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Gemma 3 4B vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Gemma 3 4B 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-4 Mini was created as an even more compact variant of Phi-4, designed to bring fourth-generation capabilities to the smallest possible footprint. Built for extreme efficiency scenarios, it enables AI capabilities on devices and applications where resources are severely constrained.
1 month newer
Phi 4 Mini
Microsoft
2025-02-01
Gemma 3 4B
2025-03-12
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Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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Gemma 3 4B
Average Score:62.3%(+2.1%)
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Phi 4 Mini
Average Score:60.2%
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini
2024-06-01
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 4 Mini
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Gemma 3 4B
Avg Score:62.3%(+2.1%)
Providers:1
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Phi 4 Mini
Avg Score:60.2%
Providers:0