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Gemma 3 12B vs Phi 4
Comprehensive side-by-side LLM comparison
Gemma 3 12B leads with 1.7% higher average benchmark score. Gemma 3 12B offers 230.1K more tokens in context window than Phi 4. Both models have similar pricing. Gemma 3 12B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Gemma 3 12B was developed as part of the third generation of Google's open-source model family, designed to provide enhanced capabilities in a mid-sized format. Built with improved architecture and training techniques, it balances performance with practical deployment considerations for diverse use cases.
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Microsoft
Phi-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
3 months newer
Phi 4
Microsoft
2024-12-12
Gemma 3 12B
2025-03-12
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Pricing Comparison
Cost per million tokens (USD)
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Gemma 3 12B
Input:$0.05
Output:$0.10($0.06 cheaper)
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Phi 4
Input:$0.07
Output:$0.14
Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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Gemma 3 12B
Average Score:61.0%(+1.7%)
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Phi 4
Average Score:59.2%
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Knowledge Cutoff
Training data recency comparison
Phi 4
2024-06-01
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
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Gemma 3 12B
Avg Score:61.0%(+1.7%)
Providers:1
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Phi 4
Avg Score:59.2%
Providers:1