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Llama 3.1 8B Instruct vs Phi 4
Comprehensive side-by-side LLM comparison
Phi 4 leads with 12.0% higher average benchmark score. Llama 3.1 8B Instruct offers 230.1K more tokens in context window than Phi 4. Both models have similar pricing. Llama 3.1 8B Instruct is available on 9 providers. Overall, Phi 4 is the stronger choice for coding tasks.
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Meta
Llama 3.1 8B was developed as an efficient open-source model, designed to bring capable instruction-following to applications with limited computational resources. Built with 8 billion parameters, it provides a lightweight option for developers seeking reliable performance without the overhead of larger models.
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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.
4 months newer
Llama 3.1 8B Instruct
Meta
2024-07-23
Phi 4
Microsoft
2024-12-12
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Pricing Comparison
Cost per million tokens (USD)
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Llama 3.1 8B Instruct
Input:$0.03
Output:$0.03($0.15 cheaper)
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Phi 4
Input:$0.07
Output:$0.14
Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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Llama 3.1 8B Instruct
Average Score:60.1%
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Phi 4
Average Score:72.1%(+12.0%)
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Knowledge Cutoff
Training data recency comparison
Llama 3.1 8B Instruct
2023-12-31
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 3.1 8B Instruct
9 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Cerebras
Throughput: 2047 tok/s
Latency: 0.2ms
DeepInfra
Throughput: 118 tok/s
Latency: 0.5ms
Fireworks
Throughput: 292 tok/s
Latency: 0.5ms
Groq
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Llama 3.1 8B Instruct
Avg Score:60.1%
Providers:9
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Phi 4
Avg Score:72.1%(+12.0%)
Providers:1