Model Comparison

Gemini 3.1 Pro vs MiniMax M2.7

MiniMax M2.7 shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini 3.1 Pro outperforms in 1 benchmarks (Terminal-Bench 2.0), while MiniMax M2.7 is better at 2 benchmarks (GDPval-AA, SWE-Bench Pro).

MiniMax M2.7 shows notably better performance in the majority of benchmarks.

Thu Apr 02 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 02 2026 • llm-stats.com
Google
Gemini 3.1 Pro
Input tokens$2.50
Output tokens$15.00
Best providerGoogle
MiniMax
MiniMax M2.7
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Context Window

Maximum input and output token capacity

Only Gemini 3.1 Pro specifies input context (1,048,576 tokens). Only Gemini 3.1 Pro specifies output context (65,536 tokens).

Google
Gemini 3.1 Pro
Input1,048,576 tokens
Output65,536 tokens
MiniMax
MiniMax M2.7
Input- tokens
Output- tokens
Thu Apr 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 3.1 Pro supports multimodal inputs, whereas MiniMax M2.7 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

Text
Images
Audio
Video

MiniMax M2.7

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.1 Pro is licensed under a proprietary license, while MiniMax M2.7 uses MIT.

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

Gemini 3.1 Pro

Proprietary

Closed source

MiniMax M2.7

MIT

Open weights

Release Timeline

When each model was launched

Gemini 3.1 Pro was released on 2026-02-19, while MiniMax M2.7 was released on 2026-03-18.

MiniMax M2.7 is 1 month newer than Gemini 3.1 Pro.

Gemini 3.1 Pro

Feb 19, 2026

1 months ago

MiniMax M2.7

Mar 18, 2026

2 weeks ago

3w newer

Knowledge Cutoff

When training data ends

Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while MiniMax M2.7'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 MiniMax M2.7's cutoff date.

Gemini 3.1 Pro

Jan 2025

MiniMax M2.7

—

Outputs Comparison

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Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Higher Terminal-Bench 2.0 score (68.5% vs 57.0%)
MiniMax
Has open weights
Higher GDPval-AA score (50.0% vs 43.9%)
Higher SWE-Bench Pro score (56.2% vs 54.2%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 3.1 Pro
MiniMax
MiniMax M2.7

FAQ

Common questions about Gemini 3.1 Pro vs MiniMax M2.7

MiniMax M2.7 shows notably better performance in the majority of benchmarks. Gemini 3.1 Pro 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.
Gemini 3.1 Pro scores t2-bench: 99.3%, LiveCodeBench Pro: 96.2%, GPQA: 94.3%, MMMLU: 92.6%, BrowseComp: 85.9%. 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%.
Gemini 3.1 Pro supports 1.0M tokens and MiniMax M2.7 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemini 3.1 Pro is developed by Google and MiniMax M2.7 is developed by MiniMax.