Model Comparison

Gemma 3n E2B vs MiniMax M1 80K

Comparing Gemma 3n E2B and MiniMax M1 80K across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 3n E2B and MiniMax M1 80K don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

448.0B diff

MiniMax M1 80K has 448.0B more parameters than Gemma 3n E2B, making it 5600.0% larger.

Google
Gemma 3n E2B
8.0Bparameters
MiniMax
MiniMax M1 80K
456.0Bparameters
8.0B
Gemma 3n E2B
456.0B
MiniMax M1 80K

Context Window

Maximum input and output token capacity

Only MiniMax M1 80K specifies input context (1,000,000 tokens). Only MiniMax M1 80K specifies output context (40,000 tokens).

Google
Gemma 3n E2B
Input- tokens
Output- tokens
MiniMax
MiniMax M1 80K
Input1,000,000 tokens
Output40,000 tokens
Sun May 10 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B supports multimodal inputs, whereas MiniMax M1 80K does not.

Gemma 3n E2B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3n E2B

Text
Images
Audio
Video

MiniMax M1 80K

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E2B is licensed under a proprietary license, while MiniMax M1 80K uses MIT.

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

Gemma 3n E2B

Proprietary

Closed source

MiniMax M1 80K

MIT

Open weights

Release Timeline

When each model was launched

Gemma 3n E2B was released on 2025-06-26, while MiniMax M1 80K was released on 2025-06-16.

Gemma 3n E2B is 0 month newer than MiniMax M1 80K.

Gemma 3n E2B

Jun 26, 2025

10 months ago

1w newer
MiniMax M1 80K

Jun 16, 2025

10 months ago

Knowledge Cutoff

When training data ends

Gemma 3n E2B has a documented knowledge cutoff of 2024-06-01, while MiniMax M1 80K's cutoff date is not specified.

We can confirm Gemma 3n E2B's training data extends to 2024-06-01, but cannot make a direct comparison without MiniMax M1 80K's cutoff date.

Gemma 3n E2B

Jun 2024

MiniMax M1 80K

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Outputs Comparison

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Key Takeaways

Google
Supports multimodal inputs
MiniMax
Larger context window (1,000,000 tokens)
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E2B
MiniMax
MiniMax M1 80K

FAQ

Common questions about Gemma 3n E2B vs MiniMax M1 80K.

Which is better, Gemma 3n E2B or MiniMax M1 80K?

Gemma 3n E2B (Google) and MiniMax M1 80K (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 Gemma 3n E2B compare to MiniMax M1 80K in benchmarks?

Gemma 3n E2B scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%. MiniMax M1 80K scores MATH-500: 96.8%, ZebraLogic: 86.8%, AIME 2024: 86.0%, MMLU-Pro: 81.1%, AIME 2025: 76.9%.

What are the context window sizes for Gemma 3n E2B and MiniMax M1 80K?

Gemma 3n E2B supports an unknown number of tokens and MiniMax M1 80K supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 3n E2B and MiniMax M1 80K?

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

Who makes Gemma 3n E2B and MiniMax M1 80K?

Gemma 3n E2B is developed by Google and MiniMax M1 80K is developed by MiniMax.