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Llama 3.2 3B Instruct vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Reasoning leads with 19.5% higher average benchmark score. Overall, Phi 4 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 Reasoning was developed to incorporate extended analytical thinking into the Phi-4 architecture, designed to spend more time on complex problem-solving. Built to combine compact model efficiency with reasoning depth, it represents Microsoft's exploration of thoughtful small models.
7 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Phi 4 Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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Llama 3.2 3B Instruct
Average Score:55.1%
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Phi 4 Reasoning
Average Score:74.6%(+19.5%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Reasoning
2025-03-01
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 Reasoning
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Llama 3.2 3B Instruct
Avg Score:55.1%
Providers:1
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Phi 4 Reasoning
Avg Score:74.6%(+19.5%)
Providers:0