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Llama 3.3 70B Instruct vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Mini Reasoning leads with 1.5% higher average benchmark score. Llama 3.3 70B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
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Meta
Llama 3.3 70B was introduced with refinements to the Llama 3 architecture, designed to incorporate improvements in instruction-following and task performance. Built to continue the evolution of Meta's 70B tier, it provides enhanced quality while maintaining the deployment characteristics valued by the open-source community.
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Microsoft
Phi-4 Mini Reasoning was developed to incorporate extended thinking capabilities into the ultra-compact Phi-4 Mini architecture. Built to demonstrate that reasoning enhancements can be applied even to very small models, it brings analytical depth to resource-constrained environments.
4 months newer
Llama 3.3 70B Instruct
Meta
2024-12-06
Phi 4 Mini Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Llama 3.3 70B Instruct
Average Score:50.5%
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Phi 4 Mini Reasoning
Average Score:52.0%(+1.5%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini Reasoning
2025-02-01
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 3.3 70B Instruct
9 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Cerebras
Throughput: 2220 tok/s
Latency: 0.65ms
DeepInfra
Throughput: 37 tok/s
Latency: 0.65ms
Fireworks
Throughput: 197 tok/s
Latency: 0.65ms
Groq
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Llama 3.3 70B Instruct
Avg Score:50.5%
Providers:9
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Phi 4 Mini Reasoning
Avg Score:52.0%(+1.5%)
Providers:0