Knowledge · NVIDIA

Nemotron Nano 8B on MMLU-Pro: score, rank and what it means

Nemotron Nano 8B scores 53.5 on MMLU-Pro, placing it #580 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
53.5
0–100 scale
Rank
#580
of 600
Percentile
3th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
38.1
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Nemotron Nano 8B 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 8B sits at #580 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 38.1 points. The median model in this index scores 76.1, which puts Nemotron Nano 8B below the midpoint.

NVIDIA models average 67.0 on this benchmark. Nemotron Nano 8B is 13.5 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 8B is 6.3 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 53.5 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 $0.46 per million input tokens, Nemotron Nano 8B 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
Gemma 3 1.5B Google DeepMind 32768 $0.40 48.9
SmolLM3 7B Hugging Face 16384 $0.19 44.3
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1
DBRX 1.5B Databricks 16384 $0.32 47.0
Zephyr 7B Hugging Face 32768 $0.23 42.5

Other benchmarks for Nemotron Nano 8B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 41.5 581 3th
SWE-bench Verified 31.1 575 4th
HumanEval 51.2 565 6th
MATH-500 50.2 554 8th
AIME 2025 35.2 567 6th
LiveCodeBench 37.0 556 7th
IFEval 58.7 580 3th
TruthfulQA 55.7 569 5th
HellaSwag 68.7 551 8th
MMMU 46.2 579 4th
Arena Elo 1192.6 563 6th

FAQ

What score does Nemotron Nano 8B get on MMLU-Pro?

Nemotron Nano 8B scores 53.5 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Nemotron Nano 8B rank on MMLU-Pro?

It ranks #580 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Pro at 91.6.

Is Nemotron Nano 8B 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 8B cost?

Nemotron Nano 8B costs $0.46 per million input tokens and $1.64 per million output tokens.

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