What is janus?

Janus is a series of AI models from DeepSeek that can both understand images and generate images from text, using a single unified architecture. Most AI models are specialized, a model that answers questions about images is separate from a model that creates images from text prompts. Janus attempts to do both within the same framework. The core research insight, as described in the README, is that understanding and generating images benefit from different visual processing strategies. Rather than forcing one visual encoder (the part of the model that processes images) to serve both purposes, Janus uses separate encoding pathways for understanding and generation while still sharing a single underlying transformer, the type of neural network that powers modern AI models. This separation is claimed to reduce conflict between the two tasks and improve performance on both. The series currently has three variants. The original Janus model (1.3 billion parameters) focuses on the decoupled encoding approach. JanusFlow (1.3B) integrates a generation technique called rectified flow into the language model framework. Janus-Pro (available in 1B and 7B sizes) is an improved version with more training data and refined training strategy. You would use Janus if you are an AI researcher or developer working with multimodal models and want a single model that can describe what is in an image (visual understanding) and also create images from text instructions (image generation). Models are available to download from Hugging Face and are written in Python. The code license is MIT and the model weights have a separate model license. The full README is longer than what was provided.