Mathematics · NVIDIA

Nemotron 4 Instruct on MATH-500: score, rank and what it means

Nemotron 4 Instruct scores 77.9 on MATH-500, placing it #260 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
77.9
0–100 scale
Rank
#260
of 600
Percentile
57th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
18.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with Nemotron 4 Instruct highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Nemotron 4 Instruct sits at #260 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 18.8 points. The median model in this index scores 76.0, which puts Nemotron 4 Instruct above the midpoint.

NVIDIA models average 63.9 on this benchmark. Nemotron 4 Instruct is 14.0 points above that provider line, so it is a stronger result than the average NVIDIA model.

Among multimodal models, the average is 81.3. Nemotron 4 Instruct is 3.4 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 77.9 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 $4.10 per million input tokens, Nemotron 4 Instruct is above the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Codestral Instruct Mistral AI 65536 $4.01 75.1
Hunyuan-Turbo Tencent 128000 $10.55 75.8
Llama 3 Baseten Baseten 128000 $3.62 74.9
GPT-4.1 Mini OpenAI 128000 $10.43 74.3
Nemotron 4 Instruct NVIDIA 65536 $4.10 76.4
Fusion Turbo OpenRouter 8192 $8.55 71.7
Nemotron 4 NVIDIA 65536 $4.18 76.6

Other benchmarks for Nemotron 4 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.3 140 77th
GPQA Diamond 74.2 162 73th
SWE-bench Verified 64.4 224 63th
HumanEval 83.3 154 74th
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 MATH-500?

Nemotron 4 Instruct scores 77.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Nemotron 4 Instruct rank on MATH-500?

It ranks #260 of 600 models, in the 57th percentile. The leader is GPT-5.2 Max at 96.7.

Is Nemotron 4 Instruct good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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.

Related