EXAONE 4.5 Technical Report
Abstract
This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual encoder into the existing EXAONE 4.0 framework, enabling native multimodal pretraining over both visual and textual modalities. The model is trained on large-scale data with careful curation, particularly emphasizing document-centric corpora that align with LG's strategic application domains. This targeted data design enables substantial performance gains in document understanding and related tasks, while also delivering broad improvements across general language capabilities. EXAONE 4.5 extends context length up to 256K tokens, facilitating long-context reasoning and enterprise-scale use cases. Comparative evaluations demonstrate that EXAONE 4.5 achieves competitive performance in general benchmarks while outperforming state-of-the-art models of similar scale in document understanding and Korean contextual reasoning. As part of LG's ongoing effort toward practical industrial deployment, EXAONE 4.5 is designed to be continuously extended with additional domains and application scenarios to advance AI for a better life.
Cite
@article{arxiv.2604.08644,
title = {EXAONE 4.5 Technical Report},
author = {Eunbi Choi and Kibong Choi and Sehyun Chun and Seokhee Hong and Junwon Hwang and Hyojin Jeon and Ahra Jo and Hyunjik Jo and Yeonsik Jo and Joonkee Kim and Seonghwan Kim and Soyeon Kim and Sunkyoung Kim and Yireun Kim and Yongil Kim and Changhun Lee and Haeju Lee and Jinsik Lee and Kyungmin Lee and Sangha Park and Kwangrok Ryoo and Minju Seo and Sejong Yang and Heuiyeen Yeen and Hwan Chang and Stanley Jungkyu Choi and Yejin Choi and Kyubeen Han and Joonwon Jang and Kijeong Jeon and Geunyeong Jeong and Gerrard Jeongwon Jo and Jiyeon Jung and Daeseong Kim and Dohoon Kim and Dohyun Kim and Hyunseo Kim and Minu Kim and Myoungshin Kim and Youchul Kim and Byungoh Ko and Christopher Lee and Edward Hwayoung Lee and Honglak Lee and Jiyoung Lee and Sangeun Lee and Seungwon Lim and Woohyung Lim and Jueun Mun and Jaewoo Park and Jimin Park and Jinho Park and Yongmin Park and Wooseok Seo and Yongwoo Song and Sihyuk Yi and Kyungjae Yoo and Sangyeon Yoon},
journal= {arXiv preprint arXiv:2604.08644},
year = {2026}
}