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Llama 3.2 11B Instruct vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 2.5% higher average benchmark score. Both models have similar pricing. Llama 3.2 11B Instruct is available on 6 providers. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 3.2 11B was introduced as a mid-sized variant in the Llama 3.2 family, designed to offer enhanced capabilities while maintaining efficiency. Built to provide a balanced option for applications requiring more than lightweight models but less than flagship sizes, it serves diverse use cases in the open-source community.
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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.
4 months newer
Llama 3.2 11B Instruct
Meta
2024-09-25
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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Pricing Comparison
Cost per million tokens (USD)
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Llama 3.2 11B Instruct
Input:$0.05
Output:$0.05($0.05 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 6 common benchmarks
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Llama 3.2 11B Instruct
Average Score:66.4%
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Phi-4-multimodal-instruct
Average Score:68.8%(+2.5%)
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Knowledge Cutoff
Training data recency comparison
Llama 3.2 11B Instruct
2023-12-31
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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Llama 3.2 11B Instruct
6 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
DeepInfra
Throughput: 108 tok/s
Latency: 0.5ms
Fireworks
Throughput: 125 tok/s
Latency: 0.2ms
Groq
Throughput: 100 tok/s
Latency: 0.5ms
Sambanova
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Llama 3.2 11B Instruct
Avg Score:66.4%
Providers:6
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Phi-4-multimodal-instruct
Avg Score:68.8%(+2.5%)
Providers:1