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Gemma 3 4B vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Mini Reasoning leads with 21.2% higher average benchmark score. Gemma 3 4B supports multimodal inputs. Overall, Phi 4 Mini Reasoning is the stronger choice for coding tasks.
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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 Reasoning was developed to incorporate extended thinking capabilities into the ultra-compact Phi-4 Mini architecture. Built to demonstrate that reasoning enhancements can be applied even to very small models, it brings analytical depth to resource-constrained environments.
1 month newer
Gemma 3 4B
2025-03-12
Phi 4 Mini Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Gemma 3 4B
Average Score:30.8%
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Phi 4 Mini Reasoning
Average Score:52.0%(+21.2%)
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Knowledge Cutoff
Training data recency comparison
Gemma 3 4B
2024-08-01
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 3 4B
1 providers
DeepInfra
Throughput: 33 tok/s
Latency: 0.2ms
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Phi 4 Mini Reasoning
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Gemma 3 4B
Avg Score:30.8%
Providers:1
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Phi 4 Mini Reasoning
Avg Score:52.0%(+21.2%)
Providers:0