Noometry

Model comparison

DeepSeek-V3.1 vs Nemotron 3 Super

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 39.6 on the Noometry Index. Nemotron 3 Super costs 2.5× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

Last verified . 16 shared benchmarks.

DeepSeek-V3.1 DeepSeek

42.2

Rank #106 Confirmed

Nemotron 3 Super NVIDIA

39.6

Rank #147 Confirmed

Summary

  • They share 16 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 6 categories and Nemotron 3 Super in 2 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where DeepSeek-V3.1 leads 27.3 to 17.9.
  • Nemotron 3 Super is cheaper at $0.08 / $0.45 per million input/output tokens, against $0.25 / $0.95 for DeepSeek-V3.1.
  • Nemotron 3 Super accepts more context: 262K tokens versus 164K.

Side by side

DeepSeek-V3.1Nemotron 3 Super
ProviderDeepSeekNVIDIA
Noometry Index42.239.6
Released2025-08-212026-03-11
WeightsOpenOpen
Context window164K262K
Max output8K131K
Input $ / M tokens$0.25$0.08
Output $ / M tokens$0.95$0.45
Results tracked2721

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Category by category

Coding Too close to call

DeepSeek-V3.1: 39.8 (#140), Nemotron 3 Super: 38.9 (#153)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
WeirdML38.4%38%
LMArena Coding14171403
SciCode—36%
ALE-Bench—213.9

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.3 (#109), Nemotron 3 Super: 17.9 (#274)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
LMArena Hard Prompts14171386
SimpleBench40%—
Kagi LLM Benchmark53.2%—
NYT Connections (extended)—15.4%
CritPt—3.1%
DTBench82.7%—
LMCA24.3%—
Epoch Capabilities Index139.92—
ForecastBench58—

Math Nemotron 3 Super leads

DeepSeek-V3.1: 36.1 (#125), Nemotron 3 Super: 37.6 (#95)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
LMArena Math14201381
MathArena Final-Answer Competitions—60.4%

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.0 (#86), Nemotron 3 Super: 38.2 (#136)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
LMArena Expert14031397
Vectara Hallucination Rate5.5%—

Multilingual DeepSeek-V3.1 leads

DeepSeek-V3.1: 51.8 (#100), Nemotron 3 Super: 48.6 (#139)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
LMArena Non-English14001356
LMArena Chinese14701430
LMArena French14471404
LMArena German14121341
LMArena Russian14051336
LMArena Spanish14291417
LMArena Japanese1374—
LMArena Korean1337—

Instruction Following DeepSeek-V3.1 leads

DeepSeek-V3.1: 74.1 (#105), Nemotron 3 Super: 71.4 (#149)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
LMArena Instruction Following14001347

Long Context Nemotron 3 Super leads

DeepSeek-V3.1: 36.3 (#227), Nemotron 3 Super: 41.5 (#134)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
LMArena Longer Query14221362
Fiction.LiveBench52.8%—

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.5 (#93), Nemotron 3 Super: 56.1 (#135)

BenchmarkDeepSeek-V3.1Nemotron 3 Super
LMArena Text14201378
LMArena Creative Writing14011317
LMArena Multi-Turn14081369
EQ-Bench Creative Writing1436—

Frequently asked questions

Is DeepSeek-V3.1 better than Nemotron 3 Super?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 39.6 on the Noometry Index. Nemotron 3 Super costs 2.5× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

Which is cheaper, DeepSeek-V3.1 or Nemotron 3 Super?

Nemotron 3 Super is cheaper. It lists at $0.08 per million input tokens and $0.45 per million output tokens; DeepSeek-V3.1 lists at $0.25 and $0.95.

Is DeepSeek-V3.1 or Nemotron 3 Super better for coding?

They score almost the same on coding (39.8 vs 38.9); test both on your own repository before choosing.

Which has the bigger context window?

Nemotron 3 Super does, with 262K tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and Nemotron 3 Super share?

16 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Nemotron 3 Super has 21.

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