Side-by-side comparison
Mistral 7B Instruct v0.1 vs Llama 3.2 3B Instruct
Mistral
Mistral 7B Instruct v0.1
Input / 1M
$0.1100
Output / 1M
$0.1900
| Mistral 7B Instruct v0.1 | Llama 3.2 3B Instruct | |
|---|---|---|
| Provider | Mistral | Meta |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 2,824 | 80,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | text-only | text-only |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.1100 | 0.0510 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1900 | 0.3400 |
Frequently asked questions
Which is cheaper, Mistral 7B Instruct v0.1 or Llama 3.2 3B Instruct?
Mistral 7B Instruct v0.1 is cheaper than Llama 3.2 3B Instruct on a 50/50 input/output blend by about $0.0455 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, Mistral 7B Instruct v0.1 or Llama 3.2 3B Instruct?
Llama 3.2 3B Instruct has the larger context window at 80k tokens versus 3k tokens for Mistral 7B Instruct v0.1. That means Llama 3.2 3B Instruct can ingest about 28.3x as much text per request.
What is the difference between Mistral 7B Instruct v0.1 and Llama 3.2 3B Instruct?
Mistral 7B Instruct v0.1 comes from Mistral; Llama 3.2 3B Instruct comes from Meta. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.