Model Comparison

DiffusionGemma 26B-A4B vs MiniMax M2.7Which is better in 2026?

Comparing DiffusionGemma 26B-A4B and MiniMax M2.7 across benchmarks, pricing, and capabilities.

Verdict: DiffusionGemma 26B-A4B vs MiniMax M2.7 — which is better?

DiffusionGemma 26B-A4B (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.

Choose DiffusionGemma 26B-A4B if…

  • you want the most recent training data — it shipped Jun 2026

Choose MiniMax M2.7 if…

  • you want predictable pricing at $0.30/M input and $1.20/M output

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DiffusionGemma 26B-A4B and MiniMax M2.7don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only MiniMax M2.7 specifies input context (196,608 tokens). Only MiniMax M2.7 specifies output context (196,608 tokens).

Google
DiffusionGemma 26B-A4B
Input- tokens
Output- 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

DiffusionGemma 26B-A4B supports multimodal inputs, whereas MiniMax M2.7 does not.

DiffusionGemma 26B-A4B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DiffusionGemma 26B-A4B

Text
Images
Audio
Video

MiniMax M2.7

Text
Images
Audio
Video

License

Usage and distribution terms

DiffusionGemma 26B-A4B 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.

DiffusionGemma 26B-A4B

Apache 2.0

Open weights

MiniMax M2.7

MIT

Open weights

Release Timeline

When each model was launched

DiffusionGemma 26B-A4B was released on 2026-06-10, while MiniMax M2.7 was released on 2026-03-18.

DiffusionGemma 26B-A4B is 3 months newer than MiniMax M2.7.

DiffusionGemma 26B-A4B

Jun 10, 2026

1 months ago

2mo newer
MiniMax M2.7

Mar 18, 2026

4 months ago

Knowledge Cutoff

When training data ends

DiffusionGemma 26B-A4B has a documented knowledge cutoff of 2025-01-01, while MiniMax M2.7's cutoff date is not specified.

We can confirm DiffusionGemma 26B-A4B's training data extends to 2025-01-01, but cannot make a direct comparison without MiniMax M2.7's cutoff date.

DiffusionGemma 26B-A4B

Jan 2025

MiniMax M2.7

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Supports multimodal inputs
MiniMax
Larger context window (196,608 tokens)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DiffusionGemma 26B-A4B and MiniMax M2.7 side-by-side, then vote on the output you prefer.

DiffusionGemma 26B-A4B
✓ Preferred
MiniMax M2.7
Open in Playground
AI Model Comparison Table
Feature
Google
DiffusionGemma 26B-A4B
MiniMax
MiniMax M2.7

FAQ

Common questions about DiffusionGemma 26B-A4B vs MiniMax M2.7.

Which is better, DiffusionGemma 26B-A4B or MiniMax M2.7?

DiffusionGemma 26B-A4B (Google) and MiniMax M2.7 (MiniMax) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DiffusionGemma 26B-A4B compare to MiniMax M2.7 in benchmarks?

DiffusionGemma 26B-A4B scores MMMLU: 81.5%, MMLU-Pro: 77.6%, GPQA: 73.2%, MathVision: 70.5%, AIME 2026: 69.1%. 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%.

What are the context window sizes for DiffusionGemma 26B-A4B and MiniMax M2.7?

DiffusionGemma 26B-A4B supports an unknown number of 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 DiffusionGemma 26B-A4B and MiniMax M2.7?

Key differences include multimodal support (yes vs no), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DiffusionGemma 26B-A4B and MiniMax M2.7?

DiffusionGemma 26B-A4B is developed by Google and MiniMax M2.7 is developed by MiniMax.

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