Side-by-side comparison
Llama 4 Scout vs Mistral Small 3.2 24B
Meta
Llama 4 Scout
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.0800
Output / 1M
$0.3000
Mistral
Mistral Small 3.2 24B
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.0750
Output / 1M
$0.2000
| Llama 4 Scout | Mistral Small 3.2 24B | |
|---|---|---|
| Provider | Meta | Mistral |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 327,680 | 128,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.0800 | 0.0750 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.3000 | 0.2000 |
Frequently asked questions
Which is cheaper, Llama 4 Scout or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is cheaper than Llama 4 Scout on a 50/50 input/output blend by about $0.0525 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Llama 4 Scout or Mistral Small 3.2 24B?
Llama 4 Scout has the larger context window at 328k tokens versus 128k tokens for Mistral Small 3.2 24B. That means Llama 4 Scout can ingest about 2.6x as much text per request.
What is the difference between Llama 4 Scout and Mistral Small 3.2 24B?
Llama 4 Scout comes from Meta; Mistral Small 3.2 24B comes from Mistral. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.