Side-by-side comparison
Mixtral 8x22B Instruct vs Qwen-Max
Mistral
Mixtral 8x22B Instruct
🔧 Tools
{} JSON
Input / 1M
$2.0000
Output / 1M
$6.0000
| Mixtral 8x22B Instruct | Qwen-Max | |
|---|---|---|
| Provider | Mistral | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 65,536 | 32,768 |
| 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 → | 2.0000 | 1.0400 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 6.0000 | 4.1600 |
Frequently asked questions
Which is cheaper, Mixtral 8x22B Instruct or Qwen-Max ?
Qwen-Max is cheaper than Mixtral 8x22B Instruct 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, Mixtral 8x22B Instruct or Qwen-Max ?
Mixtral 8x22B Instruct has the larger context window at 66k tokens versus 33k tokens for Qwen-Max . That means Mixtral 8x22B Instruct can ingest about 2.0x as much text per request.
What is the difference between Mixtral 8x22B Instruct and Qwen-Max ?
Mixtral 8x22B Instruct comes from Mistral; Qwen-Max 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.