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Llama 3.1 8B Instruct vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 3.7% higher average benchmark score. Llama 3.1 8B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
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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-3.5 MoE was created using a mixture-of-experts architecture, designed to provide enhanced capabilities while maintaining efficiency through sparse activation. Built to combine the benefits of larger models with practical computational requirements, it represents Microsoft's exploration of efficient scaling techniques.
1 month newer
Llama 3.1 8B Instruct
Meta
2024-07-23
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
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Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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Llama 3.1 8B Instruct
Average Score:60.8%
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Phi-3.5-MoE-instruct
Average Score:64.5%(+3.7%)
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Knowledge Cutoff
Training data recency comparison
Llama 3.1 8B Instruct
2023-12-31
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:60.8%
Providers:9
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Phi-3.5-MoE-instruct
Avg Score:64.5%(+3.7%)
Providers:0