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DeepSeek-V3.1 vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 40.4% higher average benchmark score. DeepSeek-V3.1 offers 71.7K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $1.07 cheaper per million tokens. Overall, DeepSeek-V3.1 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.1 was developed as an incremental advancement over DeepSeek-V3, designed to refine the mixture-of-experts architecture with improved training techniques. Built to enhance quality and efficiency while maintaining the open-source philosophy, it represents continued iteration on DeepSeek's flagship model line.
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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.
4 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
DeepSeek-V3.1
DeepSeek
2025-01-10
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.1
Input:$0.27
Output:$1.00
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($1.07 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V3.1
Average Score:79.3%(+40.4%)
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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-V3.1
2 providers
DeepInfra
Novita
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Phi-3.5-mini-instruct
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DeepSeek-V3.1
Avg Score:79.3%(+40.4%)
Providers:2
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Phi-3.5-mini-instruct
Avg Score:38.9%
Providers:1