Multimodal · Alibaba Cloud

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

Qwen3-Coder Base scores 73.4 on MMMU, placing it #208 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
73.4
0–100 scale
Rank
#208
of 600
Percentile
65th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
13.5
points

Score distribution

The chart shows the top 10 models on MMMU, with Qwen3-Coder Base 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-Coder Base sits at #208 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 13.5 points. The median model in this index scores 70.0, which puts Qwen3-Coder Base above the midpoint.

Alibaba Cloud models average 69.4 on this benchmark. Qwen3-Coder Base is 4.0 points above that provider line, so it is a stronger result than the average Alibaba Cloud model.

Among coding models, the average is 66.1. Qwen3-Coder Base is 7.3 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 73.4 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 $3.99 per million input tokens, Qwen3-Coder Base is below 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
Kimi K2 Base Moonshot AI 65536 $4.82 79.2
Llama 3.3 Groq Instruct Groq 65536 $4.08 76.7
Seed-OSS ByteDance 32768 $3.74 75.3
Llama 3.3 Chat Meta AI 32768 $4.18 76.9
Qwen3-Coder Base Alibaba Cloud 200000 $3.99 76.6
Reka Core Reka AI 32768 $12.17 77.4
MiniMax-M2 Base MiniMax 65536 $4.20 76.4

Other benchmarks for Qwen3-Coder Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.3 235 61th
GPQA Diamond 72.2 216 64th
SWE-bench Verified 64.0 232 61th
HumanEval 78.5 282 53th
MATH-500 82.4 156 74th
AIME 2025 73.7 193 68th
LiveCodeBench 68.0 227 62th
IFEval 85.7 168 72th
TruthfulQA 80.8 162 73th
HellaSwag 85.5 228 62th
Arena Elo 1409.2 185 69th

FAQ

What score does Qwen3-Coder Base get on MMMU?

Qwen3-Coder Base scores 73.4 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Qwen3-Coder Base rank on MMMU?

It ranks #208 of 600 models, in the 65th percentile. The leader is GPT-5.2 Max at 86.9.

Is Qwen3-Coder Base 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-Coder Base cost?

Qwen3-Coder Base costs $3.99 per million input tokens and $18.04 per million output tokens.

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