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

LongCLIP-B16

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:

• Reference implementation: LongCLIP-B16
• Original Weight: LongCLIP-B16
• Resolution: 3x224x224
• Support Cooper version:
  • Cooper SDK: [2.5.2]
  • Cooper Foundry: [2.2]

Model	Device	Model Link
LongCLIP-B16 Image Encoder	N1-655	Model_Link
LongCLIP-B16 Text Encoder	N1-655	Model_Link
LongCLIP-B16 Image encoder	CV72	Model_Link
LongCLIP-B16 Text Encoder	CV72	Model_Link
LongCLIP-B16 Image encoder	CV75	Model_Link
LongCLIP-B16 Text Encoder	CV75	Model_Link