Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Nemotron Ultra 253B is clearly ahead on the aggregate, 50 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Nemotron Ultra 253B's sharpest advantage is in mathematics, where it averages 51.3 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 51 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 Ultra 253B 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. GPT-4.1 nano gives you the larger context window at 1M, compared with 32K for Nemotron Ultra 253B.
Pick Nemotron Ultra 253B if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Nemotron Ultra 253B
43.5
GPT-4.1 nano
65.2
Nemotron Ultra 253B
51.3
GPT-4.1 nano
9.8
Nemotron Ultra 253B
78
GPT-4.1 nano
83.2
Nemotron Ultra 253B is ahead overall, 50 to 23. The biggest single separator in this matchup is AIME 2024, where the scores are 51 and 9.8.
GPT-4.1 nano has the edge for knowledge tasks in this comparison, averaging 65.2 versus 43.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Nemotron Ultra 253B has the edge for math in this comparison, averaging 51.3 versus 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for instruction following in this comparison, averaging 83.2 versus 78. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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