AI model comparison

Llama 4 Scout vs Sonar

Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B.

Input / 1M
$0.18
Output / 1M
$0.59
Context
1.31M
perplexity logo

Perplexity

Sonar

Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources.

Input / 1M
$1
Output / 1M
$1
Context
127K

At a glance

Quick verdict

How the two models stack up on the things people ask about most.

Lower price

meta-llama logo

Llama 4 Scout

3.8x cheaper for a typical chat

Higher intelligence score

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Llama 4 Scout

8.1 vs 7.7 on Artificial Analysis

Larger context window

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Llama 4 Scout

1.31M vs 127K tokens

Newer release

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Llama 4 Scout

Released April 5, 2025

Benchmarks

Benchmark scores

Independent scores from Artificial Analysis. Higher is better.

Intelligence index

meta-llama logoLlama 4 Scout8.1
perplexity logoSonar7.7

Coding index

meta-llama logoLlama 4 Scout8.2
perplexity logoSonarNot available

Agentic index

meta-llama logoLlama 4 Scout0.5
perplexity logoSonarNot available

Pricing

Llama 4 Scout vs Sonar API pricing

Per-token API rates. Cheaper option highlighted.

Metricmeta-llama logoLlama 4 Scoutperplexity logoSonar
Input tokensPer 1M tokens$0.18$1
Output tokensPer 1M tokens$0.59$1
Cached input (read)Per 1M tokensNot availableNot available
Cache writePer 1M tokensNot availableNot available
Web searchPer requestNot available$0.005

What it costs in practice

Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.

Chat message

2K in, 500 out

meta-llama logoLlama 4 Scout$0.66
perplexity logoSonar$2.50

Coding task

30K in, 4K out

meta-llama logoLlama 4 Scout$7.76
perplexity logoSonar$34

Long document summary

150K in, 2K out

meta-llama logoLlama 4 Scout$28.18
perplexity logoSonar$152

Specs

Context window and capabilities

How much each model can read, how much it can write, and what it accepts as input.

Metricmeta-llama logoLlama 4 Scoutperplexity logoSonar
Context window1.31M tokens127K tokens
Max output118K tokens114K tokens
Input typesImage, TextImage, Text
Output typesTextText
Reasoning effort levelsNot availableNot available
Default reasoning effortNot availableNot available
Release dateApril 5, 2025January 27, 2025

Features

Supported features

API features available for each model.

Metricmeta-llama logoLlama 4 Scoutperplexity logoSonar
Tool callingSupportedNot supported
Structured outputsSupportedNot supported
JSON modeSupportedNot supported
ReasoningNot supportedNot supported
TemperatureSupportedSupported
Stop sequencesSupportedNot supported
Deterministic seedSupportedNot supported
Verbosity controlNot supportedNot supported

Our take

Llama 4 Scout is 3.8x cheaper for a typical chat. Llama 4 Scout scores higher on the Artificial Analysis Intelligence Index (8.1 vs 7.7). Llama 4 Scout has the larger context window (1.31M vs 127K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.

FAQ

Frequently asked questions

Is Llama 4 Scout or Sonar cheaper?

Llama 4 Scout is cheaper for a typical chat (2K input tokens and 500 output tokens). Llama 4 Scout costs $0.18 per 1M input tokens and $0.59 per 1M output tokens, while Sonar costs $1 per 1M input tokens and $1 per 1M output tokens.

Which has a bigger context window, Llama 4 Scout or Sonar?

Llama 4 Scout supports up to 1.31M tokens of context, compared with 127K for Sonar.

Is Llama 4 Scout smarter than Sonar?

On the Artificial Analysis Intelligence Index, Llama 4 Scout scores 8.1 and Sonar scores 7.7, putting Llama 4 Scout ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.

Can I use Llama 4 Scout and Sonar at the same time?

Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Llama 4 Scout and Sonar answer side by side and keep the better response.

meta-llama logoperplexity logo

Why choose? Ask both.

Send one prompt to Llama 4 Scout and Sonar at the same time. Compare the answers side by side and keep the best one.