Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Nemotron 3 Ultra 500B is clearly ahead on the aggregate, 67 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Nemotron 3 Ultra 500B's sharpest advantage is in mathematics, where it averages 74.4 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 76 to 9.8. GPT-4.1 nano does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Nemotron 3 Ultra 500B is the reasoning model in the pair, while GPT-4.1 nano 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 Ultra 500B gives you the larger context window at 10M, compared with 1M for GPT-4.1 nano.
Pick Nemotron 3 Ultra 500B if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Nemotron 3 Ultra 500B
62.5
GPT-4.1 nano
65.2
Nemotron 3 Ultra 500B
74.4
GPT-4.1 nano
9.8
Nemotron 3 Ultra 500B
84
GPT-4.1 nano
83.2
Nemotron 3 Ultra 500B is ahead overall, 67 to 23. The biggest single separator in this matchup is AIME 2024, where the scores are 76 and 9.8.
GPT-4.1 nano has the edge for knowledge tasks in this comparison, averaging 65.2 versus 62.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Nemotron 3 Ultra 500B has the edge for math in this comparison, averaging 74.4 versus 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
Nemotron 3 Ultra 500B has the edge for instruction following in this comparison, averaging 84 versus 83.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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