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 40. 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 14.1. 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 Llama 4 Behemoth 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 32K for Llama 4 Behemoth.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Llama 4 Behemoth 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
Llama 4 Behemoth
34.6
GPT-5.2 Pro
84.8
Llama 4 Behemoth
14.1
GPT-5.2 Pro
96
Llama 4 Behemoth
55.1
GPT-5.2 Pro
95.2
Llama 4 Behemoth
47.1
GPT-5.2 Pro
81.5
Llama 4 Behemoth
36.7
GPT-5.2 Pro
95
Llama 4 Behemoth
68
GPT-5.2 Pro
93.4
Llama 4 Behemoth
62.8
GPT-5.2 Pro
98.2
Llama 4 Behemoth
52.9
GPT-5.2 Pro is ahead overall, 90 to 40. 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 36.7. 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 14.1. 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 52.9. 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 47.1. 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 34.6. 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 55.1. Inside this category, OfficeQA 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 68. 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 62.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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