Multimodal · Alibaba Cloud

Qwen3-Max Max on MMMU: score, rank and what it means

Qwen3-Max Max scores 78.9 on MMMU, placing it #76 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
78.9
0–100 scale
Rank
#76
of 600
Percentile
87th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
8.0
points

Score distribution

The chart shows the top 10 models on MMMU, with Qwen3-Max Max 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, Qwen3-Max Max sits at #76 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 8.0 points. The median model in this index scores 70.0, which puts Qwen3-Max Max above the midpoint.

Alibaba Cloud models average 69.4 on this benchmark. Qwen3-Max Max is 9.5 points above that provider line, so it is a stronger result than the average Alibaba Cloud model.

Among frontier models, the average is 81.6. Qwen3-Max Max 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 78.9 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 $18.53 per million input tokens, Qwen3-Max Max 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
Doubao 1.5 Pro ByteDance 200000 $13.65 79.7
Llama 4 Maverick Instruct Meta AI 200000 $5.33 81.7
GLM-4.6 Instruct Zhipu AI 1000000 $5.15 80.4
Grok 3 Pro xAI 400000 $16.61 83.8
Qwen3-Max Max Alibaba Cloud 400000 $18.53 85.9
Sonar Pro Pro Perplexity 200000 $13.59 79.7
Claude 3.7 Sonnet Max Anthropic 128000 $16.88 83.7

Other benchmarks for Qwen3-Max Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 85.2 62 90th
GPQA Diamond 83.8 14 98th
SWE-bench Verified 74.3 49 92th
HumanEval 90.2 44 93th
MATH-500 92.8 14 98th
AIME 2025 82.7 58 90th
LiveCodeBench 82.8 16 97th
IFEval 93.7 15 98th
TruthfulQA 89.3 8 99th
HellaSwag 91.4 51 92th
Arena Elo 1467.7 38 94th

FAQ

What score does Qwen3-Max Max get on MMMU?

Qwen3-Max Max scores 78.9 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Qwen3-Max Max rank on MMMU?

It ranks #76 of 600 models, in the 87th percentile. The leader is GPT-5.2 Max at 86.9.

Is Qwen3-Max Max good at MMMU?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Qwen3-Max Max cost?

Qwen3-Max Max costs $18.53 per million input tokens and $74.05 per million output tokens.

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