Model Comparison

DiffusionGemma 26B-A4B vs MiniMax M3Which is better in 2026?

MiniMax M3 significantly outperforms across most benchmarks.

Verdict: DiffusionGemma 26B-A4B vs MiniMax M3 — which is better?

DiffusionGemma 26B-A4B (by Google) and MiniMax M3 (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.

DiffusionGemma 26B-A4B outperforms in 0 benchmarks, while MiniMax M3 is better at 2 benchmarks (MMMU-Pro, OmniDocBench 1.5). MiniMax M3 significantly outperforms across most benchmarks.

Choose DiffusionGemma 26B-A4B if…

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

Choose MiniMax M3 if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DiffusionGemma 26B-A4B outperforms in 0 benchmarks, while MiniMax M3 is better at 2 benchmarks (MMMU-Pro, OmniDocBench 1.5).

MiniMax M3 significantly outperforms across most benchmarks.

Fri Jul 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only MiniMax M3 specifies input context (512,000 tokens). Only MiniMax M3 specifies output context (131,072 tokens).

Google
DiffusionGemma 26B-A4B
Input- tokens
Output- tokens
MiniMax
MiniMax M3
Input512,000 tokens
Output131,072 tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DiffusionGemma 26B-A4B and MiniMax M3 support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DiffusionGemma 26B-A4B

Text
Images
Audio
Video

MiniMax M3

Text
Images
Audio
Video

License

Usage and distribution terms

DiffusionGemma 26B-A4B is licensed under Apache 2.0, while MiniMax M3 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 M3

MIT

Open weights

Release Timeline

When each model was launched

DiffusionGemma 26B-A4B was released on 2026-06-10, while MiniMax M3 was released on 2026-06-01.

DiffusionGemma 26B-A4B is 0 month newer than MiniMax M3.

DiffusionGemma 26B-A4B

Jun 10, 2026

1 months ago

1w newer
MiniMax M3

Jun 1, 2026

1 months ago

Knowledge Cutoff

When training data ends

DiffusionGemma 26B-A4B has a documented knowledge cutoff of 2025-01-01, while MiniMax M3'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 M3's cutoff date.

DiffusionGemma 26B-A4B

Jan 2025

MiniMax M3

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

No standout differentiators in the data we have for this pair.

Larger context window (512,000 tokens)
Higher MMMU-Pro score (78.1% vs 54.3%)
Higher OmniDocBench 1.5 score (91.6% vs 31.9%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DiffusionGemma 26B-A4B and MiniMax M3 side-by-side, then vote on the output you prefer.

DiffusionGemma 26B-A4B
✓ Preferred
MiniMax M3
Open in Playground
AI Model Comparison Table
Feature
Google
DiffusionGemma 26B-A4B
MiniMax
MiniMax M3

FAQ

Common questions about DiffusionGemma 26B-A4B vs MiniMax M3.

Which is better, DiffusionGemma 26B-A4B or MiniMax M3?

MiniMax M3 significantly outperforms across most benchmarks. DiffusionGemma 26B-A4B is made by Google and MiniMax M3 is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DiffusionGemma 26B-A4B compare to MiniMax M3 in benchmarks?

DiffusionGemma 26B-A4B scores MMMLU: 81.5%, MMLU-Pro: 77.6%, GPQA: 73.2%, MathVision: 70.5%, AIME 2026: 69.1%. MiniMax M3 scores OmniDocBench 1.5: 91.6%, SpreadSheetBench-v1: 89.3%, USAMO 2026: 85.7%, Video-MME: 85.4%, VideoMMMU: 84.6%.

What are the context window sizes for DiffusionGemma 26B-A4B and MiniMax M3?

DiffusionGemma 26B-A4B supports an unknown number of tokens and MiniMax M3 supports 512K 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 M3?

Key differences include licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DiffusionGemma 26B-A4B and MiniMax M3?

DiffusionGemma 26B-A4B is developed by Google and MiniMax M3 is developed by MiniMax.