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 85. 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 knowledge, where it averages 81.5 against 72.5. The single biggest benchmark swing on the page is HLE, 44 to 26. GPT-5.2-Codex does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $2.00 input / $8.00 output per 1M tokens for GPT-5.2-Codex. That is roughly 18.8x on output cost alone.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. GPT-5.2-Codex only becomes the better choice if agentic is the priority or you want the cheaper token bill.
GPT-5.2 Pro
85.9
GPT-5.2-Codex
87
GPT-5.2 Pro
84.8
GPT-5.2-Codex
76
GPT-5.2 Pro
96
GPT-5.2-Codex
87.6
GPT-5.2 Pro
95.2
GPT-5.2-Codex
92
GPT-5.2 Pro
81.5
GPT-5.2-Codex
72.5
GPT-5.2 Pro
95
GPT-5.2-Codex
92
GPT-5.2 Pro
93.4
GPT-5.2-Codex
88.4
GPT-5.2 Pro
98.2
GPT-5.2-Codex
95.4
GPT-5.2 Pro is ahead overall, 90 to 85. The biggest single separator in this matchup is HLE, where the scores are 44 and 26.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 72.5. 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 76. 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 95.4. 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 92. Inside this category, BBH is the benchmark that creates the most daylight between them.
GPT-5.2-Codex has the edge for agentic tasks in this comparison, averaging 87 versus 85.9. 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 87.6. 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 92. 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 88.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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