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Llama 3.3 70B Instruct vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Reasoning leads with 4.0% 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 Reasoning was developed to incorporate extended analytical thinking into the Phi-4 architecture, designed to spend more time on complex problem-solving. Built to combine compact model efficiency with reasoning depth, it represents Microsoft's exploration of thoughtful small models.
4 months newer
Llama 3.3 70B Instruct
Meta
2024-12-06
Phi 4 Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Llama 3.3 70B Instruct
Average Score:70.5%
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Phi 4 Reasoning
Average Score:74.5%(+4.0%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Reasoning
2025-03-01
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:70.5%
Providers:9
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Phi 4 Reasoning
Avg Score:74.5%(+4.0%)
Providers:0