Commonsense · OpenAI

GPT-4.1 Nano on HellaSwag: score, rank and what it means

GPT-4.1 Nano scores 82.5 on HellaSwag, placing it #334 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
82.5
0–100 scale
Rank
#334
of 600
Percentile
44th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
13.6
points

Score distribution

The chart shows the top 10 models on HellaSwag, with GPT-4.1 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, GPT-4.1 Nano sits at #334 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 13.6 points. The median model in this index scores 83.6, which puts GPT-4.1 Nano below the midpoint.

OpenAI models average 90.5 on this benchmark. GPT-4.1 Nano is 8.0 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. GPT-4.1 Nano is 2.7 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 82.5 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 $7.42 per million input tokens, GPT-4.1 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
Nova Lite Amazon 65536 $9.20 73.4
Fusion Max OpenRouter 65536 $9.14 72.5
Llama 3.1 Cerebras Base Cerebras 65536 $3.36 72.7
Mistral Small 3 Chat Mistral AI 200000 $3.54 73.7
GPT-4.1 Nano OpenAI 32768 $7.42 70.5
Mixtral Turbo Together AI 65536 $3.20 72.4
Mixtral Turbo Instruct Together AI 32768 $3.16 71.9

Other benchmarks for GPT-4.1 Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.0 352 41th
GPQA Diamond 65.8 345 43th
SWE-bench Verified 59.7 332 45th
HumanEval 72.0 379 37th
MATH-500 75.3 319 47th
AIME 2025 59.5 390 35th
LiveCodeBench 64.3 310 48th
IFEval 80.3 328 45th
TruthfulQA 75.3 325 46th
MMMU 66.6 363 40th
Arena Elo 1352.6 360 40th

FAQ

What score does GPT-4.1 Nano get on HellaSwag?

GPT-4.1 Nano scores 82.5 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does GPT-4.1 Nano rank on HellaSwag?

It ranks #334 of 600 models, in the 44th percentile. The leader is GPT-5.2 Max at 96.1.

Is GPT-4.1 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 GPT-4.1 Nano cost?

GPT-4.1 Nano costs $7.42 per million input tokens and $32.36 per million output tokens.

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