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Gemma 3 4B vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 2.1% higher average benchmark score. Gemma 3 4B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Gemma 3 4B was developed as a compact yet capable open-source model, designed to strike a balance between performance and resource efficiency. Built with 4 billion parameters and instruction tuning, it provides a practical option for applications requiring moderate capability with manageable computational costs.
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Microsoft
Phi-3.5 MoE was created using a mixture-of-experts architecture, designed to provide enhanced capabilities while maintaining efficiency through sparse activation. Built to combine the benefits of larger models with practical computational requirements, it represents Microsoft's exploration of efficient scaling techniques.
6 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Gemma 3 4B
2025-03-12
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Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
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Gemma 3 4B
Average Score:63.7%
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Phi-3.5-MoE-instruct
Average Score:65.8%(+2.1%)
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Knowledge Cutoff
Training data recency comparison
Gemma 3 4B
2024-08-01
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 3 4B
1 providers
DeepInfra
Throughput: 33 tok/s
Latency: 0.2ms
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Phi-3.5-MoE-instruct
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Gemma 3 4B
Avg Score:63.7%
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:65.8%(+2.1%)
Providers:0