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Llama 3.2 3B Instruct vs Phi 4
Comprehensive side-by-side LLM comparison
Phi 4 leads with 1.1% 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. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta's latest advancement in AI technology.
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Microsoft
Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
2 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Phi 4
Microsoft
2024-12-12
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 23 common benchmarks
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Llama 3.2 3B Instruct
Average Score:36.3%
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Phi 4
Average Score:37.3%(+1.1%)
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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:36.3%
Providers:1
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Phi 4
Avg Score:37.3%(+1.1%)
Providers:1