Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Instant is clearly ahead on the aggregate, 85 to 40. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Instant's sharpest advantage is in coding, where it averages 75.5 against 14.1. The single biggest benchmark swing on the page is SWE-bench Pro, 77 to 15.
GPT-5.2 Instant 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 Instant gives you the larger context window at 128K, compared with 32K for Llama 4 Behemoth.
Pick GPT-5.2 Instant 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 Instant
79.6
Llama 4 Behemoth
34.6
GPT-5.2 Instant
75.5
Llama 4 Behemoth
14.1
GPT-5.2 Instant
93.1
Llama 4 Behemoth
55.1
GPT-5.2 Instant
90.9
Llama 4 Behemoth
47.1
GPT-5.2 Instant
79.8
Llama 4 Behemoth
36.7
GPT-5.2 Instant
95
Llama 4 Behemoth
68
GPT-5.2 Instant
94.4
Llama 4 Behemoth
62.8
GPT-5.2 Instant
97.2
Llama 4 Behemoth
52.9
GPT-5.2 Instant is ahead overall, 85 to 40. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 77 and 15.
GPT-5.2 Instant has the edge for knowledge tasks in this comparison, averaging 79.8 versus 36.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for coding in this comparison, averaging 75.5 versus 14.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for math in this comparison, averaging 97.2 versus 52.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for reasoning in this comparison, averaging 90.9 versus 47.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for agentic tasks in this comparison, averaging 79.6 versus 34.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 Instant has the edge for multimodal and grounded tasks in this comparison, averaging 93.1 versus 55.1. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Instant 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 Instant has the edge for multilingual tasks in this comparison, averaging 94.4 versus 62.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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