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.
Qwen
Qwen3 32B
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
Meta
Llama 4 Scout
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
Qwen3 32B
1.2x cheaper for a typical chat
Higher intelligence score
Qwen3 32B
8.6 vs 8.1 on Artificial Analysis
Larger context window
Llama 4 Scout
1.31M vs 131K tokens
Newer release
Qwen3 32B
Released April 28, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
Qwen3 32B vs Llama 4 Scout API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.08 | $0.10 |
| Output tokensPer 1M tokens | $0.28 | $0.30 |
| Cached input (read)Per 1M tokens | Not available | Not available |
| Cache writePer 1M tokens | Not available | Not 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
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 131K tokens | 1.31M tokens |
| Max output | 16K tokens | 16K tokens |
| Input types | Text | Image, Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | April 28, 2025 | April 5, 2025 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not 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.
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.