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Llama 3.1 8B Instruct vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. 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-4 Mini was created as an even more compact variant of Phi-4, designed to bring fourth-generation capabilities to the smallest possible footprint. Built for extreme efficiency scenarios, it enables AI capabilities on devices and applications where resources are severely constrained.
6 months newer
Llama 3.1 8B Instruct
Meta
2024-07-23
Phi 4 Mini
Microsoft
2025-02-01
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Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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Llama 3.1 8B Instruct
Average Score:57.9%(+0.6%)
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Phi 4 Mini
Average Score:57.3%
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Knowledge Cutoff
Training data recency comparison
Llama 3.1 8B Instruct
2023-12-31
Phi 4 Mini
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:57.9%(+0.6%)
Providers:9
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Phi 4 Mini
Avg Score:57.3%
Providers:0