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Gemma 3 4B vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 15.6% higher average benchmark score. Gemma 3 4B 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 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 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 4B
2025-03-12
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Pricing Comparison
Cost per million tokens (USD)
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Gemma 3 4B
Input:$0.02
Output:$0.04($0.09 cheaper)
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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 4B
Average Score:65.4%
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Phi-4-multimodal-instruct
Average Score:81.0%(+15.6%)
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Knowledge Cutoff
Training data recency comparison
Phi-4-multimodal-instruct
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-multimodal-instruct
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Gemma 3 4B
Avg Score:65.4%
Providers:1
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Phi-4-multimodal-instruct
Avg Score:81.0%(+15.6%)
Providers:1