Commonsense · OpenAI

o4 Nano on HellaSwag: score, rank and what it means

o4 Nano scores 81.2 on HellaSwag, placing it #363 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
81.2
0–100 scale
Rank
#363
of 600
Percentile
40th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
14.9
points

Score distribution

The chart shows the top 10 models on HellaSwag, with o4 Nano highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, o4 Nano sits at #363 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 14.9 points. The median model in this index scores 83.6, which puts o4 Nano below the midpoint.

OpenAI models average 90.5 on this benchmark. o4 Nano is 9.3 points below that provider line, so it is a weaker result than the average OpenAI model.

Among mid-range models, the average is 79.8. o4 Nano is 1.4 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 81.2 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 $8.61 per million input tokens, o4 Nano is above the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
OLMo 2 Base Allen Institute for AI 65536 $2.39 67.4
o3 Nano OpenAI 32768 $7.78 70.6
Claude Haiku 4.5 Mini Anthropic 16384 $8.76 71.6
Firesearch Pro Fireworks AI 32768 $7.67 70.4
o4 Nano OpenAI 65536 $8.61 72.0
Auto OpenRouter 32768 $7.53 70.2
Claude 3.7 Sonnet Nano Anthropic 65536 $6.93 68.9

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
MATH-500 74.0 349 42th
AIME 2025 64.2 354 41th
LiveCodeBench 65.9 278 54th
IFEval 81.6 286 52th
TruthfulQA 75.2 327 46th
MMMU 70.2 296 51th
Arena Elo 1374.8 294 51th

FAQ

What score does o4 Nano get on HellaSwag?

o4 Nano scores 81.2 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does o4 Nano rank on HellaSwag?

It ranks #363 of 600 models, in the 40th percentile. The leader is GPT-5.2 Max at 96.1.

Is o4 Nano good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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