EXAONE-3.5-7.8B-Instruct: benchmark scores, price and ranking
EXAONE-3.5-7.8B-Instruct from LGAI-EXAONE ranks #500 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.6), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- LGAI-EXAONE
- Type
- Open-weight / local model
- Open weights
- Yes
- Aggregate rank
- #500 of 743 (score 46.6)
Across the 1 benchmark where at least ten models are scored, EXAONE-3.5-7.8B-Instruct is in the top 10% on 0 and in the top half on 0.
EXAONE-3.5-7.8B-Instruct benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| MMLU-Pro | 46.2% | #83 of 136 | HuggingFace MMLU-Pro leaderboard | 2026-10-13 |
About EXAONE-3.5-7.8B-Instruct
EXAONE-3.5-7.8B-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-3.5-7.8B-Instruct stands
On our aggregate score, EXAONE-3.5-7.8B-Instruct is #500 of 743 ranked models, in the lower half. Its score is 46.6; the scale is centred on 50, so it sits 3.4 points below the typical model. That beats 33% of the ranked field. Among the 5 ranked LGAI-EXAONE models it is #4. The next one up is EXAONE-3.5-32B-Instruct at 48.4. The next one down is EXAONE-3.5-2.4B-Instruct at 45.7.
EXAONE-3.5-7.8B-Instruct, benchmark by benchmark
EXAONE-3.5-7.8B-Instruct lands below the middle on MMLU-Pro: 46.2%, #83 of 136, with 60% of the field scoring higher. Darwin-180B-RSI leads at 88.1%; the closest result above is Phi-3.5-mini-instruct at 47.9%. It covers 57-subject knowledge + reasoning. The board median is 55.3%, so EXAONE-3.5-7.8B-Instruct is 9.0 points below 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
- #497 Composer 2.5 (46.6)
- #498 gemini-2.0-flash-lite (46.6)
- #499 Mellum2-12B-A2.5B-Thinking-SFT (46.6)
- #501 GPT-4.5 Preview (Feb 2025) (46.6)
- #502 mimo-v2-pro (46.6)
- #503 Yi-1.5-9B-Chat (46.6)
More from LGAI-EXAONE
- EXAONE-4.5-33B (#81, 52.1)
- K-EXAONE-236B-A23B (#84, 52.0)
- EXAONE-3.5-32B-Instruct (#359, 48.4)
- EXAONE-3.5-2.4B-Instruct (#562, 45.7)
Compare it on the live leaderboard → · How the aggregate score works