Model comparison
Gemini 3.1 Pro vs Gemini 2.5 Pro
The primary observable difference is that Gemini 3.1 Pro has a higher cost per million tokens for both input and output compared to Gemini 2.5 Pro, despite similar context and modality support.
Gemini 3.1 Pro
Google's latest frontier model with expanded reasoning.
Gemini 2.5 Pro
Google's bet on massive context and native multimodality.
Specs
| Metric | Gemini 3.1 Pro | Gemini 2.5 Pro |
|---|---|---|
| Context window | 1.0M tokens↑ | 1.0M tokens |
| Input $/1M tokens | $2.00 | $1.25↑ |
| Output $/1M tokens | $12.00 | $10.00↑ |
| Modalities | Audio · File · Image · Text · Video | Text · Image · File · Audio · Video |
| Open weights | No | No |
How they differ
Cost profile
Gemini 3.1 Pro
Gemini 3.1 Pro is priced at $2.0 per million input tokens and $12.0 per million output tokens.
Gemini 2.5 Pro
Gemini 2.5 Pro is priced at $1.25 per million input tokens and $10.0 per million output tokens.
Context handling
Gemini 3.1 Pro
Gemini 3.1 Pro also supports a context size of 1,048,576 tokens but demonstrates improved consistency and coherence in multi-turn interactions near the context limit.
Gemini 2.5 Pro
Gemini 2.5 Pro supports a context size of 1,048,576 tokens with stable performance throughout.
Vision
Gemini 3.1 Pro
Gemini 3.1 Pro supports the same input modalities, with improvements in OCR implementation and multimodal coherence.
Gemini 2.5 Pro
Gemini 2.5 Pro supports input modalities that include image, text, audio, video, and file.
Gemini 3.1 Pro — what sets it apart
- +Gemini 3.1 Pro provides better long-term coherence in extended multi-turn interactions.
- +Demonstrates improved optimization in coding tasks and enhanced multimodal integration.
Gemini 2.5 Pro — what sets it apart
- +Gemini 2.5 Pro offers lower input and output costs, making it more budget-friendly.
- +Processes inputs and outputs with slightly faster average latency.
The higher operational cost of Gemini 3.1 Pro compared to Gemini 2.5 Pro is the most consequential difference, with potential justifications in improved reasoning and multimodal capabilities.
Analysis synthesized from gpt-4o, llama-4-maverick, phi-4, etc.