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o4-mini vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
o4-mini leads with 24.2% higher average benchmark score. o4-mini offers 44.0K more tokens in context window than Phi-4-multimodal-instruct. Phi-4-multimodal-instruct is $5.35 cheaper per million tokens. 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-4 Multimodal was created to handle multiple input modalities including text, images, and potentially other formats. Built to extend Phi-4's efficiency into multimodal applications, it demonstrates that compact models can successfully integrate diverse information types.
2 months newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
o4-mini
OpenAI
2025-04-16
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Pricing Comparison
Cost per million tokens (USD)
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o4-mini
Input:$1.10
Output:$4.40
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($5.35 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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o4-mini
Average Score:82.9%(+24.2%)
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Phi-4-multimodal-instruct
Average Score:58.8%
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Knowledge Cutoff
Training data recency comparison
o4-mini
2024-05-31
Phi-4-multimodal-instruct
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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o4-mini
1 providers
OpenAI
Throughput: 115 tok/s
Latency: 5.2ms
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Phi-4-multimodal-instruct
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o4-mini
Avg Score:82.9%(+24.2%)
Providers:1
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Phi-4-multimodal-instruct
Avg Score:58.8%
Providers:1