Side-by-side comparison
Qwen-Max vs Mistral Large 2407
Mistral
Mistral Large 2407
🔧 Tools
{} JSON
Input / 1M
$2.0000
Output / 1M
$6.0000
| Qwen-Max | Mistral Large 2407 | |
|---|---|---|
| Provider | Qwen | Mistral |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 32,768 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 1.0400 | 2.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 4.1600 | 6.0000 |
Frequently asked questions
Which is cheaper, Qwen-Max or Mistral Large 2407?
Qwen-Max is cheaper than Mistral Large 2407 on a 50/50 input/output blend by about $1.4 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, Qwen-Max or Mistral Large 2407?
Mistral Large 2407 has the larger context window at 131k tokens versus 33k tokens for Qwen-Max . That means Mistral Large 2407 can ingest about 4.0x as much text per request.
What is the difference between Qwen-Max and Mistral Large 2407?
Qwen-Max comes from Qwen; Mistral Large 2407 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.