Knowledge · NVIDIA

Nemotron 4 Instruct on MMLU-Pro: score, rank and what it means

Nemotron 4 Instruct scores 81.3 on MMLU-Pro, placing it #140 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
81.3
0–100 scale
Rank
#140
of 600
Percentile
77th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
10.3
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Nemotron 4 Instruct 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 4 Instruct sits at #140 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 10.3 points. The median model in this index scores 76.1, which puts Nemotron 4 Instruct above the midpoint.

NVIDIA models average 67.0 on this benchmark. Nemotron 4 Instruct is 14.3 points above that provider line, so it is a stronger result than the average NVIDIA model.

Among multimodal models, the average is 80.0. Nemotron 4 Instruct is 1.3 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 81.3 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 $4.10 per million input tokens, Nemotron 4 Instruct is above 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
Qwen3-Coder Instruct Alibaba Cloud 128000 $4.66 78.1
Reka Core Reasoning Reka AI 32768 $13.11 78.5
Command A Pro Cohere 200000 $14.28 81.3
Kimi K1.5 Chat Moonshot AI 128000 $5.11 80.2
Nemotron 4 Instruct NVIDIA 65536 $4.10 76.4
Sonar Max Perplexity 32768 $11.60 77.8
Llama 3.3 Groq Instruct Groq 65536 $4.08 76.7

Other benchmarks for Nemotron 4 Instruct

BenchmarkScoreRankPercentileRelative
GPQA Diamond 74.2 162 73th
SWE-bench Verified 64.4 224 63th
HumanEval 83.3 154 74th
MATH-500 77.9 260 57th
AIME 2025 69.8 261 57th
LiveCodeBench 66.4 266 56th
IFEval 83.0 245 59th
TruthfulQA 80.7 164 73th
HellaSwag 84.9 253 58th
MMMU 74.2 181 70th
Arena Elo 1413.2 177 71th

FAQ

What score does Nemotron 4 Instruct get on MMLU-Pro?

Nemotron 4 Instruct scores 81.3 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Nemotron 4 Instruct rank on MMLU-Pro?

It ranks #140 of 600 models, in the 77th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Nemotron 4 Instruct good at MMLU-Pro?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 4 Instruct cost?

Nemotron 4 Instruct costs $4.10 per million input tokens and $14.46 per million output tokens.

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