Mathematics · OpenAI

o4 Nano on MATH-500: score, rank and what it means

o4 Nano scores 74.0 on MATH-500, placing it #349 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
74.0
0–100 scale
Rank
#349
of 600
Percentile
42th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
22.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with o4 Nano 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, o4 Nano sits at #349 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 22.7 points. The median model in this index scores 76.0, which puts o4 Nano below the midpoint.

OpenAI models average 87.5 on this benchmark. o4 Nano is 13.5 points below that provider line, so it is a weaker result than the average OpenAI model.

Among mid-range models, the average is 70.0. o4 Nano is 4.0 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 74.0 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 $8.61 per million input tokens, o4 Nano 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
Fusion Pro OpenRouter 65536 $8.69 72.2
Fusion OpenRouter 16384 $8.41 71.1
Mixtral Turbo Base Together AI 32768 $2.53 69.7
Mixtral Turbo Chat Together AI 32768 $3.02 71.7
o4 Nano OpenAI 65536 $8.61 72.0
Doubao 1.5 Pro Mini ByteDance 32768 $8.30 72.3
Claude Haiku 4.5 Mini Anthropic 16384 $8.76 71.6

Other benchmarks for o4 Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.9 339 44th
GPQA Diamond 67.3 327 46th
SWE-bench Verified 62.3 272 55th
HumanEval 74.7 350 42th
AIME 2025 64.2 354 41th
LiveCodeBench 65.9 278 54th
IFEval 81.6 286 52th
TruthfulQA 75.2 327 46th
HellaSwag 81.2 363 40th
MMMU 70.2 296 51th
Arena Elo 1374.8 294 51th

FAQ

What score does o4 Nano get on MATH-500?

o4 Nano scores 74.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does o4 Nano rank on MATH-500?

It ranks #349 of 600 models, in the 42nd percentile. The leader is GPT-5.2 Max at 96.7.

Is o4 Nano good at MATH-500?

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 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 o4 Nano cost?

o4 Nano costs $8.61 per million input tokens and $41.97 per million output tokens.

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