Knowledge · Alibaba Cloud

Qwen3 7B on MMLU-Pro: score, rank and what it means

Qwen3 7B scores 64.2 on MMLU-Pro, placing it #466 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
64.2
0–100 scale
Rank
#466
of 600
Percentile
22th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
27.4
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Qwen3 7B 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 7B sits at #466 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 27.4 points. The median model in this index scores 76.1, which puts Qwen3 7B below the midpoint.

Alibaba Cloud models average 75.9 on this benchmark. Qwen3 7B is 11.7 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.

Among small open-weight models, the average is 59.8. Qwen3 7B is 4.4 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 64.2 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 $1.37 per million input tokens, Qwen3 7B is below 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
Llama 3.1 Cerebras 8B Cerebras 32768 $1.02 58.2
Llama 3 Modal 8B Modal 32768 $0.98 56.6
Seed-OSS 8B ByteDance 8192 $1.05 57.1
GLM-4.5 8B Zhipu AI 32768 $1.46 61.3
Qwen3 7B Alibaba Cloud 32768 $1.37 59.8
Gemma 3 8B Google DeepMind 16384 $0.96 56.5
Hunyuan-Large 8B Tencent 4096 $1.29 58.7

Other benchmarks for Qwen3 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 55.2 460 23th
SWE-bench Verified 44.7 468 22th
HumanEval 65.2 439 27th
MATH-500 60.8 453 25th
AIME 2025 49.3 464 23th
LiveCodeBench 50.3 445 26th
IFEval 68.9 478 20th
TruthfulQA 65.8 447 26th
HellaSwag 77.0 416 31th
MMMU 56.4 481 20th
Arena Elo 1283.5 439 27th

FAQ

What score does Qwen3 7B get on MMLU-Pro?

Qwen3 7B scores 64.2 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Qwen3 7B rank on MMLU-Pro?

It ranks #466 of 600 models, in the 22nd percentile. The leader is GPT-5.2 Pro at 91.6.

Is Qwen3 7B good at MMLU-Pro?

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 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 7B cost?

Qwen3 7B costs $1.37 per million input tokens and $7.23 per million output tokens.

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