Qwen-3D: A Generalist 3D Vision-Language Model for Spatial Understanding

Large Multimodal Models (LMMs) have achieved remark-able success on images and short videos, yet scaling them to long videosremains challenging due to frame-centric tokenization and limited con-text windows. 3D geometry provides a natural compression mechanismfor visual streams: depth and camera pose enable observations from mul-tiple views and time steps to be fused into a persistent, world-aligned rep-resentation. While recent 3D LMMs leverage geometry-aware representa-tions to improve spatial reasoning, they continue to lag behind specialist3D perception systems on grounding and segmentation tasks. We arguethat a key limitation is geometry-aware decoding: existing methods com-municate 3D predictions through language tokens, proposal selection, orlightweight grounding queries, creating a bottleneck between languagereasoning and dense geometric prediction. Building on these insights, weintroduce Qwen-3D, a geometry-aware LMM that compresses visual in-formation within the Qwen backbone using multi-view geometric cues,enabling efficient long-horizon visual reasoning over static scenes. Qwen-3D augments visual tokens with 3D Rotary Positional Embeddings, al-lowing attention to operate directly in 3D scene space rather than acrossindependent image frames and thereby facilitating scalable cross-viewand temporal reasoning. To bridge language and geometry, Qwen-3D in-corporates a query-based segmentation decoder that grounds languagedirectly in the underlying 3D scene representation, unifying referentialgrounding, instance segmentation, and visual question answering acrossboth images and videos. Across a diverse set of benchmarks, Qwen-3Dsurpasses existing 3D LMMs and outperforms several large proprietary2D models. Notably, Qwen-3D achieves these improvements while main-taining strong performance on standard 2D vision–language benchmarksby jointly training on 2D and 3D data. Our code and checkpoints can befound at the project website https://qwen-3d.github.io/.