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Gemma 3n E2B vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Gemma 3n E2B leads with 31.5% higher average benchmark score. Gemma 3n E2B supports multimodal inputs. Overall, Gemma 3n E2B is the stronger choice for coding tasks.
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Gemma 3n E2B is a multimodal language model developed by Google. The model shows competitive results across 11 benchmarks. Notable strengths include PIQA (78.9%), BoolQ (76.4%), ARC-E (75.8%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
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Microsoft
Phi 4 Mini Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 68.0% across 3 benchmarks. It excels particularly in MATH-500 (94.6%), AIME (57.5%), GPQA (52.0%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
1 month newer
Phi 4 Mini Reasoning
Microsoft
2025-04-30
Gemma 3n E2B
2025-06-26
Average performance across 14 common benchmarks
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Gemma 3n E2B
Average Score:46.1%(+31.5%)
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Phi 4 Mini Reasoning
Average Score:14.6%
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E2B
2024-06-01
Phi 4 Mini Reasoning
2025-02-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemma 3n E2B
0 providers
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Phi 4 Mini Reasoning
0 providers
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Gemma 3n E2B
Avg Score:46.1%(+31.5%)
Providers:0
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Phi 4 Mini Reasoning
Avg Score:14.6%
Providers:0