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DeepSeek-V3.1 vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 19.7% 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, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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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.
4 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
DeepSeek-V3.1
DeepSeek
2025-01-10
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 45 common benchmarks
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DeepSeek-V3.1
Average Score:20.8%
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Phi-3.5-mini-instruct
Average Score:40.4%(+19.7%)
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:20.8%
Providers:2
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Phi-3.5-mini-instruct
Avg Score:40.4%(+19.7%)
Providers:1