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o3-mini vs Phi 4
Comprehensive side-by-side LLM comparison
o3-mini leads with 19.4% higher average benchmark score. o3-mini offers 268.0K more tokens in context window than Phi 4. Phi 4 is $5.29 cheaper per million tokens. Overall, o3-mini is the stronger choice for coding tasks.
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OpenAI
o3-mini is a language model developed by OpenAI. The model shows competitive results across 26 benchmarks. It excels particularly in COLLIE (98.7%), MATH (97.9%), IFEval (93.9%). It supports a 300K token context window for handling large documents. The model is available through 2 API providers. Released in 2025, it represents OpenAI's latest advancement in AI technology.
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Microsoft
Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
1 month newer
Phi 4
Microsoft
2024-12-12
o3-mini
OpenAI
2025-01-30
Pricing Comparison
Cost per million tokens (USD)
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o3-mini
Input:$1.10
Output:$4.40
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Phi 4
Input:$0.07
Output:$0.14($5.29 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 32 common benchmarks
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o3-mini
Average Score:46.3%(+19.4%)
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Phi 4
Average Score:26.8%
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Knowledge Cutoff
Training data recency comparison
o3-mini
2023-09-30
Phi 4
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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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:46.3%(+19.4%)
Providers:2
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Phi 4
Avg Score:26.8%
Providers:1