Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.2 (Thinking) is clearly ahead on the aggregate, 70 to 61. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V3.2 (Thinking)'s sharpest advantage is in agentic, where it averages 69.4 against 55.3. The single biggest benchmark swing on the page is HumanEval, 79 to 59. Nemotron 3 Super 120B A12B does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
DeepSeek V3.2 (Thinking) is the reasoning model in the pair, while Nemotron 3 Super 120B A12B 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 120B A12B gives you the larger context window at 256K, compared with 128K for DeepSeek V3.2 (Thinking).
Pick DeepSeek V3.2 (Thinking) if you want the stronger benchmark profile. Nemotron 3 Super 120B A12B only becomes the better choice if instruction following is the priority or you need the larger 256K context window.
DeepSeek V3.2 (Thinking)
69.4
Nemotron 3 Super 120B A12B
55.3
DeepSeek V3.2 (Thinking)
51.2
Nemotron 3 Super 120B A12B
44.2
DeepSeek V3.2 (Thinking)
71
Nemotron 3 Super 120B A12B
60.4
DeepSeek V3.2 (Thinking)
80.6
Nemotron 3 Super 120B A12B
71.8
DeepSeek V3.2 (Thinking)
64.4
Nemotron 3 Super 120B A12B
55.8
DeepSeek V3.2 (Thinking)
85
Nemotron 3 Super 120B A12B
86
DeepSeek V3.2 (Thinking)
80.8
Nemotron 3 Super 120B A12B
81.5
DeepSeek V3.2 (Thinking)
85.1
Nemotron 3 Super 120B A12B
74.6
DeepSeek V3.2 (Thinking) is ahead overall, 70 to 61. The biggest single separator in this matchup is HumanEval, where the scores are 79 and 59.
DeepSeek V3.2 (Thinking) has the edge for knowledge tasks in this comparison, averaging 64.4 versus 55.8. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for coding in this comparison, averaging 51.2 versus 44.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for math in this comparison, averaging 85.1 versus 74.6. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for reasoning in this comparison, averaging 80.6 versus 71.8. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for agentic tasks in this comparison, averaging 69.4 versus 55.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
DeepSeek V3.2 (Thinking) has the edge for multimodal and grounded tasks in this comparison, averaging 71 versus 60.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Nemotron 3 Super 120B A12B has the edge for instruction following in this comparison, averaging 86 versus 85. 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 80.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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