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GPT-3.5 Turbo vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 43.6% 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. Overall, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
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OpenAI
GPT-3.5 Turbo is a language model developed by OpenAI. The model shows competitive results across 8 benchmarks. Notable strengths include DROP (70.2%), MMLU (69.8%), HumanEval (68.0%). The model is available through 2 API providers.
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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.
1 year newer
GPT-3.5 Turbo
OpenAI
2023-03-21
Phi-3.5-mini-instruct
Microsoft
2024-08-23
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 34 common benchmarks
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GPT-3.5 Turbo
Average Score:9.9%
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Phi-3.5-mini-instruct
Average Score:53.5%(+43.6%)
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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:9.9%
Providers:2
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Phi-3.5-mini-instruct
Avg Score:53.5%(+43.6%)
Providers:1