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o3-mini vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
o3-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. Phi-4-multimodal-instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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-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 days newer
o3-mini
OpenAI
2025-01-30
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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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-4-multimodal-instruct
Input:$0.05
Output:$0.10($5.35 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
o3-mini
2023-09-30
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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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:0.0%
Providers:2
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1