Commonsense · OpenRouter

Auto Pro on HellaSwag: score, rank and what it means

Auto Pro scores 81.6 on HellaSwag, placing it #356 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
81.6
0–100 scale
Rank
#356
of 600
Percentile
41th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
14.5
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Auto Pro 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 Pro sits at #356 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 14.5 points. The median model in this index scores 83.6, which puts Auto Pro below the midpoint.

OpenRouter models average 80.2 on this benchmark. Auto Pro is 1.4 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 Pro is 1.8 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 81.6 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 $8.41 per million input tokens, Auto Pro 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
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
Yi-Lightning Base 01.AI 16384 $3.31 72.7
Firesearch Reasoning Fireworks AI 32768 $7.74 69.0
Sonar Mini Perplexity 65536 $6.52 67.9
Auto Pro OpenRouter 8192 $8.41 71.2
Auto Reasoning OpenRouter 65536 $8.39 71.5
Gemma 3 Base Google DeepMind 65536 $3.09 71.1

Other benchmarks for Auto Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.6 287 52th
GPQA Diamond 68.8 300 50th
SWE-bench Verified 60.5 316 47th
HumanEval 76.7 313 48th
MATH-500 71.4 375 38th
AIME 2025 65.5 335 44th
LiveCodeBench 62.7 337 44th
IFEval 80.7 317 47th
TruthfulQA 72.7 373 38th
MMMU 66.3 366 39th
Arena Elo 1356.0 353 41th

FAQ

What score does Auto Pro get on HellaSwag?

Auto Pro scores 81.6 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Auto Pro rank on HellaSwag?

It ranks #356 of 600 models, in the 41st percentile. The leader is GPT-5.2 Max at 96.1.

Is Auto Pro 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 Pro cost?

Auto Pro costs $8.41 per million input tokens and $45.80 per million output tokens.

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