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GPT-3.5 Turbo vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
GPT-3.5 Turbo leads with 1.9% higher average benchmark score. Phi-3.5-mini-instruct offers 235.5K more tokens in context window than GPT-3.5 Turbo. Phi-3.5-mini-instruct is $1.80 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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OpenAI
GPT-3.5 Turbo was developed as an optimized version of GPT-3.5, designed to provide a balance of capability and efficiency for conversational and completion tasks. Built to serve as a cost-effective option for applications requiring reliable language understanding and generation, it became widely adopted for chatbots, content generation, and general-purpose AI assistance.
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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.
1 year newer
GPT-3.5 Turbo
OpenAI
2023-03-21
Phi-3.5-mini-instruct
Microsoft
2024-08-23
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Pricing Comparison
Cost per million tokens (USD)
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GPT-3.5 Turbo
Input:$0.50
Output:$1.50
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($1.80 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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GPT-3.5 Turbo
Average Score:53.6%(+1.9%)
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Phi-3.5-mini-instruct
Average Score:51.7%
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Knowledge Cutoff
Training data recency comparison
GPT-3.5 Turbo
2021-09-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GPT-3.5 Turbo
2 providers
Azure
Throughput: 90 tok/s
Latency: 0.8ms
OpenAI
Throughput: 100 tok/s
Latency: 0.5ms
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GPT-3.5 Turbo
Avg Score:53.6%(+1.9%)
Providers:2
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Phi-3.5-mini-instruct
Avg Score:51.7%
Providers:1