AI model comparison

Qwen3 32B vs Llama 4 Scout

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

Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue.

Input / 1M
$0.08
Output / 1M
$0.28
Context
131K

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
$0.10
Output / 1M
$0.30
Context
1.31M

At a glance

Quick verdict

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

Lower price

qwen logo

Qwen3 32B

1.2x cheaper for a typical chat

Higher intelligence score

qwen logo

Qwen3 32B

8.6 vs 8.1 on Artificial Analysis

Larger context window

meta-llama logo

Llama 4 Scout

1.31M vs 131K tokens

Newer release

qwen logo

Qwen3 32B

Released April 28, 2025

Benchmarks

Benchmark scores

Independent scores from Artificial Analysis. Higher is better.

Intelligence index

qwen logoQwen3 32B8.6
meta-llama logoLlama 4 Scout8.1

Coding index

qwen logoQwen3 32B15.3
meta-llama logoLlama 4 Scout8.2

Agentic index

qwen logoQwen3 32B0.9
meta-llama logoLlama 4 Scout0.5

Pricing

Qwen3 32B vs Llama 4 Scout API pricing

Per-token API rates. Cheaper option highlighted.

Metricqwen logoQwen3 32Bmeta-llama logoLlama 4 Scout
Input tokensPer 1M tokens$0.08$0.10
Output tokensPer 1M tokens$0.28$0.30
Cached input (read)Per 1M tokensNot availableNot available
Cache writePer 1M tokensNot availableNot available

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

qwen logoQwen3 32B$0.30
meta-llama logoLlama 4 Scout$0.35

Coding task

30K in, 4K out

qwen logoQwen3 32B$3.52
meta-llama logoLlama 4 Scout$4.20

Long document summary

150K in, 2K out

qwen logoQwen3 32B$12.56
meta-llama logoLlama 4 Scout$15.60

Specs

Context window and capabilities

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

Metricqwen logoQwen3 32Bmeta-llama logoLlama 4 Scout
Context window131K tokens1.31M tokens
Max output16K tokens16K tokens
Input typesTextImage, Text
Output typesTextText
Reasoning effort levelsNot availableNot available
Default reasoning effortNot availableNot available
Release dateApril 28, 2025April 5, 2025

Features

Supported features

API features available for each model.

Metricqwen logoQwen3 32Bmeta-llama logoLlama 4 Scout
Tool callingSupportedSupported
Structured outputsSupportedSupported
JSON modeSupportedSupported
ReasoningSupportedNot supported
TemperatureSupportedSupported
Stop sequencesSupportedSupported
Deterministic seedSupportedSupported
Verbosity controlNot supportedNot supported

Our take

Qwen3 32B is 1.2x cheaper for a typical chat. Qwen3 32B scores higher on the Artificial Analysis Intelligence Index (8.6 vs 8.1). Llama 4 Scout has the larger context window (1.31M vs 131K 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 Qwen3 32B or Llama 4 Scout cheaper?

Qwen3 32B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3 32B costs $0.08 per 1M input tokens and $0.28 per 1M output tokens, while Llama 4 Scout costs $0.10 per 1M input tokens and $0.30 per 1M output tokens.

Which has a bigger context window, Qwen3 32B or Llama 4 Scout?

Llama 4 Scout supports up to 1.31M tokens of context, compared with 131K for Qwen3 32B.

Is Qwen3 32B smarter than Llama 4 Scout?

On the Artificial Analysis Intelligence Index, Qwen3 32B scores 8.6 and Llama 4 Scout scores 8.1, putting Qwen3 32B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.

Can I use Qwen3 32B and Llama 4 Scout at the same time?

Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3 32B and Llama 4 Scout answer side by side and keep the better response.

qwen logometa-llama logo

Why choose? Ask both.

Send one prompt to Qwen3 32B and Llama 4 Scout at the same time. Compare the answers side by side and keep the best one.