Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K 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.

Microsoft

Phi 4

Microsoft

Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model shows particular specialization in math tasks with an average performance of 80.5%. 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.

Microsoft

Phi 4

Microsoft

2024-12-12

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

2025-09-29

9 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.2-Exp

Input:$0.27
Output:$0.41
Microsoft

Phi 4

$0.47 cheaper
Input:$0.07
Output:$0.14

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.2-Exp

Larger context
Max Context:229.4K
Parameters:685.0B
Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B

Average performance across 24 common benchmarks

DeepSeek

DeepSeek-V3.2-Exp

+2.8%
Average Score:38.6%
Microsoft

Phi 4

Average Score:35.8%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.2-Exp

factuality
+94.1%
97.1%
math
+6.0%
86.5%
code
64.3%
general
62.1%
Microsoft

Phi 4

factuality
3.0%
math
80.5%
code
+11.9%
76.1%
general
+4.5%
66.6%
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

DeepSeek

DeepSeek-V3.2-Exp

2 providers

Novita

ZeroEval

Throughput: 100 tok/s
Latency: 0.7ms
Microsoft

Phi 4

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
DeepSeek

DeepSeek-V3.2-Exp

+2.8%
Avg Score:38.6%
Providers:2
Microsoft

Phi 4

Avg Score:35.8%
Providers:1