Multimodal · OpenRouter

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

Auto Turbo scores 70.0 on MMMU, placing it #301 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
70.0
0–100 scale
Rank
#301
of 600
Percentile
50th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
16.9
points

Score distribution

The chart shows the top 10 models on MMMU, with Auto Turbo 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 Turbo sits at #301 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 16.9 points. The median model in this index scores 70.0, which puts Auto Turbo below the midpoint.

OpenRouter models average 66.0 on this benchmark. Auto Turbo is 4.0 points above that provider line, so it is a stronger result than the average OpenRouter model.

Among mid-range models, the average is 65.0. Auto Turbo is 5.0 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 70.0 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 $7.96 per million input tokens, Auto Turbo 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
Claude Sonnet 4.5 Nano Anthropic 8192 $8.93 72.0
Llama 3.1 Cerebras Cerebras 128000 $4.01 76.0
MiniMax-Text Base MiniMax 128000 $3.66 74.9
Sonar Perplexity 200000 $10.57 76.0
Auto Turbo OpenRouter 65536 $7.96 70.9
Codestral Instruct Mistral AI 65536 $4.01 75.1
Llama 3 Lambda Instruct Lambda 32768 $3.92 75.8

Other benchmarks for Auto Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.0 305 49th
GPQA Diamond 69.1 291 52th
SWE-bench Verified 57.1 365 39th
HumanEval 75.7 332 45th
MATH-500 71.2 377 37th
AIME 2025 64.8 340 43th
LiveCodeBench 60.2 366 39th
IFEval 80.7 318 47th
TruthfulQA 71.7 383 36th
HellaSwag 83.9 283 53th
Arena Elo 1345.5 371 38th

FAQ

What score does Auto Turbo get on MMMU?

Auto Turbo scores 70.0 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Auto Turbo rank on MMMU?

It ranks #301 of 600 models, in the 50th percentile. The leader is GPT-5.2 Max at 86.9.

Is Auto Turbo 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 Turbo cost?

Auto Turbo costs $7.96 per million input tokens and $33.26 per million output tokens.

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