Model Comparison
Gemini 3.1 Pro vs MiMo-V2.5-ProWhich is better in 2026?
Gemini 3.1 Pro shows notably better performance in the majority of benchmarks. MiMo-V2.5-Pro is 10.3x cheaper per token.
Verdict: Gemini 3.1 Pro vs MiMo-V2.5-Pro — which is better?
Gemini 3.1 Pro (by Google) and MiMo-V2.5-Pro (by Xiaomi) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Gemini 3.1 Pro outperforms in 4 benchmarks (GPQA, Humanity's Last Exam, SWE-Bench Verified, Terminal-Bench 2.0), while MiMo-V2.5-Pro is better at 2 benchmarks (GDPval-AA, SWE-Bench Pro). Gemini 3.1 Pro shows notably better performance in the majority of benchmarks.
On price, MiMo-V2.5-Pro is roughly 10.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Gemini 3.1 Pro if…
- you want the strongest raw capability — it leads on 4 of 6 shared benchmarks
Choose MiMo-V2.5-Pro if…
- cost matters — it's about 10.3x cheaper per token
- you want the most recent training data — it shipped Apr 2026
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3.1 Pro outperforms in 4 benchmarks (GPQA, Humanity's Last Exam, SWE-Bench Verified, Terminal-Bench 2.0), while MiMo-V2.5-Pro is better at 2 benchmarks (GDPval-AA, SWE-Bench Pro).
Gemini 3.1 Pro shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.1 Pro ($2.50/1M tokens) is 5.7x more expensive than MiMo-V2.5-Pro ($0.43/1M tokens).
For output processing, Gemini 3.1 Pro ($15.00/1M tokens) is 17.2x more expensive than MiMo-V2.5-Pro ($0.87/1M tokens).
In conclusion, Gemini 3.1 Pro is more expensive than MiMo-V2.5-Pro.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. MiMo-V2.5-Pro can generate longer responses up to 131,072 tokens, while Gemini 3.1 Pro is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemini 3.1 Pro supports multimodal inputs, whereas MiMo-V2.5-Pro does not.
Gemini 3.1 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 3.1 Pro
MiMo-V2.5-Pro
License
Usage and distribution terms
Gemini 3.1 Pro is licensed under a proprietary license, while MiMo-V2.5-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Gemini 3.1 Pro was released on 2026-02-19, while MiMo-V2.5-Pro was released on 2026-04-27.
MiMo-V2.5-Pro is 2 months newer than Gemini 3.1 Pro.
Feb 19, 2026
3 months ago
Apr 27, 2026
1 months ago
2mo newerKnowledge Cutoff
When training data ends
Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while MiMo-V2.5-Pro's cutoff date is not specified.
We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without MiMo-V2.5-Pro's cutoff date.
Jan 2025
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Provider Availability
Gemini 3.1 Pro is available from Google. MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita.
Gemini 3.1 Pro
MiMo-V2.5-Pro
Outputs Comparison
Key Takeaways
Detailed Comparison
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FAQ
Common questions about Gemini 3.1 Pro vs MiMo-V2.5-Pro.