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DeepSeek R1 Zero vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
DeepSeek R1 Zero leads with 42.9% higher average benchmark score. Overall, DeepSeek R1 Zero is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-R1-Zero was introduced as an experimental variant trained with minimal human supervision, designed to develop reasoning patterns through self-guided reinforcement learning. Built to explore how models can discover analytical strategies independently, it represents research into autonomous reasoning capability development.
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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.
5 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
DeepSeek R1 Zero
DeepSeek
2025-01-20
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek R1 Zero
Average Score:73.3%(+42.9%)
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Phi-3.5-mini-instruct
Average Score:30.4%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek R1 Zero
0 providers
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Phi-3.5-mini-instruct
1 providers
Azure
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DeepSeek R1 Zero
Avg Score:73.3%(+42.9%)
Providers:0
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Phi-3.5-mini-instruct
Avg Score:30.4%
Providers:1