Model Comparison
Gemma 4 31B vs MiMo-V2.5-ProWhich is better in 2026?
Gemma 4 31B has a slight edge in benchmark performance. Gemma 4 31B is 2.8x cheaper per token.
Verdict: Gemma 4 31B vs MiMo-V2.5-Pro — which is better?
Gemma 4 31B (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.
Gemma 4 31B outperforms in 3 benchmarks (GPQA, LiveCodeBench v6, MMLU-Pro), while MiMo-V2.5-Pro is better at 2 benchmarks (GDPval-AA, Humanity's Last Exam). Gemma 4 31B has a slight edge in benchmark performance.
On price, Gemma 4 31B is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5-Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemma 4 31B if…
- you want the strongest raw capability — it leads on 3 of 5 shared benchmarks
- cost matters — it's about 2.8x cheaper per token
Choose MiMo-V2.5-Pro if…
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
Performance Benchmarks
Comparative analysis across standard metrics
Gemma 4 31B outperforms in 3 benchmarks (GPQA, LiveCodeBench v6, MMLU-Pro), while MiMo-V2.5-Pro is better at 2 benchmarks (GDPval-AA, Humanity's Last Exam).
Gemma 4 31B has a slight edge in benchmark performance.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 4 31B ($0.13/1M tokens) is 3.3x cheaper than MiMo-V2.5-Pro ($0.43/1M tokens).
For output processing, Gemma 4 31B ($0.38/1M tokens) is 2.3x cheaper than MiMo-V2.5-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.5-Pro is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.5-Pro has 992.5B more parameters than Gemma 4 31B, making it 3233.0% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.5-Pro accepts 1,048,576 input tokens compared to Gemma 4 31B's 262,144 tokens. Both models can generate responses up to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Gemma 4 31B supports multimodal inputs, whereas MiMo-V2.5-Pro does not.
Gemma 4 31B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemma 4 31B
MiMo-V2.5-Pro
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while MiMo-V2.5-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Gemma 4 31B was released on 2026-04-02, while MiMo-V2.5-Pro was released on 2026-04-27.
MiMo-V2.5-Pro is 1 month newer than Gemma 4 31B.
Apr 2, 2026
3 months ago
Apr 27, 2026
2 months ago
3w newerKnowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while MiMo-V2.5-Pro's cutoff date is not specified.
We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without MiMo-V2.5-Pro's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita.
Gemma 4 31B
MiMo-V2.5-Pro
Outputs Comparison
Key Takeaways
Gemma 4 31B
View detailsDetailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Gemma 4 31B and MiMo-V2.5-Pro side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Gemma 4 31B vs MiMo-V2.5-Pro.