Perplexity: Sonar

Public pricingIntelligence 79/100Medium memoryVision

Perplexity: Sonar is a multimodal model for vision-language understanding. It combines multimodal input handling and image understanding with a 127K tokens context window and a balanced-cost profile. Use it for vision-language understanding and content analysis when latency, cost, and throughput matters.

Input

$1.00/1M

Output

$1.00/1M

Cached

$0.25/1M

Batch

$0.50/1M

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Technical specifications

Sonar at a glance.

Memory

127,072

tokens

Max reply

8,192

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

—

Released

Jan 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

  • Screenshot analysis, image understanding, or document OCR.
  • 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 — 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 costs roughly $115 per month. Input is $1.00 /1M tokens and output is $1.00 /1M tokens.
Sonar has a 127,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 23,826 words of input and history in a single call.
Beyond text generation, Sonar supports understanding images, strict JSON output. It streams replies by default.
Sonar was released in January 2025, with training data cut off around October 2024.
Models in a similar class include Sonar Reasoning Pro, Sonar Pro, Sonar Pro Search. The "Similar models" section below this FAQ links into each.

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