Model Comparison

Gemma 4 31B vs MiniMax M2.7Which is better in 2026?

MiniMax M2.7 significantly outperforms across most benchmarks. Gemma 4 31B is 2.7x cheaper per token.

Verdict: Gemma 4 31B vs MiniMax M2.7 — which is better?

Gemma 4 31B (by Google) and MiniMax M2.7 (by MiniMax) 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 MiniMax M2.7 is better at 1 benchmark (GDPval-AA). MiniMax M2.7 significantly outperforms across most benchmarks.

On price, Gemma 4 31B is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemma 4 31B also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemma 4 31B if…

  • cost matters — it's about 2.7x cheaper per token
  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Apr 2026

Choose MiniMax M2.7 if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemma 4 31B outperforms in 0 benchmarks, while MiniMax M2.7 is better at 1 benchmark (GDPval-AA).

MiniMax M2.7 significantly outperforms across most benchmarks.

Fri Jul 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 4 31B costs less

For input processing, Gemma 4 31B ($0.13/1M tokens) is 2.3x cheaper than MiniMax M2.7 ($0.30/1M tokens).

For output processing, Gemma 4 31B ($0.38/1M tokens) is 3.2x cheaper than MiniMax M2.7 ($1.20/1M tokens).

In conclusion, MiniMax M2.7 is more expensive than Gemma 4 31B.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Jul 17 2026 • llm-stats.com
Google
Gemma 4 31B
Input tokens$0.13
Output tokens$0.38
Best providerDeepinfra
MiniMax
MiniMax M2.7
Input tokens$0.30
Output tokens$1.20
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemma 4 31B accepts 262,144 input tokens compared to MiniMax M2.7's 196,608 tokens. MiniMax M2.7 can generate longer responses up to 196,608 tokens, while Gemma 4 31B is limited to 131,072 tokens.

Google
Gemma 4 31B
Input262,144 tokens
Output131,072 tokens
MiniMax
MiniMax M2.7
Input196,608 tokens
Output196,608 tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 4 31B supports multimodal inputs, whereas MiniMax M2.7 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

Text
Images
Audio
Video

MiniMax M2.7

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 4 31B is licensed under Apache 2.0, while MiniMax M2.7 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Gemma 4 31B

Apache 2.0

Open weights

MiniMax M2.7

MIT

Open weights

Release Timeline

When each model was launched

Gemma 4 31B was released on 2026-04-02, while MiniMax M2.7 was released on 2026-03-18.

Gemma 4 31B is 1 month newer than MiniMax M2.7.

Gemma 4 31B

Apr 2, 2026

3 months ago

2w newer
MiniMax M2.7

Mar 18, 2026

4 months ago

Knowledge Cutoff

When training data ends

Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while MiniMax M2.7'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 MiniMax M2.7's cutoff date.

Gemma 4 31B

Jan 2025

MiniMax M2.7

—

Provider Availability

Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. MiniMax M2.7 is available from Fireworks, MiniMax, Novita.

Gemma 4 31B

deepinfra logo
Deepinfra
Input Price:Input: $0.13/1MOutput Price:Output: $0.38/1M
friendli logo
FriendliAI
Input Price:Input: $0.14/1MOutput Price:Output: $0.40/1M
novita logo
Novita
Input Price:Input: $0.14/1MOutput Price:Output: $0.40/1M
together logo
Together
Input Price:Input: $0.39/1MOutput Price:Output: $0.97/1M

MiniMax M2.7

fireworks logo
Fireworks
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (262,144 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
MiniMax
Higher GDPval-AA score (39.3% vs 26.1%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemma 4 31B and MiniMax M2.7 side-by-side, then vote on the output you prefer.

Gemma 4 31B
✓ Preferred
MiniMax M2.7
Open in Playground
AI Model Comparison Table
Feature
Google
Gemma 4 31B
MiniMax
MiniMax M2.7

FAQ

Common questions about Gemma 4 31B vs MiniMax M2.7.

Which is better, Gemma 4 31B or MiniMax M2.7?

MiniMax M2.7 significantly outperforms across most benchmarks. Gemma 4 31B is made by Google and MiniMax M2.7 is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 4 31B compare to MiniMax M2.7 in benchmarks?

Gemma 4 31B scores AIME 2026: 89.2%, MMMLU: 88.4%, t2-bench: 86.4%, MathVision: 85.6%, MMLU-Pro: 85.2%. MiniMax M2.7 scores SWE-bench Multilingual: 76.5%, MLE-Bench Lite: 66.6%, MM-ClawBench: 62.7%, Terminal-Bench 2.0: 57.0%, SWE-Bench Pro: 56.2%.

Is Gemma 4 31B cheaper than MiniMax M2.7?

Gemma 4 31B is 2.3x cheaper for input tokens. Gemma 4 31B costs $0.13/M input and $0.38/M output via deepinfra. MiniMax M2.7 costs $0.30/M input and $1.20/M output via fireworks.

What are the context window sizes for Gemma 4 31B and MiniMax M2.7?

Gemma 4 31B supports 262K tokens and MiniMax M2.7 supports 197K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 4 31B and MiniMax M2.7?

Key differences include context window (262K vs 197K), input pricing ($0.13 vs $0.30/M), multimodal support (yes vs no), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 4 31B and MiniMax M2.7?

Gemma 4 31B is developed by Google and MiniMax M2.7 is developed by MiniMax.

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