Mathematics · OpenAI

GPT-5.2 Nano on MATH-500: score, rank and what it means

GPT-5.2 Nano scores 74.8 on MATH-500, placing it #332 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
74.8
0–100 scale
Rank
#332
of 600
Percentile
45th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
21.9
points

Score distribution

The chart shows the top 10 models on MATH-500, with GPT-5.2 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, GPT-5.2 Nano sits at #332 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 21.9 points. The median model in this index scores 76.0, which puts GPT-5.2 Nano below the midpoint.

OpenAI models average 87.5 on this benchmark. GPT-5.2 Nano is 12.7 points below that provider line, so it is a weaker result than the average OpenAI model.

Among multimodal models, the average is 81.3. GPT-5.2 Nano is 6.5 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 74.8 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 $9.73 per million input tokens, GPT-5.2 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
Grok 4 Nano xAI 16384 $8.97 72.7
Mixtral Groq Groq 16384 $3.37 73.1
Phi-4 Chat Microsoft 65536 $3.66 74.7
Reka Flash Reka AI 128000 $9.95 74.1
GPT-5.2 Nano OpenAI 128000 $9.73 73.5
Sonar Pro Mini Perplexity 8192 $8.02 70.3
Mixtral Groq Chat Groq 8192 $3.09 72.0

Other benchmarks for GPT-5.2 Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.4 320 47th
GPQA Diamond 68.4 306 49th
SWE-bench Verified 62.4 268 55th
HumanEval 79.7 241 60th
AIME 2025 72.0 218 64th
LiveCodeBench 64.2 311 48th
IFEval 80.4 322 46th
TruthfulQA 78.2 249 59th
HellaSwag 82.7 328 45th
MMMU 70.7 279 54th
Arena Elo 1389.1 252 58th

FAQ

What score does GPT-5.2 Nano get on MATH-500?

GPT-5.2 Nano scores 74.8 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does GPT-5.2 Nano rank on MATH-500?

It ranks #332 of 600 models, in the 45th percentile. The leader is GPT-5.2 Max at 96.7.

Is GPT-5.2 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 GPT-5.2 Nano cost?

GPT-5.2 Nano costs $9.73 per million input tokens and $49.56 per million output tokens.

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