Side-by-side comparison
Devstral 2 2512 vs Qwen3 235B A22B
Mistral
Devstral 2 2512
🔧 Tools
{} JSON
Input / 1M
$0.4000
Output / 1M
$2.0000
| Devstral 2 2512 | Qwen3 235B A22B | |
|---|---|---|
| Provider | Mistral | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 262,144 | 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 → | 0.4000 | 0.4550 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 2.0000 | 1.8200 |
Frequently asked questions
Which is cheaper, Devstral 2 2512 or Qwen3 235B A22B?
Qwen3 235B A22B is cheaper than Devstral 2 2512 on a 50/50 input/output blend by about $0.0625 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, Devstral 2 2512 or Qwen3 235B A22B?
Devstral 2 2512 has the larger context window at 262k tokens versus 131k tokens for Qwen3 235B A22B. That means Devstral 2 2512 can ingest about 2.0x as much text per request.
What is the difference between Devstral 2 2512 and Qwen3 235B A22B?
Devstral 2 2512 comes from Mistral; Qwen3 235B A22B 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.