DeepSeek-R1 vs NVIDIA Nemotron Nano 9B V2
Wins 4 of 6 areas
Coding · Reasoning · Long documents · Following instructions
Wins 0 of 6 areas
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DeepSeek-R1 is the stronger all-rounder.NVIDIA Nemotron Nano 9B V2 is cheaper.
Scores updated · 18 tests both models report · How we compare
Where each one wins
Tests won in each of the six areas 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.
- ReasoningHard problems that need careful thinking20DeepSeek-R12 of 3 tests · 1 tie
- CodingWriting and fixing software20DeepSeek-R12 of 2 tests
- Long documentsFinding answers in very long texts10DeepSeek-R11 of 1 test
- Following instructionsDoing exactly what it is asked10DeepSeek-R11 of 1 test
- AgentsCarrying out multi-step tasks on its own00Even0 each · 1 tie
- FactsGetting facts right instead of making them up11Even1 each
Agents, long documents and following instructions rest on a single test each.
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.
NVIDIA Nemotron Nano 9B V2 costs 97% less for the same work.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where DeepSeek-R1 pulls ahead
- Reasons across sets of long documentsAA-LCR+35points ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+18.7points ahead
- Code for real scientific research problemsSciCode+16.3points ahead
Where NVIDIA Nemotron Nano 9B V2 pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+29.8points ahead
Every test, side by side
All 18 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingDeepSeek-R1
- SciCodeDeepSeek-R1 by 16.338.322+16.3
- Terminal-Bench HardDeepSeek-R1 by 4.66.11.5+4.6
ReasoningDeepSeek-R1
- GPQA DiamondDeepSeek-R1 by 13.870.857+13.8
- Humanity's Last ExamDeepSeek-R1 by 3.68.54.9+3.6
- CritPttie0.60tie
FactsEven
- AA-Omniscience · Non-hallucinationNVIDIA Nemotron Nano 9B V2 by 29.89.739.5+29.8
- AA-Omniscience · AccuracyDeepSeek-R1 by 18.730.511.8+18.7
Following instructionsDeepSeek-R1
- IFBenchDeepSeek-R1 by 11.43927.6+11.4
Other results8 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.
- Artificial Analysis Coding IndexDeepSeek-R1 by 16.324.68.3+16.3
- τ²-Bench Telecom (AA run)NVIDIA Nemotron Nano 9B V2 by 10.511.421.9+10.5
- AA-OmniscienceDeepSeek-R1 by 9.3-32.2-41.5+9.3
- LiveCodeBenchNVIDIA Nemotron Nano 9B V2 by 7.663.571.1+7.6
- IFEvalNVIDIA Nemotron Nano 9B V2 by 783.390.3+7
- AA IntelligenceDeepSeek-R1 by 411.47.4+4
- AIME 2025NVIDIA Nemotron Nano 9B V2 by 2.17072.1+2.1
- MATH-500 (EM)tie97.397.8tie
Questions people ask
Which is better, DeepSeek-R1 or NVIDIA Nemotron Nano 9B V2?
DeepSeek-R1 wins four of the six areas where both have results: coding, reasoning, long documents and following instructions. NVIDIA Nemotron Nano 9B V2 wins none, but costs 97% less. They are level on agents and facts.
Which is better for coding?
DeepSeek-R1. It wins 2 of the 2 coding tests both models report; NVIDIA Nemotron Nano 9B V2 wins none.
Which is cheaper?
DeepSeek-R1 costs $2.00 per million input tokens and $4.00 per million output tokens; NVIDIA Nemotron Nano 9B V2 costs $0.04 and $0.16. That makes NVIDIA Nemotron Nano 9B V2 about 97% cheaper for the same work.
How do you compare the two?
We use the 18 benchmark tests both models have published scores on. The verdict counts the 10 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 8 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.