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Llama 3.2 3B Instruct vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Both models have similar pricing. Phi-4-multimodal-instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 3.2 3B was created as an ultra-compact open-source model, designed to enable on-device and edge deployment scenarios. Built with just 3 billion parameters while retaining instruction-following abilities, it brings Meta's language technology to mobile devices, IoT applications, and resource-constrained environments.
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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 3B 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 3B Instruct
Input:$0.01
Output:$0.02($0.12 cheaper)
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10
Performance Metrics
Context window and performance specifications
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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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Llama 3.2 3B Instruct
1 providers
DeepInfra
Throughput: 171.5 tok/s
Latency: 0.24ms
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Phi-4-multimodal-instruct
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Llama 3.2 3B Instruct
Avg Score:0.0%
Providers:1
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1