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 42. 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 12.9. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 15.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Scout. That is roughly Infinityx on output cost alone. GPT-5.2 Pro is the reasoning model in the pair, while Llama 4 Scout 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. Llama 4 Scout gives you the larger context window at 10M, compared with 400K for GPT-5.2 Pro.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Llama 4 Scout only becomes the better choice if you want the cheaper token bill or you need the larger 10M context window.
GPT-5.2 Pro
85.9
Llama 4 Scout
40.6
GPT-5.2 Pro
84.8
Llama 4 Scout
12.9
GPT-5.2 Pro
96
Llama 4 Scout
57.8
GPT-5.2 Pro
95.2
Llama 4 Scout
55
GPT-5.2 Pro
81.5
Llama 4 Scout
35.6
GPT-5.2 Pro
95
Llama 4 Scout
68
GPT-5.2 Pro
93.4
Llama 4 Scout
59.8
GPT-5.2 Pro
98.2
Llama 4 Scout
51
GPT-5.2 Pro is ahead overall, 90 to 42. 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 35.6. 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 12.9. 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 51. 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 55. 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 40.6. 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 57.8. 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 59.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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