Model Comparison
Gemma 4 31B vs Kimi K2.6Which is better in 2026?
Kimi K2.6 significantly outperforms across most benchmarks. Gemma 4 31B is 7.5x cheaper per token.
Verdict: Gemma 4 31B vs Kimi K2.6 — which is better?
Gemma 4 31B (by Google) and Kimi K2.6 (by Moonshot AI) 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 Kimi K2.6 is better at 7 benchmarks (AIME 2026, GDPval-AA, GPQA, Humanity's Last Exam, LiveCodeBench v6, MathVision, MMMU-Pro). Kimi K2.6 significantly outperforms across most benchmarks.
On price, Gemma 4 31B is roughly 7.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Gemma 4 31B if…
- cost matters — it's about 7.5x cheaper per token
Choose Kimi K2.6 if…
- you want the strongest raw capability — it leads on 7 of 7 shared benchmarks
- 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 Kimi K2.6 is better at 7 benchmarks (AIME 2026, GDPval-AA, GPQA, Humanity's Last Exam, LiveCodeBench v6, MathVision, MMMU-Pro).
Kimi K2.6 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 5.8x cheaper than Kimi K2.6 ($0.75/1M tokens).
For output processing, Gemma 4 31B ($0.38/1M tokens) is 9.2x cheaper than Kimi K2.6 ($3.50/1M tokens).
In conclusion, Kimi K2.6 is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.6 has 969.3B more parameters than Gemma 4 31B, making it 3157.3% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 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 Kimi K2.6 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 4 31B
Kimi K2.6
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while Kimi K2.6 uses Modified MIT License.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Modified MIT License
Open weights
Release Timeline
When each model was launched
Gemma 4 31B was released on 2026-04-02, while Kimi K2.6 was released on 2026-04-20.
Kimi K2.6 is 1 month newer than Gemma 4 31B.
Apr 2, 2026
3 months ago
Apr 20, 2026
2 months ago
2w newerKnowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Kimi K2.6'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 Kimi K2.6's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. Kimi K2.6 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
Gemma 4 31B
Kimi K2.6
Outputs Comparison
Key Takeaways
Gemma 4 31B
View detailsKimi K2.6
View detailsMoonshot AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Gemma 4 31B and Kimi K2.6 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Gemma 4 31B vs Kimi K2.6.