Mistral Large 3 2512 vs Qwen3 VL 30B A3B Thinking
Mistral Large 3 2512
Qwen3 VL 30B A3B Thinking
| Mistral Large 3 2512 | Qwen3 VL 30B A3B Thinking | |
|---|---|---|
| Provider | Mistral | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary β | 262,144 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary β | 0.5000 | 0.1300 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3β5Γ pricier than input. Glossary β | 1.5000 | 1.5600 |
Frequently asked questions
Which is cheaper, Mistral Large 3 2512 or Qwen3 VL 30B A3B Thinking?
Qwen3 VL 30B A3B Thinking is cheaper than Mistral Large 3 2512 on a 50/50 input/output blend by about $0.155 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, Mistral Large 3 2512 or Qwen3 VL 30B A3B Thinking?
Mistral Large 3 2512 has the larger context window at 262k tokens versus 131k tokens for Qwen3 VL 30B A3B Thinking. That means Mistral Large 3 2512 can ingest about 2.0x as much text per request.
What is the difference between Mistral Large 3 2512 and Qwen3 VL 30B A3B Thinking?
Mistral Large 3 2512 comes from Mistral; Qwen3 VL 30B A3B Thinking 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.