Side-by-side comparison
Qwen2.5 VL 72B Instruct vs Mistral Small 3.1 24B
Qwen
Qwen2.5 VL 72B Instruct
👁 Vision
{} JSON
Input / 1M
$0.2500
Output / 1M
$0.7500
Mistral
Mistral Small 3.1 24B
👁 Vision
Input / 1M
$0.3500
Output / 1M
$0.5600
| Qwen2.5 VL 72B Instruct | Mistral Small 3.1 24B | |
|---|---|---|
| Provider | Qwen | Mistral |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 32,000 | 128,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, json_mode | vision |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.2500 | 0.3500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.7500 | 0.5600 |
Frequently asked questions
Which is cheaper, Qwen2.5 VL 72B Instruct or Mistral Small 3.1 24B?
Mistral Small 3.1 24B is cheaper than Qwen2.5 VL 72B Instruct on a 50/50 input/output blend by about $0.045 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, Qwen2.5 VL 72B Instruct or Mistral Small 3.1 24B?
Mistral Small 3.1 24B has the larger context window at 128k tokens versus 32k tokens for Qwen2.5 VL 72B Instruct. That means Mistral Small 3.1 24B can ingest about 4.0x as much text per request.
What is the difference between Qwen2.5 VL 72B Instruct and Mistral Small 3.1 24B?
Qwen2.5 VL 72B Instruct comes from Qwen; Mistral Small 3.1 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.