EXAONE-3.5-32B-Instruct: benchmark scores, price and ranking
EXAONE-3.5-32B-Instruct from LGAI-EXAONE ranks #359 of 743 LLMs on the LLMs Tiger aggregate benchmark score (48.4), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- LGAI-EXAONE
- Type
- Open-weight / local model
- Open weights
- Yes
- Aggregate rank
- #359 of 743 (score 48.4)
Across the 1 benchmark where at least ten models are scored, EXAONE-3.5-32B-Instruct is in the top 10% on 0 and in the top half on 1.
EXAONE-3.5-32B-Instruct benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| MMLU-Pro | 58.9% | #63 of 136 | HuggingFace MMLU-Pro leaderboard | 2026-10-13 |
About EXAONE-3.5-32B-Instruct
EXAONE-3.5-32B-Instruct is an open-weight model that can run on your own hardware from LGAI-EXAONE. No API price is listed for it yet. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.
Where EXAONE-3.5-32B-Instruct stands
On our aggregate score, EXAONE-3.5-32B-Instruct is #359 of 743 ranked models, around the middle of the table. Its score is 48.4; the scale is centred on 50, so it sits 1.6 points below the typical model. That beats 52% of the ranked field. Among the 5 ranked LGAI-EXAONE models it is #3. The next one up is K-EXAONE-236B-A23B at 52.0. The next one down is EXAONE-3.5-7.8B-Instruct at 46.6.
EXAONE-3.5-32B-Instruct, benchmark by benchmark
MMLU-Pro puts EXAONE-3.5-32B-Instruct at 58.9%, #63 of 136. That beats 54% of the models tested, but 29.2 points short of Darwin-180B-RSI (88.1%). The results either side are Mellum2-12B-A2.5B-Base-Pretrain (59.3%) and MiMo-7B-RL (58.6%). It covers 57-subject knowledge + reasoning. The board median is 55.3%, so EXAONE-3.5-32B-Instruct is 3.7 points above it. Source: HuggingFace MMLU-Pro leaderboard, captured 2026-10-13.
Reading these numbers
The 1 score on this page comes from 1 source: HuggingFace MMLU-Pro leaderboard (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 1 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #356 yi-lightning (48.4)
- #357 Kimi K2.6 (48.4)
- #358 o1-mini (high) (48.4)
- #360 pixtral-large-2411 (48.3)
- #361 Muse Glimmer (high) (48.3)
- #362 gpt-3.5-turbo-0125 (48.3)
More from LGAI-EXAONE
- EXAONE-4.5-33B (#81, 52.1)
- K-EXAONE-236B-A23B (#84, 52.0)
- EXAONE-3.5-7.8B-Instruct (#500, 46.6)
- EXAONE-3.5-2.4B-Instruct (#562, 45.7)
Compare it on the live leaderboard → · How the aggregate score works