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Llama 3.2 3B Instruct vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 1.1% higher average benchmark score. Both models have similar pricing. 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-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
1 month newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Llama 3.2 3B Instruct
Meta
2024-09-25
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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($0.17 cheaper)
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10
Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
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Llama 3.2 3B Instruct
Average Score:61.2%
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Phi-3.5-mini-instruct
Average Score:62.3%(+1.1%)
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-3.5-mini-instruct
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Llama 3.2 3B Instruct
Avg Score:61.2%
Providers:1
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Phi-3.5-mini-instruct
Avg Score:62.3%(+1.1%)
Providers:1