LongCLIP extends the CLIP vision–language framework to support significantly longer text inputs, enabling richer contextual understanding while preserving strong image–text alignment.

Original paper: Long-CLIP: Unlocking Long-Text Capability in CLIP, Zhang et al., 2024

This model uses the LongCLIP B/16 variant, which is based on a ViT-Base backbone with 16×16 image patches and enhanced long-text encoding capacity. It is well suited for vision–language applications such as image retrieval, zero-shot classification, and multimodal reasoning where long textual prompts or descriptions are important.

Model Configuration: