Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Nemotron 3 Ultra 500B is clearly ahead on the aggregate, 67 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Nemotron 3 Ultra 500B is the reasoning model in the pair, while GPT-4o mini 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 128K for GPT-4o mini.
Pick Nemotron 3 Ultra 500B if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding 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-4o mini
82
Nemotron 3 Ultra 500B
49.7
GPT-4o mini
87.2
Nemotron 3 Ultra 500B
81
GPT-4o mini
87
Nemotron 3 Ultra 500B is ahead overall, 67 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 66 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 62.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 87.2 versus 49.7. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 87 versus 81. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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