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Side-by-side comparison

Llama 3.2 11B Vision Instruct vs Qwen2.5 VL 72B Instruct

Meta

Llama 3.2 11B Vision Instruct

πŸ‘ Vision {} JSON
Input / 1M
$0.2450
Output / 1M
$0.2450
View Llama 3.2 11B Vision Instruct β†’
Qwen

Qwen2.5 VL 72B Instruct

πŸ‘ Vision {} JSON
Input / 1M
$0.2500
Output / 1M
$0.7500
View Qwen2.5 VL 72B Instruct β†’
Llama 3.2 11B Vision InstructQwen2.5 VL 72B Instruct
Provider Meta Qwen
Context window Maximum tokens (input + output) the model can process in a single request. Glossary β†’ 131,072 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 β†’ 0.2450 0.2500
Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5Γ— pricier than input. Glossary β†’ 0.2450 0.7500

Frequently asked questions

Which is cheaper, Llama 3.2 11B Vision Instruct or Qwen2.5 VL 72B Instruct?

Llama 3.2 11B Vision Instruct is cheaper than Qwen2.5 VL 72B Instruct on a 50/50 input/output blend by about $0.255 per 1M tokens. Exact savings depend on your input-vs-output ratio β€” use the cost calculator on this page for a workload-specific estimate.

Which has a larger context window, Llama 3.2 11B Vision Instruct or Qwen2.5 VL 72B Instruct?

Llama 3.2 11B Vision Instruct has the larger context window at 131k tokens versus 32k tokens for Qwen2.5 VL 72B Instruct. That means Llama 3.2 11B Vision Instruct can ingest about 4.1x as much text per request.

What is the difference between Llama 3.2 11B Vision Instruct and Qwen2.5 VL 72B Instruct?

Llama 3.2 11B Vision Instruct comes from Meta; Qwen2.5 VL 72B Instruct comes from Qwen. They differ in pricing, context window, and supported capabilities β€” see the side-by-side table on this page for the exact figures, refreshed nightly.

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