AI model comparison
Llama 4 Scout vs Llama 3.2 1B Instruct
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
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
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis.
- Input / 1M
- $0.03
- Output / 1M
- $0.20
- Context
- 60K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Llama 3.2 1B Instruct
2.3x cheaper for a typical chat
Higher intelligence score
Llama 4 Scout
8.1 vs 4.8 on Artificial Analysis
Larger context window
Llama 4 Scout
1.31M vs 60K tokens
Newer release
Llama 4 Scout
Released April 5, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
Llama 4 Scout vs Llama 3.2 1B Instruct API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.10 | $0.03 |
| Output tokensPer 1M tokens | $0.30 | $0.20 |
| 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 | 1.31M tokens | 60K tokens |
| Max output | 16K tokens | 54K tokens |
| Input types | Image, Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | April 5, 2025 | September 25, 2024 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Not supported |
| Structured outputs | Supported | Not supported |
| JSON mode | Supported | Not supported |
| Reasoning | Not supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
- Llama 4 Scout vs Gemini 2.5 Flash Lite
- Llama 4 Scout vs Llama 3.1 8B Instruct
- Llama 4 Scout vs Qwen3 30B A3B Instruct 2507
- Llama 4 Scout vs Llama 3.3 70B Instruct
- Llama 4 Scout vs GPT-4.1 Nano
- Llama 4 Scout vs Llama 4 Maverick
- Llama 4 Scout vs Qwen3 32B
- Llama 4 Scout vs Nemotron 3 Nano 30B A3B
- Llama 4 Scout vs Qwen3 14B
- Llama 4 Scout vs Qwen2.5 72B Instruct
- Llama 4 Scout vs Nova Lite 1.0
- Llama 4 Scout vs Llama 3.1 70B Instruct
- Llama 4 Scout vs Llama 3.2 3B Instruct
- Llama 3.2 1B Instruct vs Llama 3.3 70B Instruct
- Llama 3.2 1B Instruct vs Llama 3.1 8B Instruct
- Llama 3.2 1B Instruct vs Llama 3.1 70B Instruct
- Llama 3.2 1B Instruct vs Reka Flash 3
- Llama 3.2 1B Instruct vs Ministral 3 14B 2512
- Llama 3.2 1B Instruct vs Nova Micro 1.0
- Llama 3.2 1B Instruct vs Llama 3.2 3B Instruct
- Llama 3.2 1B Instruct vs Ministral 3 8B 2512
- Llama 3.2 1B Instruct vs Gemma 3 27B
- Llama 3.2 1B Instruct vs Granite 4.0 Micro
- Llama 3.2 1B Instruct vs Ministral 3 3B 2512
- Llama 3.2 1B Instruct vs Gemma 3 4B
- Llama 3.2 1B Instruct vs Gemma 3 12B
Our take
Llama 3.2 1B Instruct is 2.3x cheaper for a typical chat. Llama 4 Scout scores higher on the Artificial Analysis Intelligence Index (8.1 vs 4.8). Llama 4 Scout has the larger context window (1.31M vs 60K 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 Llama 3.2 1B Instruct cheaper?
Llama 3.2 1B Instruct is cheaper for a typical chat (2K input tokens and 500 output tokens). Llama 3.2 1B Instruct costs $0.03 per 1M input tokens and $0.20 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, Llama 4 Scout or Llama 3.2 1B Instruct?
Llama 4 Scout supports up to 1.31M tokens of context, compared with 60K for Llama 3.2 1B Instruct.
Is Llama 4 Scout smarter than Llama 3.2 1B Instruct?
On the Artificial Analysis Intelligence Index, Llama 4 Scout scores 8.1 and Llama 3.2 1B Instruct scores 4.8, 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 Llama 3.2 1B Instruct at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Llama 4 Scout and Llama 3.2 1B Instruct answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Llama 4 Scout and Llama 3.2 1B Instruct at the same time. Compare the answers side by side and keep the best one.