Model card
LocateAnything-3B is a specialized vision-language model from NVIDIA designed specifically for high-precision spatial grounding. Unlike general-purpose multimodal models that provide broad descriptions, this 3B-parameter architecture focuses on the 'where' as much as the 'what.' It excels at mapping natural language queries to specific bounding boxes within an image, making it a critical tool for developers building object detection pipelines, visual search engines, or automated robotic vision systems. For engineers looking to integrate grounding capabilities without the massive computational overhead of larger models, its 3B footprint offers a highly efficient middle ground between lightweight detectors and heavy LLMs. It is particularly useful for zero-shot object localization tasks where pre-defined labels are insufficient and you need to detect arbitrary objects via text prompts. Integration is straightforward via Hugging Face, making it a plug-and-play option for RAG-based vision workflows or complex scene understanding applications.
Model files and versions
Download this model
We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.
nvidia/LocateAnything-3BInstall the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model nvidia/LocateAnything-3BREADME.md is used as an example; replace it with another repository file when needed.
modelscope download --model nvidia/LocateAnything-3B README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('nvidia/LocateAnything-3B')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/nvidia/LocateAnything-3B.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/nvidia/LocateAnything-3B.gitHow to use
- 01Step 1
Read the model card and source information.
- 02Step 2
Start with a small, non-sensitive evaluation.
- 03Step 3
Review quality, licensing and usage limits.
- 04Step 4
Adopt it only after validation.
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