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o1-mini vs o4-mini
Comprehensive side-by-side LLM comparison
o4-mini leads with 21.4% higher average benchmark score. o4-mini offers 106.5K more tokens in context window than o1-mini. o4-mini is $9.50 cheaper per million tokens. o4-mini supports multimodal inputs. Overall, o4-mini is the stronger choice for coding tasks.
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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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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.
7 months newer
o1-mini
OpenAI
2024-09-12
o4-mini
OpenAI
2025-04-16
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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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o4-mini
Input:$1.10
Output:$4.40($9.50 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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o1-mini
Average Score:60.0%
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o4-mini
Average Score:81.4%(+21.4%)
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Knowledge Cutoff
Training data recency comparison
o4-mini
2024-05-31
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:60.0%
Providers:2
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o4-mini
Avg Score:81.4%(+21.4%)
Providers:1