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Gemma 3n E2B vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Phi 4 Mini leads with 22.2% higher average benchmark score. Gemma 3n E2B supports multimodal inputs. Overall, Phi 4 Mini 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 is a language model developed by Microsoft. It achieves strong performance with an average score of 65.4% across 17 benchmarks. It excels particularly in GSM8k (88.6%), ARC-C (83.7%), BoolQ (81.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
4 months newer
Phi 4 Mini
Microsoft
2025-02-01
Gemma 3n E2B
2025-06-26
Average performance across 21 common benchmarks
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Gemma 3n E2B
Average Score:30.7%
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Phi 4 Mini
Average Score:52.9%(+22.2%)
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E2B
2024-06-01
Phi 4 Mini
2024-06-01
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
0 providers
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Gemma 3n E2B
Avg Score:30.7%
Providers:0
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Phi 4 Mini
Avg Score:52.9%(+22.2%)
Providers:0