Model Comparison

Gemma 3n E4B Instructed vs Ministral 3 (3B Instruct 2512)

Comparing Gemma 3n E4B Instructed and Ministral 3 (3B Instruct 2512) across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 3n E4B Instructed and Ministral 3 (3B Instruct 2512) don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Google
Gemma 3n E4B Instructed
Input tokens$20.00
Output tokens$40.00
Best providerTogether
Mistral AI
Ministral 3 (3B Instruct 2512)
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

5.0B diff

Gemma 3n E4B Instructed has 5.0B more parameters than Ministral 3 (3B Instruct 2512), making it 166.7% larger.

Google
Gemma 3n E4B Instructed
8.0Bparameters
Mistral AI
Ministral 3 (3B Instruct 2512)
3.0Bparameters
8.0B
Gemma 3n E4B Instructed
3.0B
Ministral 3 (3B Instruct 2512)

Context Window

Maximum input and output token capacity

Only Gemma 3n E4B Instructed specifies input context (32,000 tokens). Only Gemma 3n E4B Instructed specifies output context (32,000 tokens).

Google
Gemma 3n E4B Instructed
Input32,000 tokens
Output32,000 tokens
Mistral AI
Ministral 3 (3B Instruct 2512)
Input- tokens
Output- tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3n E4B Instructed and Ministral 3 (3B Instruct 2512) support multimodal inputs.

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

Gemma 3n E4B Instructed

Text
Images
Audio
Video

Ministral 3 (3B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B Instructed is licensed under a proprietary license, while Ministral 3 (3B Instruct 2512) uses Apache 2.0.

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

Gemma 3n E4B Instructed

Proprietary

Closed source

Ministral 3 (3B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B Instructed was released on 2025-06-26, while Ministral 3 (3B Instruct 2512) was released on 2025-12-04.

Ministral 3 (3B Instruct 2512) is 5 months newer than Gemma 3n E4B Instructed.

Gemma 3n E4B Instructed

Jun 26, 2025

9 months ago

Ministral 3 (3B Instruct 2512)

Dec 4, 2025

4 months ago

5mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while Ministral 3 (3B Instruct 2512)'s cutoff date is not specified.

We can confirm Gemma 3n E4B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without Ministral 3 (3B Instruct 2512)'s cutoff date.

Gemma 3n E4B Instructed

Jun 2024

Ministral 3 (3B Instruct 2512)

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (32,000 tokens)
Mistral AI
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B Instructed
Mistral AI
Ministral 3 (3B Instruct 2512)

FAQ

Common questions about Gemma 3n E4B Instructed vs Ministral 3 (3B Instruct 2512)

Gemma 3n E4B Instructed (Google) and Ministral 3 (3B Instruct 2512) (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Gemma 3n E4B Instructed scores HumanEval: 75.0%, MGSM: 67.0%, MMLU: 64.9%, Global-MMLU-Lite: 64.5%, MBPP: 63.6%. Ministral 3 (3B Instruct 2512) scores MATH: 83.0%, Wild Bench: 56.8%, Arena Hard: 30.5%, MM-MT-Bench: 7.8%.
Gemma 3n E4B Instructed supports 32K tokens and Ministral 3 (3B Instruct 2512) 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 licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B Instructed is developed by Google and Ministral 3 (3B Instruct 2512) is developed by Mistral AI.