Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro is clearly ahead on the aggregate, 90 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Pro's sharpest advantage is in coding, where it averages 84.8 against 43.2. The single biggest benchmark swing on the page is LiveCodeBench, 81 to 39.
GPT-5.2 Pro is the reasoning model in the pair, while DeepSeek V3.2 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5.2 Pro gives you the larger context window at 400K, compared with 128K for DeepSeek V3.2.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Pro
85.9
DeepSeek V3.2
58.8
GPT-5.2 Pro
84.8
DeepSeek V3.2
43.2
GPT-5.2 Pro
96
DeepSeek V3.2
66
GPT-5.2 Pro
95.2
DeepSeek V3.2
75.3
GPT-5.2 Pro
81.5
DeepSeek V3.2
60
GPT-5.2 Pro
95
DeepSeek V3.2
85
GPT-5.2 Pro
93.4
DeepSeek V3.2
82.1
GPT-5.2 Pro
98.2
DeepSeek V3.2
82.1
GPT-5.2 Pro is ahead overall, 90 to 64. The biggest single separator in this matchup is LiveCodeBench, where the scores are 81 and 39.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 60. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 43.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for math in this comparison, averaging 98.2 versus 82.1. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 75.3. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 58.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 66. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for instruction following in this comparison, averaging 95 versus 85. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 82.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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