Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mercury 2 is clearly ahead on the aggregate, 65 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mercury 2's sharpest advantage is in reasoning, where it averages 80.1 against 69.5. The single biggest benchmark swing on the page is MuSR, 82 to 60. Nemotron 3 Super 100B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Mercury 2 is the reasoning model in the pair, while Nemotron 3 Super 100B 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 100B gives you the larger context window at 1M, compared with 128K for Mercury 2.
Pick Mercury 2 if you want the stronger benchmark profile. Nemotron 3 Super 100B only becomes the better choice if coding is the priority or you need the larger 1M context window.
Mercury 2
63.7
Nemotron 3 Super 100B
56.6
Mercury 2
41.1
Nemotron 3 Super 100B
41.3
Mercury 2
68.3
Nemotron 3 Super 100B
60.4
Mercury 2
80.1
Nemotron 3 Super 100B
69.5
Mercury 2
57.2
Nemotron 3 Super 100B
52.8
Mercury 2
84
Nemotron 3 Super 100B
84
Mercury 2
79.7
Nemotron 3 Super 100B
79.5
Mercury 2
80.9
Nemotron 3 Super 100B
72.6
Mercury 2 is ahead overall, 65 to 59. The biggest single separator in this matchup is MuSR, where the scores are 82 and 60.
Mercury 2 has the edge for knowledge tasks in this comparison, averaging 57.2 versus 52.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Nemotron 3 Super 100B has the edge for coding in this comparison, averaging 41.3 versus 41.1. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for math in this comparison, averaging 80.9 versus 72.6. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for reasoning in this comparison, averaging 80.1 versus 69.5. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for agentic tasks in this comparison, averaging 63.7 versus 56.6. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for multimodal and grounded tasks in this comparison, averaging 68.3 versus 60.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Mercury 2 and Nemotron 3 Super 100B are effectively tied for instruction following here, both landing at 84 on average.
Mercury 2 has the edge for multilingual tasks in this comparison, averaging 79.7 versus 79.5. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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