Coding · OpenRouter

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

Auto Max scores 73.7 on HumanEval, placing it #360 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
73.7
0–100 scale
Rank
#360
of 600
Percentile
40th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
23.1
points

Score distribution

The chart shows the top 10 models on HumanEval, with Auto Max highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Auto Max sits at #360 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 23.1 points. The median model in this index scores 77.4, which puts Auto Max below the midpoint.

OpenRouter models average 73.0 on this benchmark. Auto Max is 0.7 points above that provider line, so it is a stronger result than the average OpenRouter model.

Among mid-range models, the average is 71.5. Auto Max is 2.2 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 73.7 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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Arctic Instruct Snowflake 65536 $2.83 70.6
Reka Core Mini Reka AI 8192 $7.48 70.1
Llama 3 Replicate Base Replicate 65536 $3.15 72.1
Phi-4 Base Microsoft 32768 $3.15 71.2
Auto Max OpenRouter 8192 $8.41 71.2
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0
Hunyuan-Turbo Mini Tencent 8192 $6.59 68.3

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
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
HellaSwag 83.5 302 50th
MMMU 66.2 367 39th
Arena Elo 1365.1 331 45th

FAQ

What score does Auto Max get on HumanEval?

Auto Max scores 73.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Auto Max rank on HumanEval?

It ranks #360 of 600 models, in the 40th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Auto Max good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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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