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 43. 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 21.5. The single biggest benchmark swing on the page is SWE-bench Verified, 83 to 17.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $0.55 input / $2.19 output per 1M tokens for DeepSeek-R1. That is roughly 68.5x on output cost alone. GPT-5.2 Pro gives you the larger context window at 400K, compared with 128K for DeepSeek-R1.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. DeepSeek-R1 only becomes the better choice if you want the cheaper token bill.
GPT-5.2 Pro
85.9
DeepSeek-R1
44.5
GPT-5.2 Pro
84.8
DeepSeek-R1
21.5
GPT-5.2 Pro
96
DeepSeek-R1
47.5
GPT-5.2 Pro
95.2
DeepSeek-R1
50.9
GPT-5.2 Pro
81.5
DeepSeek-R1
37.9
GPT-5.2 Pro
95
DeepSeek-R1
69
GPT-5.2 Pro
93.4
DeepSeek-R1
60.4
GPT-5.2 Pro
98.2
DeepSeek-R1
52.5
GPT-5.2 Pro is ahead overall, 90 to 43. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 83 and 17.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 37.9. 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 21.5. Inside this category, SWE-bench Verified 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 52.5. 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 50.9. 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 44.5. 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 47.5. 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 69. 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 60.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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