Scaling Spatial Intelligence with Multimodal Foundation Models
Authors: name: Zhongang Cai; name: Ruisi Wang; name: Chenyang Gu; name: Fanyi Pu; name: Junxiang Xu; name: Yubo Wang; name: Wanqi Yin; name: Zhitao Yang; name: Chen Wei; name: Qingping Sun; name: Tongxi Zhou; name: Jiaqi Li; name: Hui En Pang; name: Oscar Qian; name: Yukun Wei; name: Zhiqian Lin; name: Xuanke Shi; name: Kewang Deng; name: Xiaoyang Han; name: Zukai Chen; name: Xiangyu Fan; name: Hanming Deng; name: Lewei Lu; name: Liang Pan; name: Bo Li; name: Ziwei Liu; name: Quan Wang; name: Dahua Lin; name: Lei Yang
Published: 2025-11-17 18:59:33

Abstract: Despite remarkable progress, multimodal foundation models still exhibit surprising deficiencies in spatial intelligence. In this work, we explore scaling up multimodal foundation models to cultivate spatial intelligence within the SenseNova-SI family, built upon established multimodal foundations including visual understanding models (i.e., Qwen3-VL and InternVL3) and unified understanding and generation models (i.e., Bagel). We take a principled approach to constructing high-performing and robust spatial intelligence by systematically curating SenseNova-SI-8M: eight million diverse data samples under a rigorous taxonomy of spatial capabilities. SenseNova-SI demonstrates unprecedented performance across a broad range of spatial intelligence benchmarks: 68.7% on VSI-Bench, 43.3% on MMSI, 85.6% on MindCube, 54.6% on ViewSpatial, and 50.1% on SITE, while maintaining strong general multimodal understanding (e.g., 84.9% on MMBench-En). More importantly, we analyze the impact of data scaling, discuss early signs of emergent generalization capabilities enabled by diverse data training, analyze the risk of overfitting and language shortcuts, present a preliminary study on spatial chain-of-thought reasoning, and validate the potential downstream application. SenseNova-SI is an ongoing project, and this report will be updated continuously. All newly trained multimodal foundation models are publicly released to facilitate further research in this direction.