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 35. 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 14.8. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 15.
GPT-5.2 Pro is the reasoning model in the pair, while DeepSeek V3.1 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 V3.1.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. DeepSeek V3.1 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 V3.1
32.9
GPT-5.2 Pro
84.8
DeepSeek V3.1
14.8
GPT-5.2 Pro
96
DeepSeek V3.1
39.5
GPT-5.2 Pro
95.2
DeepSeek V3.1
40.7
GPT-5.2 Pro
81.5
DeepSeek V3.1
30.5
GPT-5.2 Pro
95
DeepSeek V3.1
67
GPT-5.2 Pro
93.4
DeepSeek V3.1
60.8
GPT-5.2 Pro
98.2
DeepSeek V3.1
44.2
GPT-5.2 Pro is ahead overall, 90 to 35. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 15.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 30.5. Inside this category, GPQA 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 14.8. Inside this category, SWE-bench Pro 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 44.2. Inside this category, HMMT Feb 2023 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 40.7. Inside this category, SimpleQA 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 32.9. 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 39.5. 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 67. 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 60.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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