{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mobilevlm-a-fast-reproducible-and-strong","title":"MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices","arxiv_id":"2312.16886","date":"2023-12-28","proceeding":null,"authors":["Xiangxiang Chu","Limeng Qiao","Xinyang Lin","Shuang Xu","Yang Yang","Yiming Hu","Fei Wei","Xinyu Zhang","Bo Zhang","Xiaolin Wei","Chunhua Shen"],"abstract":"We present MobileVLM, a competent multimodal vision language model (MMVLM) targeted to run on mobile devices. It is an amalgamation of a myriad of architectural designs and techniques that are mobile-oriented, which comprises a set of language models at the scale of 1.4B and 2.7B parameters, trained from scratch, a multimodal vision model that is pre-trained in the CLIP fashion, cross-modality interaction via an efficient projector. We evaluate MobileVLM on several typical VLM benchmarks. Our models demonstrate on par performance compared with a few much larger models. More importantly, we measure the inference speed on both a Qualcomm Snapdragon 888 CPU and an NVIDIA Jeston Orin GPU, and we obtain state-of-the-art performance of 21.5 tokens and 65.3 tokens per second, respectively. Our code will be made available at: https://github.com/Meituan-AutoML/MobileVLM.","url_abs":"https://arxiv.org/abs/2312.16886v2","url_pdf":"https://arxiv.org/pdf/2312.16886v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mobilevlm-a-fast-reproducible-and-strong","repo_url":"https://github.com/meituan-automl/mobilevlm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"automl","task_name":"AutoML"},{"task_slug":null,"task_name":"CPU"},{"task_slug":null,"task_name":"GPU"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"referring-expression-comprehension","task_name":"Referring Expression Comprehension"},{"task_slug":"referring-expression-generation","task_name":"Referring expression generation"}],"methods":[{"method_slug":"clip","method_name":"CLIP"},{"method_slug":"set","method_name":"SET"},{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/image-classification-on-coloninst-v1-seen","task":"Image Classification","dataset":"ColonINST-v1 (Seen)","model":"MobileVLM-1.7B (w/ LoRA, w/ extra data)","rank_in_archive_order":3,"of":17,"metrics":{"Accuray":"93.64"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-coloninst-v1-seen","task":"Image Classification","dataset":"ColonINST-v1 (Seen)","model":"MobileVLM-1.7B (w/o LoRA, w/ extra data)","rank_in_archive_order":8,"of":17,"metrics":{"Accuray":"93.02"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-coloninst-v1-unseen","task":"Image Classification","dataset":"ColonINST-v1 (Unseen)","model":"MobileVLM-1.7B\n  (w/ LoRA, w/ extra data)","rank_in_archive_order":3,"of":17,"metrics":{"Accuray":"80.44"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-coloninst-v1-unseen","task":"Image Classification","dataset":"ColonINST-v1 (Unseen)","model":"MobileVLM-1.7B\n  (w/o LoRA, w/ extra data)","rank_in_archive_order":8,"of":17,"metrics":{"Accuray":"78.75"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-generation-on-coloninst","task":"Referring expression generation","dataset":"ColonINST-v1 (Seen)","model":"MobileVLM-1.7B\n  (w/ LoRA, w/ extra data)","rank_in_archive_order":7,"of":17,"metrics":{"Accuray":"97.87"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-generation-on-coloninst","task":"Referring expression generation","dataset":"ColonINST-v1 (Seen)","model":"MobileVLM-1.7B\n  (w/o LoRA, w/ extra data)","rank_in_archive_order":8,"of":17,"metrics":{"Accuray":"97.78"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-generation-on-coloninst-1","task":"Referring expression generation","dataset":"ColonINST-v1 (Unseen)","model":"MobileVLM-1.7B\n  (w/ LoRA, w/ extra data)","rank_in_archive_order":2,"of":17,"metrics":{"Accuray":"78.03"},"uses_additional_data":false},{"leaderboard":"/sota/referring-expression-generation-on-coloninst-1","task":"Referring expression generation","dataset":"ColonINST-v1 (Unseen)","model":"MobileVLM-1.7B\n  (w/o LoRA, w/ extra data)","rank_in_archive_order":7,"of":17,"metrics":{"Accuray":"73.14"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2312.16886","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}