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Gemma 3n E4B vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
Gemma 3n E4B leads with 4.8% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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Gemma 3n E4B is a multimodal language model developed by Google. It achieves strong performance with an average score of 64.6% across 11 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). 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-3.5-vision-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 68.3% across 9 benchmarks. It excels particularly in ScienceQA (91.3%), POPE (86.1%), MMBench (81.9%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
10 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
Gemma 3n E4B
2025-06-26
Average performance across 20 common benchmarks
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Gemma 3n E4B
Average Score:35.5%(+4.8%)
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Phi-3.5-vision-instruct
Average Score:30.7%
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E4B
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 E4B
0 providers
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Phi-3.5-vision-instruct
0 providers
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Gemma 3n E4B
Avg Score:35.5%(+4.8%)
Providers:0
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Phi-3.5-vision-instruct
Avg Score:30.7%
Providers:0