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o1-mini vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct offers 62.5K more tokens in context window than o1-mini. Phi-4-multimodal-instruct is $14.85 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
o1-mini was created as a faster, more cost-effective reasoning model, designed to bring extended thinking capabilities to applications with tighter latency and budget constraints. Built to excel particularly in coding and STEM reasoning while maintaining affordability, it provides a more accessible entry point to reasoning-enhanced AI assistance.
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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.
4 months newer
o1-mini
OpenAI
2024-09-12
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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Pricing Comparison
Cost per million tokens (USD)
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o1-mini
Input:$3.00
Output:$12.00
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($14.85 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
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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o1-mini
2 providers
Azure
Throughput: 100 tok/s
Latency: 0.5ms
OpenAI
Throughput: 115 tok/s
Latency: 5.2ms
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o1-mini
Avg Score:0.0%
Providers:2
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1