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Gemma 3 12B vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 5.1% higher average benchmark score. Gemma 3 12B offers 6.1K more tokens in context window than Phi-4-multimodal-instruct. Both models have similar pricing. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
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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 Multimodal was created to handle multiple input modalities including text, images, and potentially other formats. Built to extend Phi-4's efficiency into multimodal applications, it demonstrates that compact models can successfully integrate diverse information types.
1 month newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10
Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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Gemma 3 12B
Average Score:75.9%
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Phi-4-multimodal-instruct
Average Score:81.0%(+5.1%)
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Knowledge Cutoff
Training data recency comparison
Phi-4-multimodal-instruct
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-multimodal-instruct
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Gemma 3 12B
Avg Score:75.9%
Providers:1
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Phi-4-multimodal-instruct
Avg Score:81.0%(+5.1%)
Providers:1