Knowledge · NVIDIA

Nemotron Nano 7B on MMLU-Pro: score, rank and what it means

Nemotron Nano 7B scores 56.9 on MMLU-Pro, placing it #561 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
56.9
0–100 scale
Rank
#561
of 600
Percentile
7th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
34.7
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Nemotron Nano 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Nemotron Nano 7B sits at #561 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 34.7 points. The median model in this index scores 76.1, which puts Nemotron Nano 7B below the midpoint.

NVIDIA models average 67.0 on this benchmark. Nemotron Nano 7B is 10.1 points below that provider line, so it is a weaker result than the average NVIDIA model.

Among small open-weight models, the average is 59.8. Nemotron Nano 7B is 2.9 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 56.9 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 MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Molmo 7B Allen Institute for AI 32768 $0.42 49.3
Nemotron 4 1.5B NVIDIA 32768 $0.49 50.8
Llama 3 DeepInfra 1.5B DeepInfra 32768 $0.48 48.8
Llama 3 Lambda 1.5B Lambda 16384 $0.46 48.4
Nemotron Nano 7B NVIDIA 8192 $0.35 47.5
Hunyuan-Large 1.5B Tencent 8192 $0.54 50.5
Llama 3 Baseten 1.5B Baseten 4096 $0.42 48.2

Other benchmarks for Nemotron Nano 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 41.7 580 3th
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 MMLU-Pro?

Nemotron Nano 7B scores 56.9 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Nemotron Nano 7B rank on MMLU-Pro?

It ranks #561 of 600 models, in the 7th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Nemotron Nano 7B good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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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