 total
📄

Long Documents

Process large files and contexts.

Sonar Pro Search
200k context

💰 Perplexity Monthly Cost Examples

Estimated monthly costs for common use cases.

Use Case Monthly Usage Sonar
(Budget)
Sonar Reasoning
(Flagship)
Customer Service Bot
1000 conversations/day
500k input
200k output
$0.70/mo $0.00/mo
Code Assistant
200 requests/day
1.0M input
500k output
$1.50/mo $0.00/mo
Data Analysis
500 analyses/day
2.0M input
300k output
$2.30/mo $0.00/mo

⚔️ Perplexity vs Competitors

How does {brand} compare to other major AI providers?

Brand Model Input /1M Output /1M Total /1M Context vs {brand}
Perplexity Perplexity Sonar Reasoning Current Free Free Free 127k
OpenAI OpenAI Codex Mini $1.50 $6.00 $7.50 200k Infinity% more
OpenAI OpenAI GPT-5.2 Pro $21.00 $168.00 $189.00 400k Infinity% more
OpenAI OpenAI GPT-5.2 $1.75 $14.00 $15.75 400k Infinity% more
OpenAI OpenAI GPT-5.1-Codex-Max $1.25 $10.00 $11.25 400k Infinity% more
OpenAI OpenAI GPT-5.1 $1.25 $10.00 $11.25 400k Infinity% more
OpenAI OpenAI GPT-5.1-Codex $1.25 $10.00 $11.25 400k Infinity% more

❓ Perplexity Pricing FAQ

What is the cheapest Perplexity model?

The cheapest Perplexity model is Sonar at $2.00 per 1M tokens (input + output combined).

What is the maximum context length for Perplexity models?

Perplexity models support up to 200k context length, allowing you to process large documents and maintain long conversations.

How do I choose between Perplexity models?

For budget projects, choose the cheapest model. For code generation, prioritize low output price. For complex reasoning, choose models with reasoning capability. Use our scenario guide above.

Where should I check Perplexity API pricing docs?

Use the official API docs and pricing link from this page for final verification, then use the table here to compare Perplexity models with other AI APIs on the same per-token basis.

How do I convert Perplexity API pricing per 1M tokens to per 1K tokens?

Divide the per-1M token price by 1000. For a real request estimate, calculate input tokens and output tokens separately because they may have different prices.

When is Perplexity API pricing worth it compared with a cheaper LLM?

It is usually worth considering when your application needs fresh web information, citations, source-grounded answers, or research workflows that would otherwise require a separate search and retrieval stack.