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DeepSeek-V3.2-Exp vs Phi 4
Comprehensive side-by-side LLM comparison
DeepSeek-V3.2-Exp leads with 44.2% higher average benchmark score. DeepSeek-V3.2-Exp offers 197.4K more tokens in context window than Phi 4. 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-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
9 months newer
Phi 4
Microsoft
2024-12-12
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 4
Input:$0.07
Output:$0.14($0.47 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V3.2-Exp
Average Score:87.3%(+44.2%)
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Phi 4
Average Score:43.2%
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Knowledge Cutoff
Training data recency comparison
Phi 4
2024-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
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 4
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DeepSeek-V3.2-Exp
Avg Score:87.3%(+44.2%)
Providers:2
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Phi 4
Avg Score:43.2%
Providers:1