Reasoning · NVIDIA

Nemotron Nano 7B on GPQA Diamond: score, rank and what it means

Nemotron Nano 7B scores 41.7 on GPQA Diamond, placing it #580 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
41.7
0–100 scale
Rank
#580
of 600
Percentile
3th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
45.3
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Nemotron Nano 7B 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 7B sits at #580 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 45.3 points. The median model in this index scores 68.8, which puts Nemotron Nano 7B below the midpoint.

NVIDIA models average 57.5 on this benchmark. Nemotron Nano 7B is 15.8 points below that provider line, so it is a weaker result than the average NVIDIA model.

Among small open-weight models, the average is 49.3. Nemotron Nano 7B is 7.6 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 41.7 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 $0.35 per million input tokens, Nemotron Nano 7B 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
Yi-Large 1.5B 01.AI 8192 $0.42 46.8
Llama 3 Anyscale 1.5B Anyscale 16384 $0.43 48.9
SmolLM3 7B Hugging Face 16384 $0.19 44.3
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
Nemotron Nano 7B NVIDIA 8192 $0.35 47.5
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0

Other benchmarks for Nemotron Nano 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 56.9 561 7th
SWE-bench Verified 31.0 576 4th
HumanEval 49.5 576 4th
MATH-500 48.7 570 5th
AIME 2025 31.3 580 3th
LiveCodeBench 32.3 579 4th
IFEval 60.7 569 5th
TruthfulQA 56.6 558 7th
HellaSwag 67.6 560 7th
MMMU 46.7 575 4th
Arena Elo 1180.8 575 4th

FAQ

What score does Nemotron Nano 7B get on GPQA Diamond?

Nemotron Nano 7B scores 41.7 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Nemotron Nano 7B rank on GPQA Diamond?

It ranks #580 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Nemotron Nano 7B 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 7B cost?

Nemotron Nano 7B costs $0.35 per million input tokens and $1.30 per million output tokens.

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