Side-by-side comparison
Llama Guard 4 12B vs Qwen2.5 VL 72B Instruct
Meta
Llama Guard 4 12B
👁 Vision
{} JSON
Input / 1M
$0.1800
Output / 1M
$0.1800
Qwen
Qwen2.5 VL 72B Instruct
👁 Vision
{} JSON
Input / 1M
$0.2500
Output / 1M
$0.7500
| Llama Guard 4 12B | Qwen2.5 VL 72B Instruct | |
|---|---|---|
| Provider | Meta | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 163,840 | 32,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, json_mode | vision, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.1800 | 0.2500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1800 | 0.7500 |
Frequently asked questions
Which is cheaper, Llama Guard 4 12B or Qwen2.5 VL 72B Instruct?
Llama Guard 4 12B is cheaper than Qwen2.5 VL 72B Instruct on a 50/50 input/output blend by about $0.32 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 Guard 4 12B or Qwen2.5 VL 72B Instruct?
Llama Guard 4 12B has the larger context window at 164k tokens versus 32k tokens for Qwen2.5 VL 72B Instruct. That means Llama Guard 4 12B can ingest about 5.1x as much text per request.
What is the difference between Llama Guard 4 12B and Qwen2.5 VL 72B Instruct?
Llama Guard 4 12B comes from Meta; Qwen2.5 VL 72B Instruct comes from Qwen. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.