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 70. 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 51.2. The single biggest benchmark swing on the page is LiveCodeBench, 81 to 45.
GPT-5.2 Pro gives you the larger context window at 400K, compared with 128K for DeepSeek V3.2 (Thinking).
Pick GPT-5.2 Pro if you want the stronger benchmark profile. DeepSeek V3.2 (Thinking) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5.2 Pro
85.9
DeepSeek V3.2 (Thinking)
69.4
GPT-5.2 Pro
84.8
DeepSeek V3.2 (Thinking)
51.2
GPT-5.2 Pro
96
DeepSeek V3.2 (Thinking)
71
GPT-5.2 Pro
95.2
DeepSeek V3.2 (Thinking)
80.6
GPT-5.2 Pro
81.5
DeepSeek V3.2 (Thinking)
64.4
GPT-5.2 Pro
95
DeepSeek V3.2 (Thinking)
85
GPT-5.2 Pro
93.4
DeepSeek V3.2 (Thinking)
80.8
GPT-5.2 Pro
98.2
DeepSeek V3.2 (Thinking)
85.1
GPT-5.2 Pro is ahead overall, 90 to 70. The biggest single separator in this matchup is LiveCodeBench, where the scores are 81 and 45.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 64.4. 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 51.2. 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 85.1. 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 80.6. 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 69.4. Inside this category, BrowseComp 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 71. 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 80.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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