MMLU-Redux

An improved version of the MMLU benchmark featuring manually re-annotated questions to identify and correct errors in the original dataset. Provides more reliable evaluation metrics for language models by addressing dataset quality issues found in the original MMLU.

Qwen3.5-397B-A17B from Alibaba Cloud / Qwen Team currently leads the MMLU-Redux leaderboard with a score of 0.949 across 45 evaluated AI models.

Paper

Alibaba Cloud / Qwen TeamQwen3.5-397B-A17B leads with 94.9%, followed by Alibaba Cloud / Qwen TeamQwen3.6 Plus at 94.5% and Moonshot AIKimi K2-Thinking-0905 at 94.4%.

Progress Over Time

Interactive timeline showing model performance evolution on MMLU-Redux

State-of-the-art frontier
Open
Proprietary

MMLU-Redux Leaderboard

45 models
ContextCostLicense
1
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
397B262K$0.60 / $3.60
2
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
1.0M$0.50 / $3.00
31.0T
4
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
122B262K$0.40 / $3.20
5
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
235B262K$0.30 / $3.00
6
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
236B262K$0.45 / $3.49
7
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
28B262K$0.60 / $3.60
8671B131K$0.55 / $2.19
9
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
35B
9
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
35B262K$0.25 / $2.00
11
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
27B262K$0.30 / $2.40
12
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
235B262K$0.15 / $0.80
131.0T
13
Moonshot AI
Moonshot AI
1.0T200K$0.50 / $0.50
15
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
80B66K$0.15 / $1.50
16
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
236B262K$0.30 / $1.49
17
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
33B
18671B164K$0.27 / $1.00
19
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
9B
20
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
80B66K$0.15 / $1.50
20
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
31B262K$0.20 / $1.00
22
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
33B
23560B
24
DeepSeek
DeepSeek
671B131K$0.27 / $1.10
25
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
9B262K$0.18 / $2.09
25
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
4B
27
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
31B262K$0.20 / $0.70
28
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
235B128K$0.10 / $0.10
29
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
73B131K$0.35 / $0.40
30
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
4B262K$0.10 / $1.00
31
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
9B262K$0.08 / $0.50
32
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
33B
3314B
33
Mistral AI
Mistral AI
675B128K$2.00 / $5.00
35
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
4B262K$0.10 / $0.60
36
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
15B
37
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
2B
388B
39
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
32B128K$0.09 / $0.09
40
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
8B131K$0.30 / $0.30
413B
42
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
7B
43
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
7B
44
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
800M
4521B128K$0.40 / $4.00
Notice missing or incorrect data?

FAQ

Common questions about MMLU-Redux.

What is the MMLU-Redux benchmark?

An improved version of the MMLU benchmark featuring manually re-annotated questions to identify and correct errors in the original dataset. Provides more reliable evaluation metrics for language models by addressing dataset quality issues found in the original MMLU.

What is the MMLU-Redux leaderboard?

The MMLU-Redux leaderboard ranks 45 AI models based on their performance on this benchmark. Currently, Qwen3.5-397B-A17B by Alibaba Cloud / Qwen Team leads with a score of 0.949. The average score across all models is 0.859.

What is the highest MMLU-Redux score?

The highest MMLU-Redux score is 0.949, achieved by Qwen3.5-397B-A17B from Alibaba Cloud / Qwen Team.

How many models are evaluated on MMLU-Redux?

45 models have been evaluated on the MMLU-Redux benchmark, with 0 verified results and 45 self-reported results.

Where can I find the MMLU-Redux paper?

The MMLU-Redux paper is available at https://arxiv.org/abs/2406.04127. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does MMLU-Redux cover?

MMLU-Redux is categorized under general, language, math, and reasoning. The benchmark evaluates text models.

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