Multimodal · Alibaba Cloud

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

Qwen3-Max Reasoning scores 82.3 on MMMU, placing it #29 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
82.3
0–100 scale
Rank
#29
of 600
Percentile
95th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
4.6
points

Score distribution

The chart shows the top 10 models on MMMU, with Qwen3-Max Reasoning 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 Reasoning sits at #29 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 4.6 points. The median model in this index scores 70.0, which puts Qwen3-Max Reasoning above the midpoint.

Alibaba Cloud models average 69.4 on this benchmark. Qwen3-Max Reasoning is 12.9 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 Reasoning is 0.7 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 82.3 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 $18.12 per million input tokens, Qwen3-Max Reasoning 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
Gemini 2.5 Pro Reasoning Google DeepMind 128000 $16.81 83.8
Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
Grok 3 Max xAI 2000000 $17.66 85.9
Qwen3-Max Reasoning Alibaba Cloud 2000000 $18.12 85.9
o3 OpenAI 400000 $16.80 84.5
o3 Reasoning OpenAI 200000 $18.07 85.3

Other benchmarks for Qwen3-Max Reasoning

BenchmarkScoreRankPercentileRelative
MMLU-Pro 88.1 15 98th
GPQA Diamond 79.8 61 90th
SWE-bench Verified 75.3 37 94th
HumanEval 92.6 14 98th
MATH-500 93.0 11 98th
AIME 2025 83.1 54 91th
LiveCodeBench 78.0 64 89th
IFEval 92.2 36 94th
TruthfulQA 88.8 15 98th
HellaSwag 91.5 48 92th
Arena Elo 1461.0 51 92th

FAQ

What score does Qwen3-Max Reasoning get on MMMU?

Qwen3-Max Reasoning scores 82.3 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Qwen3-Max Reasoning rank on MMMU?

It ranks #29 of 600 models, in the 95th percentile. The leader is GPT-5.2 Max at 86.9.

Is Qwen3-Max Reasoning 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 Reasoning cost?

Qwen3-Max Reasoning costs $18.12 per million input tokens and $81.94 per million output tokens.

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