Side-by-side comparison
Llama 3.2 1B Instruct vs WizardLM-2 8x22B
| Llama 3.2 1B Instruct | WizardLM-2 8x22B | |
|---|---|---|
| Provider | Meta | Microsoft |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 60,000 | 65,535 |
| 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 → | 0.0270 | 0.6200 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.2000 | 0.6200 |
Frequently asked questions
Which is cheaper, Llama 3.2 1B Instruct or WizardLM-2 8x22B?
Llama 3.2 1B Instruct is cheaper than WizardLM-2 8x22B on a 50/50 input/output blend by about $0.5065 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 3.2 1B Instruct or WizardLM-2 8x22B?
WizardLM-2 8x22B has the larger context window at 66k tokens versus 60k tokens for Llama 3.2 1B Instruct. That means WizardLM-2 8x22B can ingest about 1.1x as much text per request.
What is the difference between Llama 3.2 1B Instruct and WizardLM-2 8x22B?
Llama 3.2 1B Instruct comes from Meta; WizardLM-2 8x22B comes from Microsoft. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.