Gemini 3.1 Pro vs Qwen2.5 VL 72B
Google's frontier model with a large leap in core reasoning.
Large 72B vision-language model from Qwen 2.5 generation.
No captured outputs for these models yet.
Frequently Asked Questions: Gemini 3.1 Pro vs Qwen2.5 VL 72B▼
Which is better, Gemini 3.1 Pro or Qwen2.5 VL 72B?
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Based on the Capability Index, Gemini 3.1 Pro scores higher (86.4 vs 62.8). However, "better" depends on your use case — pricing, speed, context window, and specific capability needs all matter.
Which is cheaper, Gemini 3.1 Pro or Qwen2.5 VL 72B?
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Qwen2.5 VL 72B has a lower blended cost. Gemini 3.1 Pro: $2.00 input / $12.00 output. Qwen2.5 VL 72B: $0.80 input / $1.00 output.
Which has a larger context window, Gemini 3.1 Pro or Qwen2.5 VL 72B?
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Gemini 3.1 Pro has a larger context window: Gemini 3.1 Pro supports 1M tokens vs Qwen2.5 VL 72B at 128K tokens.
Do both Gemini 3.1 Pro and Qwen2.5 VL 72B support vision?
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Yes, both Gemini 3.1 Pro and Qwen2.5 VL 72B support vision/image input.
What are the key differences between Gemini 3.1 Pro and Qwen2.5 VL 72B?
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Key differences: Gemini 3.1 Pro has a notably higher capability index (23.6 point gap); Qwen2.5 VL 72B is significantly cheaper; only Gemini 3.1 Pro offers extended reasoning mode. Compare full specs on this page.
Which model should I choose for my use case?
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If cost is your priority, choose the cheaper option. If you need the highest intelligence for complex tasks, pick the higher-scoring model. For long documents or codebases, choose the larger context window. You can try both Gemini 3.1 Pro and Qwen2.5 VL 72B for free on idapt.app to see which performs better for your specific needs.