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DeepSeek-V3.2-Exp vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V3.2-Exp leads with 43.6% higher average benchmark score. Phi-3.5-mini-instruct offers 26.6K more tokens in context window than DeepSeek-V3.2-Exp. Both models have similar pricing. Overall, DeepSeek-V3.2-Exp is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.2-Exp was introduced as an experimental release, designed to test new architectural innovations and training methodologies. Built to explore the boundaries of mixture-of-experts design, it serves as a research preview for techniques that may be incorporated into future stable releases.
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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
Phi-3.5-mini-instruct
Microsoft
2024-08-23
DeepSeek-V3.2-Exp
DeepSeek
2025-09-29
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2-Exp
Input:$0.27
Output:$0.41
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($0.48 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V3.2-Exp
Average Score:82.5%(+43.6%)
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Phi-3.5-mini-instruct
Average Score:38.9%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2-Exp
2 providers
Novita
ZeroEval
Throughput: 100 tok/s
Latency: 0.7ms
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Phi-3.5-mini-instruct
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DeepSeek-V3.2-Exp
Avg Score:82.5%(+43.6%)
Providers:2
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Phi-3.5-mini-instruct
Avg Score:38.9%
Providers:1