Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5 (high) is clearly ahead on the aggregate, 79 to 61. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 (high)'s sharpest advantage is in multimodal & grounded, where it averages 89.4 against 60.4. The single biggest benchmark swing on the page is MMMU-Pro, 93 to 55.
GPT-5 (high) is the reasoning model in the pair, while Nemotron 3 Super 120B A12B 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. Nemotron 3 Super 120B A12B gives you the larger context window at 256K, compared with 128K for GPT-5 (high).
Pick GPT-5 (high) if you want the stronger benchmark profile. Nemotron 3 Super 120B A12B only becomes the better choice if you need the larger 256K context window or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5 (high)
75.2
Nemotron 3 Super 120B A12B
55.3
GPT-5 (high)
66.1
Nemotron 3 Super 120B A12B
44.2
GPT-5 (high)
89.4
Nemotron 3 Super 120B A12B
60.4
GPT-5 (high)
85.7
Nemotron 3 Super 120B A12B
71.8
GPT-5 (high)
71.1
Nemotron 3 Super 120B A12B
55.8
GPT-5 (high)
91
Nemotron 3 Super 120B A12B
86
GPT-5 (high)
86.4
Nemotron 3 Super 120B A12B
81.5
GPT-5 (high)
94
Nemotron 3 Super 120B A12B
74.6
GPT-5 (high) is ahead overall, 79 to 61. The biggest single separator in this matchup is MMMU-Pro, where the scores are 93 and 55.
GPT-5 (high) has the edge for knowledge tasks in this comparison, averaging 71.1 versus 55.8. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for coding in this comparison, averaging 66.1 versus 44.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for math in this comparison, averaging 94 versus 74.6. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for reasoning in this comparison, averaging 85.7 versus 71.8. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for agentic tasks in this comparison, averaging 75.2 versus 55.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for multimodal and grounded tasks in this comparison, averaging 89.4 versus 60.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for instruction following in this comparison, averaging 91 versus 86. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for multilingual tasks in this comparison, averaging 86.4 versus 81.5. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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