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Llama 3.2 3B Instruct vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Phi 4 Mini leads with 4.8% higher average benchmark score. 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 Mini was created as an even more compact variant of Phi-4, designed to bring fourth-generation capabilities to the smallest possible footprint. Built for extreme efficiency scenarios, it enables AI capabilities on devices and applications where resources are severely constrained.
4 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Phi 4 Mini
Microsoft
2025-02-01
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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 4 Mini
Average Score:66.0%(+4.8%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini
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 Mini
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Llama 3.2 3B Instruct
Avg Score:61.2%
Providers:1
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Phi 4 Mini
Avg Score:66.0%(+4.8%)
Providers:0