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Gemma 3 12B vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
Gemma 3 12B leads with 24.2% higher average benchmark score. Gemma 3 12B supports multimodal inputs. Overall, Gemma 3 12B is the stronger choice for coding tasks.
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Gemma 3 12B is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 26 benchmarks. It excels particularly in GSM8k (94.4%), IFEval (88.9%), DocVQA (87.1%). 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 Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 75.1% across 11 benchmarks. It excels particularly in FlenQA (97.7%), HumanEval+ (92.9%), IFEval (83.4%). 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
Gemma 3 12B
2025-03-12
Phi 4 Reasoning
Microsoft
2025-04-30
Performance Metrics
Context window and performance specifications
Average performance across 33 common benchmarks
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Gemma 3 12B
Average Score:49.2%(+24.2%)
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Phi 4 Reasoning
Average Score:25.0%
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Knowledge Cutoff
Training data recency comparison
Phi 4 Reasoning
2025-03-01
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 12B
1 providers
DeepInfra
Throughput: 33 tok/s
Latency: 0.2ms
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Phi 4 Reasoning
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Gemma 3 12B
Avg Score:49.2%(+24.2%)
Providers:1
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Phi 4 Reasoning
Avg Score:25.0%
Providers:0