Model card
Janus-Pro-7B is a versatile 'any-to-any' multimodal model from the DeepSeek team, designed to bridge the gap between text and visual reasoning. Unlike traditional models that treat vision as a secondary input, Janus-Pro is built for seamless cross-modal generation and understanding. For developers, this means you can move beyond simple image captioning into complex tasks like high-fidelity image synthesis, visual document parsing, and sophisticated spatial reasoning within a single 7B parameter framework. Its architecture is optimized for efficiency, making it a strong candidate for edge deployment or integration into agentic workflows where both visual perception and creative output are required. While larger models offer brute-force reasoning, Janus-Pro provides a highly competitive performance-to-latency ratio, making it ideal for real-time applications like interactive UI assistants or automated visual content pipelines. It is released under the MIT license, ensuring high flexibility for commercial integration.
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.
deepseek-ai/Janus-Pro-7BInstall the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model deepseek-ai/Janus-Pro-7BREADME.md is used as an example; replace it with another repository file when needed.
modelscope download --model deepseek-ai/Janus-Pro-7B README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('deepseek-ai/Janus-Pro-7B')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/deepseek-ai/Janus-Pro-7B.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/deepseek-ai/Janus-Pro-7B.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.
Discussions
Use this space to keep checking source information, usage experience and maintenance status.
Open source page