Jina-VLM: Small Multilingual Vision Language Model
Authors: name: Andreas Koukounas, name: Georgios Mastrapas, name: Florian Hönicke, name: Sedigheh Eslami, name: Guillaume Roncari, name: Scott Martens, name: Han Xiao
Organization: Jina AI

We present Jina-VLM, a 2.4B parameter vision-language model that achieves state-of-the-art multilingual visual question answering among open 2B-scale VLMs. The model couples a SigLIP2 vision encoder with a Qwen3 language backbone through an attention-pooling connector that enables token-efficient processing of arbitrary-resolution images. Across standard VQA benchmarks and multilingual evaluations, Jina-VLM outperforms comparable models while preserving competitive text-only performance.