MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
Xiangxiang Chu
Limeng Qiao
Xinyu Zhang
Shuang Xu
Fei Wei
Yang Yang
Xiaofei Sun
Yiming Hu
Xinyang Lin
Bo-Wen Zhang
Chunhua Shen

Abstract
We introduce MobileVLM V2, a family of significantly improved vision language models upon MobileVLM, which proves that a delicate orchestration of novel architectural design, an improved training scheme tailored for mobile VLMs, and rich high-quality dataset curation can substantially benefit VLMs' performance. Specifically, MobileVLM V2 1.7B achieves better or on-par performance on standard VLM benchmarks compared with much larger VLMs at the 3B scale. Notably, our 3B model outperforms a large variety of VLMs at the 7B+ scale. Our models will be released at https://github.com/Meituan-AutoML/MobileVLM .
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