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o4-mini vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
o4-mini leads with 44.6% higher average benchmark score. o4-mini supports multimodal inputs. Overall, o4-mini is the stronger choice for coding tasks.
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OpenAI
o4-mini was created as part of the next generation of OpenAI's reasoning models, designed to continue advancing the balance between analytical capability and operational efficiency. Built to bring cutting-edge reasoning techniques to applications requiring quick turnaround, it represents the evolution of compact reasoning-focused 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.
7 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
o4-mini
OpenAI
2025-04-16
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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o4-mini
Average Score:81.4%(+44.6%)
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Phi-3.5-MoE-instruct
Average Score:36.8%
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Knowledge Cutoff
Training data recency comparison
o4-mini
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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o4-mini
1 providers
OpenAI
Throughput: 115 tok/s
Latency: 5.2ms
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Phi-3.5-MoE-instruct
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o4-mini
Avg Score:81.4%(+44.6%)
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:36.8%
Providers:0