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o1-mini vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 40.8% higher average benchmark score. Phi-3.5-mini-instruct offers 62.5K more tokens in context window than o1-mini. Phi-3.5-mini-instruct is $14.80 cheaper per million tokens. Overall, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
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OpenAI
o1-mini is a language model developed by OpenAI. It achieves strong performance with an average score of 71.9% across 6 benchmarks. It excels particularly in HumanEval (92.4%), MATH-500 (90.0%), MMLU (85.2%). It supports a 194K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents OpenAI's latest advancement in AI technology.
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Microsoft
Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
20 days newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
o1-mini
OpenAI
2024-09-12
Pricing Comparison
Cost per million tokens (USD)
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o1-mini
Input:$3.00
Output:$12.00
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($14.80 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 34 common benchmarks
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o1-mini
Average Score:12.7%
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Phi-3.5-mini-instruct
Average Score:53.5%(+40.8%)
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:12.7%
Providers:2
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Phi-3.5-mini-instruct
Avg Score:53.5%(+40.8%)
Providers:1