DeepSeek V3.2 Benchmark Scores & Performance

Benchmark analysis of DeepSeek V3.2 by DeepSeek across 14 tests.

Creator

DeepSeek

Source Type

Open Weight

Reasoning

Non-Reasoning

Context Window

128K

Overall Score

66#30 of 88

Knowledge Benchmarks

MMLU
84
GPQA
83
SuperGPQA
81
OpenBookQA
79

Coding Benchmarks

HumanEval
76

Mathematics Benchmarks

AIME 2023
84
AIME 2024
86
AIME 2025
85
HMMT Feb 2023
80
HMMT Feb 2024
82
HMMT Feb 2025
81
BRUMO 2025
83

Reasoning Benchmarks

SimpleQA
81
MuSR
79

Frequently Asked Questions

How does DeepSeek V3.2 perform overall in AI benchmarks?

DeepSeek V3.2 ranks #30 out of 88 models with an overall score of 66. It is created by DeepSeek and features a 128K context window.

Is DeepSeek V3.2 good for knowledge and understanding?

DeepSeek V3.2 ranks #30 out of 88 models in knowledge and understanding benchmarks with an average score of 81.8. There are stronger options in this category.

Is DeepSeek V3.2 good for coding and programming?

DeepSeek V3.2 ranks #31 out of 88 models in coding and programming benchmarks with an average score of 76. There are stronger options in this category.

Is DeepSeek V3.2 good for mathematics?

DeepSeek V3.2 ranks #32 out of 88 models in mathematics benchmarks with an average score of 83. There are stronger options in this category.

Is DeepSeek V3.2 good for reasoning and logic?

DeepSeek V3.2 ranks #31 out of 88 models in reasoning and logic benchmarks with an average score of 80. There are stronger options in this category.

Is DeepSeek V3.2 open source?

Yes, DeepSeek V3.2 is an open weight model created by DeepSeek, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

What is the context window size of DeepSeek V3.2?

DeepSeek V3.2 has a context window of 128K tokens, which determines how much text it can process in a single interaction.