Commonsense · OpenRouter

Auto on HellaSwag: score, rank and what it means

Auto scores 81.1 on HellaSwag, placing it #364 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
81.1
0–100 scale
Rank
#364
of 600
Percentile
39th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
15.0
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Auto 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, Auto sits at #364 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 15.0 points. The median model in this index scores 83.6, which puts Auto below the midpoint.

OpenRouter models average 80.2 on this benchmark. Auto is 0.9 points above that provider line, so it is a stronger result than the average OpenRouter model.

Among mid-range models, the average is 79.8. Auto is 1.3 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 81.1 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 $7.53 per million input tokens, Auto 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
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
Firesearch Max Fireworks AI 8192 $7.80 69.9

Other benchmarks for Auto

BenchmarkScoreRankPercentileRelative
MMLU-Pro 73.6 362 40th
GPQA Diamond 63.9 378 37th
SWE-bench Verified 58.1 355 41th
HumanEval 75.2 340 43th
MATH-500 74.1 343 43th
AIME 2025 67.0 313 48th
LiveCodeBench 59.0 378 37th
IFEval 77.3 375 38th
TruthfulQA 73.8 357 41th
MMMU 69.6 314 48th
Arena Elo 1341.2 378 37th

FAQ

What score does Auto get on HellaSwag?

Auto scores 81.1 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Auto rank on HellaSwag?

It ranks #364 of 600 models, in the 39th percentile. The leader is GPT-5.2 Max at 96.1.

Is Auto 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 Auto cost?

Auto costs $7.53 per million input tokens and $29.19 per million output tokens.

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