Gemma 3n E2B Instructed vs Ministral 3 (14B Reasoning 2512)
Ministral 3 (14B Reasoning 2512) leads the LLM Stats Score 20.6 to -10.6.
Google · Mistral AI · Updated for 2026
Which is better?
Ministral 3 (14B Reasoning 2512) leads the overall LLM Stats Score 20.6 to -10.6, ranking #199 overall.
In the 3 individual benchmarks reported for both models, Ministral 3 (14B Reasoning 2512) wins 3; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemma 3n E2B Instructed
- you are already invested in the Google ecosystem
Choose Ministral 3 (14B Reasoning 2512)
- overall performance matters — it scores 20.6 and ranks #199 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you want the most recent training data — it shipped Dec 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for Gemma 3n E2B Instructed · 4 for Ministral 3 (14B Reasoning 2512)
Gemma 3n E2B Instructed outperforms in 0 benchmarks, while Ministral 3 (14B Reasoning 2512) is better at 3 benchmarks (AIME 2025, GPQA, LiveCodeBench).
Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Ministral 3 (14B Reasoning 2512) has 6.0B more parameters than Gemma 3n E2B Instructed, making it 75.0% larger.
Context Window
Maximum input and output token capacity
Only Ministral 3 (14B Reasoning 2512) specifies input context (262,100 tokens). Only Ministral 3 (14B Reasoning 2512) specifies output context (262,100 tokens).
Input capabilities
Documented input modalities across available providers
Both Gemma 3n E2B Instructed and Ministral 3 (14B Reasoning 2512) support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3n E2B Instructed
Ministral 3 (14B Reasoning 2512)
License
Usage and distribution terms
Gemma 3n E2B Instructed is licensed under a proprietary license, while Ministral 3 (14B Reasoning 2512) uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemma 3n E2B Instructed was released on 2025-06-26, while Ministral 3 (14B Reasoning 2512) was released on 2025-12-04.
Ministral 3 (14B Reasoning 2512) is 5 months newer than Gemma 3n E2B Instructed.
Jun 26, 2025
1.2 years ago
Dec 4, 2025
9 months ago
5mo newerKnowledge Cutoff
When training data ends
Gemma 3n E2B Instructed has a documented knowledge cutoff of 2024-06-01, while Ministral 3 (14B Reasoning 2512)'s cutoff date is not specified.
We can confirm Gemma 3n E2B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without Ministral 3 (14B Reasoning 2512)'s cutoff date.
Jun 2024
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Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3n E2B Instructed and Ministral 3 (14B Reasoning 2512) side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3n E2B Instructed vs Ministral 3 (14B Reasoning 2512).