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o3-mini vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
o3-mini leads with 39.6% higher average benchmark score. o3-mini offers 44.0K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $5.30 cheaper per million tokens. Overall, o3-mini is the stronger choice for coding tasks.
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OpenAI
o3-mini was created as an efficient variant of the o3 reasoning model, designed to provide advanced thinking capabilities with reduced computational requirements. Built to make next-generation reasoning accessible to a broader range of applications, it balances analytical depth with practical speed and cost considerations.
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Microsoft
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
5 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
o3-mini
OpenAI
2025-01-30
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Pricing Comparison
Cost per million tokens (USD)
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o3-mini
Input:$1.10
Output:$4.40
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($5.30 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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o3-mini
Average Score:88.5%(+39.6%)
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Phi-3.5-mini-instruct
Average Score:48.9%
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Knowledge Cutoff
Training data recency comparison
o3-mini
2023-09-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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o3-mini
2 providers
Azure
Throughput: 115 tok/s
Latency: 5.2ms
OpenAI
Throughput: 115 tok/s
Latency: 5.2ms
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o3-mini
Avg Score:88.5%(+39.6%)
Providers:2
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Phi-3.5-mini-instruct
Avg Score:48.9%
Providers:1