Perplexity: Sonar Pro

Public pricingIntelligence 79/100Large memoryЗрение

Perplexity: Sonar Pro — это мультимодальной‑модель для мультимодальное рассуждение и анализ. Она сочетает обработку мультимодальных входов и глубокое рассуждение и планирование, контекст 200K tokens и профиль премиальный, обеспечивая надёжную работу в задачах мультимодальное рассуждение и анализ.

Input

$3.00/1M

Output

$15.00/1M

Cached

$0.75/1M

Batch

$1.50/1M

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Technical specifications

Sonar Pro at a glance.

Memory

200,000

tokens

Max reply

8,000

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

—

Released

Mar 2025

Training cutoff

Oct 2024

Availability

Public pricing

Status

active

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Sonar Pro

  • Screenshot analysis, image understanding, or document OCR.
  • Long documents, full codebases, or extensive chat histories.
  • Multimodal pipelines mixing text + images.

When to look elsewhere

  • You need tool-use / function calling for agent workflows.

Alternatives

Similar models to compare.

FAQ

Sonar Pro — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

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At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Sonar Pro costs roughly $825 per month. Input is $3.00 /1M tokens and output is $15.00 /1M tokens.
Sonar Pro has a 200,000-token context window (large memory — an entire book or large codebase). That means you can fit about 37,500 words of input and history in a single call.
Beyond text generation, Sonar Pro supports understanding images, strict JSON output. It streams replies by default.
Sonar Pro was released in March 2025, with training data cut off around October 2024.
Models in a similar class include Sonar Pro Search, Claude 3.7 Sonnet, Claude 3.7 Sonnet (thinking). The "Similar models" section below this FAQ links into each.

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