EXAONE-Deep-32B model card (Hugging Face) Mar 18, 2025
EXAONE Deep 32B
EXAONE Deep 32B.
8
Benchmarks with a score
0
Ranked first, out of five or more models
0
In the top three
EXAONE Deep 32B
Open weights Flagship
131.4
#266 of 404
Self-Reported Index, from the lab's own numbers. No Epoch Capabilities Index score yet.
- LiveCodeBench v5 59.5% #26 /47
- MMLU-Pro 74% #114 /167
- AIME 2025 65.8% #117 /143
Where it ranks
Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.
Knowledge and language
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MATH-500 | 95.7% | #37 of 70 | Lab model card | |
| AIME 2024 | 72.1% | #58 of 88 | Lab model card | |
| GPQA Diamond | 66.1% | #200 of 302 | Lab model card | |
| AIME 2025 | 65.8% | #117 of 143 | Lab model card | |
| CSAT Math 2025 | 94.5% | #1 of 1 | Lab model card |
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| LiveCodeBench v5 | 59.5% | #26 of 47 | Lab model card |
Its lab's numbers put it at 131.4, number 266 of 404
The Self-Reported Index fits one score to the 7 capability results LG AI Research reported for this model, on the scale of the Epoch Capabilities Index. Labs choose which benchmarks to show and how to run them, so read it as the lab's claim, not an independent measurement. The 90% interval runs from 129.6 to 133.3. How we compute it.
- MATH-500 95.7
- MMLU 83
- MMLU-Pro 74
- AIME 2024 72.1
- GPQA Diamond 66.1
- AIME 2025 65.8
- LiveCodeBench v5 59.5
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.
Its system card
Every result in the longer documents the lab published with it. 2 of them aren't in the launch post.
EXAONE Deep: Reasoning Enhanced Language Models Mar 16, 2025
Capabilities
- MATH-500 95.7
- AIME 2024 72.1
- AIME 2025 65.8
- CSAT Math 2025 94.5
- GPQA Diamond 66.1
- LiveCodeBench v5 59.5
- MMLU 83
- MMLU-Pro 74