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o1 vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
o1 leads with 32.6% higher average benchmark score. o1 offers 44.0K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $74.80 cheaper per million tokens. Overall, o1 is the stronger choice for coding tasks.
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OpenAI
o1 was developed as part of OpenAI's reasoning-focused model series, designed to spend more time thinking before responding. Built to excel at complex reasoning tasks in science, coding, and mathematics, it employs extended internal reasoning processes to solve harder problems than traditional language models through careful step-by-step analysis.
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Microsoft
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
3 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
o1
OpenAI
2024-12-17
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Pricing Comparison
Cost per million tokens (USD)
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o1
Input:$15.00
Output:$60.00
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($74.80 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
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o1
Average Score:89.8%(+32.6%)
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Phi-3.5-mini-instruct
Average Score:57.2%
Provider Availability & Performance
Available providers and their performance metrics
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o1
2 providers
Azure
Throughput: 16 tok/s
Latency: 0.54ms
OpenAI
Throughput: 66 tok/s
Latency: 16.2ms
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o1
Avg Score:89.8%(+32.6%)
Providers:2
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Phi-3.5-mini-instruct
Avg Score:57.2%
Providers:1