Multimodal · OpenRouter

Auto Mini on MMMU: score, rank and what it means

Auto Mini scores 59.3 on MMMU, placing it #436 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
59.3
0–100 scale
Rank
#436
of 600
Percentile
27th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
27.6
points

Score distribution

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

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Auto Mini sits at #436 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 27.6 points. The median model in this index scores 70.0, which puts Auto Mini below the midpoint.

OpenRouter models average 66.0 on this benchmark. Auto Mini is 6.7 points below that provider line, so it is a weaker result than the average OpenRouter model.

Among mid-range models, the average is 65.0. Auto Mini is 5.7 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 59.3 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 MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
GLM-4.5 7B Zhipu AI 8192 $1.32 60.2
Embed 4 Turbo Cohere 4096 $5.13 64.0
Llama 3.1 8B Meta AI 8192 $1.15 58.7
SmolLM3 Base Hugging Face 16384 $1.38 60.4
Auto Mini OpenRouter 4096 $4.24 61.6
Kimi K2 7B Moonshot AI 16384 $1.72 62.7
Sonar Nano Perplexity 4096 $4.37 61.9

Other benchmarks for Auto Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 68.8 407 32th
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
Arena Elo 1290.3 431 28th

FAQ

What score does Auto Mini get on MMMU?

Auto Mini scores 59.3 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Auto Mini rank on MMMU?

It ranks #436 of 600 models, in the 27th percentile. The leader is GPT-5.2 Max at 86.9.

Is Auto Mini good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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.

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