Reasoning · NVIDIA

Nemotron Nano Base on GPQA Diamond: score, rank and what it means

Nemotron Nano Base scores 57.8 on GPQA Diamond, placing it #430 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
57.8
0–100 scale
Rank
#430
of 600
Percentile
28th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
29.2
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Nemotron Nano Base highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Nemotron Nano Base sits at #430 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 29.2 points. The median model in this index scores 68.8, which puts Nemotron Nano Base below the midpoint.

NVIDIA models average 57.5 on this benchmark. Nemotron Nano Base is 0.3 points above that provider line, so it is a stronger result than the average NVIDIA model.

Among open-weight models, the average is 63.6. Nemotron Nano Base is 5.8 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 57.8 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $1.85 per million input tokens, Nemotron Nano Base is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DeepSeek-R1 8B DeepSeek 16384 $1.87 64.3
GLM-4.6 7B Zhipu AI 16384 $1.52 61.8
GPT-NeoX Chat EleutherAI 16384 $1.49 60.1
StableLM 2 Stability AI 8192 $1.91 65.0
Nemotron Nano Base NVIDIA 8192 $1.85 65.0
DeepSeek-R1 7B DeepSeek 32768 $1.79 63.0
Magistral 7B Mistral AI 32768 $1.22 58.9

Other benchmarks for Nemotron Nano Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 68.0 418 30th
SWE-bench Verified 53.3 395 34th
HumanEval 68.0 415 31th
MATH-500 68.4 396 34th
AIME 2025 59.9 388 35th
LiveCodeBench 53.8 413 31th
IFEval 75.7 392 35th
TruthfulQA 68.8 407 32th
HellaSwag 79.5 388 35th
MMMU 62.2 407 32th
Arena Elo 1318.8 397 34th

FAQ

What score does Nemotron Nano Base get on GPQA Diamond?

Nemotron Nano Base scores 57.8 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Nemotron Nano Base rank on GPQA Diamond?

It ranks #430 of 600 models, in the 28th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Nemotron Nano Base good at GPQA Diamond?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the GPQA Diamond score calculated?

GPQA Diamond is a reasoning benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Nemotron Nano Base cost?

Nemotron Nano Base costs $1.85 per million input tokens and $8.64 per million output tokens.

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