Mathematics · NVIDIA

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

Nemotron 4 Chat scores 82.2 on MATH-500, placing it #160 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
82.2
0–100 scale
Rank
#160
of 600
Percentile
73th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
14.5
points

Score distribution

The chart shows the top 10 models on MATH-500, with Nemotron 4 Chat 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 Chat sits at #160 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 14.5 points. The median model in this index scores 76.0, which puts Nemotron 4 Chat above the midpoint.

NVIDIA models average 63.9 on this benchmark. Nemotron 4 Chat is 18.3 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 Chat is 0.9 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 82.2 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 $3.99 per million input tokens, Nemotron 4 Chat is below 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
Qwen3-Coder Base Alibaba Cloud 200000 $3.99 76.6
MiniMax-M2 MiniMax 200000 $5.19 80.6
Sonar Pro Perplexity 65536 $11.25 77.1
Command R+ Instruct Cohere 200000 $4.16 76.2
Nemotron 4 Chat NVIDIA 65536 $3.99 75.0
Codestral Mistral AI 65536 $4.19 77.6
ERNIE 4.0 Baidu 32768 $11.37 76.7

Other benchmarks for Nemotron 4 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.2 271 55th
GPQA Diamond 69.4 283 53th
SWE-bench Verified 62.3 271 55th
HumanEval 78.6 277 54th
AIME 2025 73.0 203 66th
LiveCodeBench 65.9 276 54th
IFEval 81.8 281 53th
TruthfulQA 79.2 210 65th
HellaSwag 84.4 268 55th
MMMU 71.1 271 55th
Arena Elo 1398.2 212 65th

FAQ

What score does Nemotron 4 Chat get on MATH-500?

Nemotron 4 Chat scores 82.2 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Nemotron 4 Chat rank on MATH-500?

It ranks #160 of 600 models, in the 73rd percentile. The leader is GPT-5.2 Max at 96.7.

Is Nemotron 4 Chat 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 Chat cost?

Nemotron 4 Chat costs $3.99 per million input tokens and $16.11 per million output tokens.

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