The two are evenly matched.
Scores updated · 13 tests both models report · How we compare
Where each one wins
Tests won in each of the one area where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
Reasoning rests on a single test.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
Every test, side by side
All 13 tests both models report. The winning score is in its model's colour; marks a score checked independently.
Other results12 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- OpenBookQADeepSeek-V3 by 46.695.448.8+46.6
- HumanEvalNVIDIA-Nemotron-3.5-Super-VL-120B-A12B-Base-BF16 by 16.165.281.3+16.1
- MATH-500 (EM)DeepSeek-V3 by 8.690.281.6+8.6
- MGSMNVIDIA-Nemotron-3.5-Super-VL-120B-A12B-Base-BF16 by 7.779.887.5+7.7
- SuperGPQADeepSeek-V3 by 653.747.6+6
- WinoGrandeDeepSeek-V3 by 5.884.979.1+5.8
- MMLUDeepSeek-V3 by 4.488.584.1+4.4
- GSM8KDeepSeek-V3 by 2.39491.7+2.3
- ARC-Challengetie95.396tie
- MMLU-Protie75.976.3tie
- PIQAtie84.785.1tie
- HellaSwagtie88.989tie
Questions people ask
Which is better, DeepSeek-V3 or NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-Base-BF16?
Neither wins more tests than the other in any of the one area where both have results.
How do you compare the two?
We use the 13 benchmark tests both models have published scores on. The verdict counts the 1 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 12 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.