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Llama 3.2 3B Instruct vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Mini Reasoning leads with 19.2% higher average benchmark score. Overall, Phi 4 Mini Reasoning is the stronger choice for coding tasks.
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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 Reasoning was developed to incorporate extended thinking capabilities into the ultra-compact Phi-4 Mini architecture. Built to demonstrate that reasoning enhancements can be applied even to very small models, it brings analytical depth to resource-constrained environments.
7 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Phi 4 Mini Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Llama 3.2 3B Instruct
Average Score:32.8%
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Phi 4 Mini Reasoning
Average Score:52.0%(+19.2%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini Reasoning
2025-02-01
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 Reasoning
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Llama 3.2 3B Instruct
Avg Score:32.8%
Providers:1
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Phi 4 Mini Reasoning
Avg Score:52.0%(+19.2%)
Providers:0