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Llama 3.2 3B Instruct vs Phi 4
Comprehensive side-by-side LLM comparison
Phi 4 leads with 17.0% higher average benchmark score. Llama 3.2 3B Instruct offers 224.0K more tokens in context window than Phi 4. Both models have similar pricing. Overall, Phi 4 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 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
2 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Phi 4
Microsoft
2024-12-12
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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($0.18 cheaper)
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Phi 4
Input:$0.07
Output:$0.14
Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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Llama 3.2 3B Instruct
Average Score:56.0%
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Phi 4
Average Score:73.0%(+17.0%)
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Knowledge Cutoff
Training data recency comparison
Phi 4
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
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Llama 3.2 3B Instruct
Avg Score:56.0%
Providers:1
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Phi 4
Avg Score:73.0%(+17.0%)
Providers:1