Gemini 3.1 Pro vs Kimi K2
Google's frontier model with a large leap in core reasoning.
MoonshotAI's large MoE model — 1T total parameters, 32B active.
No captured outputs for these models yet.
Frequently Asked Questions: Gemini 3.1 Pro vs Kimi K2▼
Which is better, Gemini 3.1 Pro or Kimi K2?
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Based on the Capability Index, Gemini 3.1 Pro scores higher (86.4 vs 78.2). 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 Kimi K2?
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Kimi K2 has a lower blended cost. Gemini 3.1 Pro: $2.00 input / $12.00 output. Kimi K2: $0.57 input / $2.30 output.
Which has a larger context window, Gemini 3.1 Pro or Kimi K2?
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Gemini 3.1 Pro has a larger context window: Gemini 3.1 Pro supports 1M tokens vs Kimi K2 at 131K tokens.
Do both Gemini 3.1 Pro and Kimi K2 support vision?
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Gemini 3.1 Pro supports vision/image input, but Kimi K2 does not.
What are the key differences between Gemini 3.1 Pro and Kimi K2?
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Key differences: Gemini 3.1 Pro has a notably higher capability index (8.2 point gap); Kimi K2 is significantly cheaper; only Gemini 3.1 Pro supports vision input; 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 Kimi K2 for free on idapt.app to see which performs better for your specific needs.