Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mercury 2 is clearly ahead on the aggregate, 65 to 48. 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 53.3. The single biggest benchmark swing on the page is MuSR, 82 to 45.
Mercury 2 gives you the larger context window at 128K, compared with 32K for Nemotron Ultra 253B.
Pick Mercury 2 if you want the stronger benchmark profile. Nemotron Ultra 253B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Mercury 2
63.7
Nemotron Ultra 253B
46.7
Mercury 2
41.1
Nemotron Ultra 253B
33.7
Mercury 2
68.3
Nemotron Ultra 253B
44.7
Mercury 2
80.1
Nemotron Ultra 253B
53.3
Mercury 2
57.2
Nemotron Ultra 253B
42.4
Mercury 2
84
Nemotron Ultra 253B
78
Mercury 2
79.7
Nemotron Ultra 253B
70.1
Mercury 2
80.9
Nemotron Ultra 253B
59.7
Mercury 2 is ahead overall, 65 to 48. The biggest single separator in this matchup is MuSR, where the scores are 82 and 45.
Mercury 2 has the edge for knowledge tasks in this comparison, averaging 57.2 versus 42.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for coding in this comparison, averaging 41.1 versus 33.7. 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 59.7. 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 53.3. 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 46.7. Inside this category, Terminal-Bench 2.0 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 44.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for instruction following in this comparison, averaging 84 versus 78. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for multilingual tasks in this comparison, averaging 79.7 versus 70.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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