Knowledge · OpenRouter

Auto Mini on MMLU-Pro: score, rank and what it means

Auto Mini scores 68.8 on MMLU-Pro, placing it #407 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
68.8
0–100 scale
Rank
#407
of 600
Percentile
32th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
22.8
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Auto Mini highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Auto Mini sits at #407 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 22.8 points. The median model in this index scores 76.1, which puts Auto Mini below the midpoint.

OpenRouter models average 72.7 on this benchmark. Auto Mini is 3.9 points below that provider line, so it is a weaker result than the average OpenRouter model.

Among mid-range models, the average is 71.5. Auto Mini is 2.7 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 68.8 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 $4.24 per million input tokens, Auto Mini is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Firefunction Mini Fireworks AI 32768 $4.63 63.2
Embed 4 Pro Cohere 4096 $5.05 63.5
SmolLM3 Hugging Face 8192 $1.71 63.1
GLM-4.6 8B Zhipu AI 8192 $1.69 63.1
Auto Mini OpenRouter 4096 $4.24 61.6
Zephyr Hugging Face 8192 $1.61 62.8
SmolLM3 Chat Hugging Face 16384 $1.61 62.1

Other benchmarks for Auto Mini

BenchmarkScoreRankPercentileRelative
GPQA Diamond 55.8 451 25th
SWE-bench Verified 48.8 431 28th
HumanEval 66.1 428 29th
MATH-500 62.1 442 26th
AIME 2025 49.8 462 23th
LiveCodeBench 53.1 417 31th
IFEval 72.4 426 29th
TruthfulQA 67.0 429 29th
HellaSwag 74.7 446 26th
MMMU 59.3 436 27th
Arena Elo 1290.3 431 28th

FAQ

What score does Auto Mini get on MMLU-Pro?

Auto Mini scores 68.8 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Auto Mini rank on MMLU-Pro?

It ranks #407 of 600 models, in the 32nd percentile. The leader is GPT-5.2 Pro at 91.6.

Is Auto Mini good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 Mini cost?

Auto Mini costs $4.24 per million input tokens and $18.05 per million output tokens.

Related