Knowledge · Alibaba Cloud

Qwen3-Coder on MMLU-Pro: score, rank and what it means

Qwen3-Coder scores 83.7 on MMLU-Pro, placing it #89 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
83.7
0–100 scale
Rank
#89
of 600
Percentile
85th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
7.9
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Qwen3-Coder highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Qwen3-Coder sits at #89 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 7.9 points. The median model in this index scores 76.1, which puts Qwen3-Coder above the midpoint.

Alibaba Cloud models average 75.9 on this benchmark. Qwen3-Coder is 7.8 points above that provider line, so it is a stronger result than the average Alibaba Cloud model.

Among coding models, the average is 72.5. Qwen3-Coder is 11.2 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 83.7 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 $4.94 per million input tokens, Qwen3-Coder is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DeepSeek-R1 DeepSeek 128000 $5.83 82.8
ERNIE 4.5 Baidu 65536 $13.44 80.0
Gemini 3 Flash Google DeepMind 128000 $15.67 83.6
Grok 3 Turbo xAI 128000 $15.97 83.1
Qwen3-Coder Alibaba Cloud 200000 $4.94 79.5
Sonar Pro Max Perplexity 128000 $14.01 81.1
Gemini 2.5 Pro Google DeepMind 200000 $15.20 81.6

Other benchmarks for Qwen3-Coder

BenchmarkScoreRankPercentileRelative
GPQA Diamond 77.9 88 85th
SWE-bench Verified 71.0 96 84th
HumanEval 83.5 146 76th
MATH-500 86.1 92 85th
AIME 2025 74.2 175 71th
LiveCodeBench 69.8 196 67th
IFEval 86.6 144 76th
TruthfulQA 79.8 192 68th
HellaSwag 86.7 188 69th
MMMU 75.2 159 74th
Arena Elo 1439.3 98 84th

FAQ

What score does Qwen3-Coder get on MMLU-Pro?

Qwen3-Coder scores 83.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Qwen3-Coder rank on MMLU-Pro?

It ranks #89 of 600 models, in the 85th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Qwen3-Coder good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 cost?

Qwen3-Coder costs $4.94 per million input tokens and $19.51 per million output tokens.

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