Model Comparison
Gemma 4 31B vs MiMo-V2.5Which is better in 2026?
MiMo-V2.5 significantly outperforms across most benchmarks. Gemma 4 31B is 1.1x cheaper per token.
Verdict: Gemma 4 31B vs MiMo-V2.5 — which is better?
Gemma 4 31B (by Google) and MiMo-V2.5 (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 0 benchmarks, while MiMo-V2.5 is better at 1 benchmark (MMMU-Pro). MiMo-V2.5 significantly outperforms across most benchmarks.
On price, Gemma 4 31B is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5 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…
- cost matters — it's about 1.1x cheaper per token
Choose MiMo-V2.5 if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- 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 0 benchmarks, while MiMo-V2.5 is better at 1 benchmark (MMMU-Pro).
MiMo-V2.5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 4 31B ($0.13/1M tokens) is 1.3x cheaper than MiMo-V2.5 ($0.17/1M tokens).
For output processing, Gemma 4 31B ($0.38/1M tokens) is 1.1x more expensive than MiMo-V2.5 ($0.34/1M tokens).
In conclusion, MiMo-V2.5 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 has 280.1B more parameters than Gemma 4 31B, making it 912.3% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.5 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
Both Gemma 4 31B and MiMo-V2.5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 4 31B
MiMo-V2.5
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while MiMo-V2.5 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 was released on 2026-04-22.
MiMo-V2.5 is 1 month newer than Gemma 4 31B.
Apr 2, 2026
3 months ago
Apr 22, 2026
2 months ago
2w newerKnowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while MiMo-V2.5'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's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. MiMo-V2.5 is available from Novita, DeepInfra.
Gemma 4 31B
MiMo-V2.5
Outputs Comparison
Key Takeaways
Gemma 4 31B
View detailsMiMo-V2.5
View detailsXiaomi
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Gemma 4 31B and MiMo-V2.5 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.