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Gemma 3 4B vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 7.0% higher average benchmark score. Gemma 3 4B supports multimodal inputs. Overall, Gemma 3 4B is the stronger choice for coding tasks.
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Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. 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 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.
1 month newer
Phi 4 Mini
Microsoft
2025-02-01
Gemma 3 4B
2025-03-12
Performance Metrics
Context window and performance specifications
Average performance across 38 common benchmarks
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Gemma 3 4B
Average Score:36.3%(+7.0%)
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Phi 4 Mini
Average Score:29.2%
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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:36.3%(+7.0%)
Providers:1
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Phi 4 Mini
Avg Score:29.2%
Providers:0