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 49.1. The single biggest benchmark swing on the page is LiveCodeBench, 81 to 40.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $10.00 input / $40.00 output per 1M tokens for o3. That is roughly 3.8x on output cost alone. GPT-5.2 Pro gives you the larger context window at 400K, compared with 200K for o3.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. o3 only becomes the better choice if you want the cheaper token bill.
GPT-5.2 Pro
85.9
o3
69.9
GPT-5.2 Pro
84.8
o3
49.1
GPT-5.2 Pro
96
o3
72.3
GPT-5.2 Pro
95.2
o3
82.6
GPT-5.2 Pro
81.5
o3
66
GPT-5.2 Pro
95
o3
85
GPT-5.2 Pro
93.4
o3
81.1
GPT-5.2 Pro
98.2
o3
87.5
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 40.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 66. 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 49.1. 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 87.5. 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 82.6. 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 69.9. 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 72.3. 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 81.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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