Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4.1 is clearly ahead on the aggregate, 65 to 61. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in multimodal & grounded, where it averages 73.6 against 60.4. The single biggest benchmark swing on the page is AIME 2024, 26.4 to 69. Nemotron 3 Super 120B A12B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Nemotron 3 Super 120B A12B. That is roughly Infinityx on output cost alone. GPT-4.1 gives you the larger context window at 1M, compared with 256K for Nemotron 3 Super 120B A12B.
Pick GPT-4.1 if you want the stronger benchmark profile. Nemotron 3 Super 120B A12B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
GPT-4.1
64.7
Nemotron 3 Super 120B A12B
55.3
GPT-4.1
51.7
Nemotron 3 Super 120B A12B
44.2
GPT-4.1
73.6
Nemotron 3 Super 120B A12B
60.4
GPT-4.1
80.9
Nemotron 3 Super 120B A12B
71.8
GPT-4.1
63.3
Nemotron 3 Super 120B A12B
55.8
GPT-4.1
87.4
Nemotron 3 Super 120B A12B
86
GPT-4.1
69
Nemotron 3 Super 120B A12B
81.5
GPT-4.1
26.4
Nemotron 3 Super 120B A12B
74.6
GPT-4.1 is ahead overall, 65 to 61. The biggest single separator in this matchup is AIME 2024, where the scores are 26.4 and 69.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 63.3 versus 55.8. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for coding in this comparison, averaging 51.7 versus 44.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Nemotron 3 Super 120B A12B has the edge for math in this comparison, averaging 74.6 versus 26.4. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for reasoning in this comparison, averaging 80.9 versus 71.8. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for agentic tasks in this comparison, averaging 64.7 versus 55.3. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for multimodal and grounded tasks in this comparison, averaging 73.6 versus 60.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 86. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Nemotron 3 Super 120B A12B has the edge for multilingual tasks in this comparison, averaging 81.5 versus 69. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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