HyperCLOVA X 32B Think
Abstract
In this report, we present HyperCLOVA X 32B Think, a vision-language model designed with particular emphasis on reasoning within the Korean linguistic and cultural context, as well as agentic ability. HyperCLOVA X 32B Think is pre-trained with a strong focus on reasoning capabilities and subsequently post-trained to support multimodal understanding, enhanced reasoning, agentic behaviors, and alignment with human preferences. Experimental evaluations against comparably sized models demonstrate that our model achieves strong performance on Korean text-to-text and vision-to-text benchmarks, as well as on agent-oriented evaluation tasks. By open-sourcing HyperCLOVA X 32B Think, we aim to support broader adoption and facilitate further research and innovation across both academic and industrial communities.
Fields of Study & Subjects
Multimodal Machine Learning Applications
Topic Modeling
Natural Language Processing Techniques
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 3 January 2026
- Document type
- Preprint