Commonsense · OpenRouter

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

Auto Max scores 83.5 on HellaSwag, placing it #302 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
83.5
0–100 scale
Rank
#302
of 600
Percentile
50th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
12.6
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Auto Max 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 Max sits at #302 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 12.6 points. The median model in this index scores 83.6, which puts Auto Max below the midpoint.

OpenRouter models average 80.2 on this benchmark. Auto Max is 3.3 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 Max is 3.7 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 83.5 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 $8.41 per million input tokens, Auto Max 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
Doubao 1.5 Pro Mini ByteDance 32768 $8.30 72.3
Llama 3 DeepInfra Chat DeepInfra 200000 $3.74 75.0
Llama 4 Scout Base Meta AI 32768 $3.95 75.3
Sonar Turbo Perplexity 65536 $10.71 75.7
Auto Max OpenRouter 8192 $8.41 71.2
Fusion Pro OpenRouter 65536 $8.69 72.2
Hunyuan-Large Base Tencent 200000 $3.64 74.0

Other benchmarks for Auto Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.5 342 43th
GPQA Diamond 69.4 280 53th
SWE-bench Verified 58.7 345 43th
HumanEval 73.7 360 40th
MATH-500 72.6 361 40th
AIME 2025 68.5 287 52th
LiveCodeBench 60.0 368 39th
IFEval 78.1 366 39th
TruthfulQA 77.5 267 56th
MMMU 66.2 367 39th
Arena Elo 1365.1 331 45th

FAQ

What score does Auto Max get on HellaSwag?

Auto Max scores 83.5 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Auto Max rank on HellaSwag?

It ranks #302 of 600 models, in the 50th percentile. The leader is GPT-5.2 Max at 96.1.

Is Auto Max 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 Max cost?

Auto Max costs $8.41 per million input tokens and $40.47 per million output tokens.

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