Gemini 3.1 Pro vs Llama 3.3 70B
Google's frontier model with a large leap in core reasoning.
Meta's efficient 70B model matching Llama 3.1 405B on key benchmarks.
No captured outputs for these models yet.
Frequently Asked Questions: Gemini 3.1 Pro vs Llama 3.3 70B▼
Which is better, Gemini 3.1 Pro or Llama 3.3 70B?
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Based on the Capability Index, Gemini 3.1 Pro scores higher (86.4 vs 61.4). 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 Llama 3.3 70B?
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Llama 3.3 70B has a lower blended cost. Gemini 3.1 Pro: $2.00 input / $12.00 output. Llama 3.3 70B: $0.10 input / $0.32 output.
Which has a larger context window, Gemini 3.1 Pro or Llama 3.3 70B?
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Gemini 3.1 Pro has a larger context window: Gemini 3.1 Pro supports 1M tokens vs Llama 3.3 70B at 131K tokens.
Do both Gemini 3.1 Pro and Llama 3.3 70B support vision?
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Gemini 3.1 Pro supports vision/image input, but Llama 3.3 70B does not.
What are the key differences between Gemini 3.1 Pro and Llama 3.3 70B?
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Key differences: Gemini 3.1 Pro has a notably higher capability index (25.0 point gap); Llama 3.3 70B 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 Llama 3.3 70B for free on idapt.app to see which performs better for your specific needs.