Janus is a new autoregressive model that unifies multimodal understanding and generation. The key innovation is the decoupling of visual encoding for these two tasks. By employing separate visual encoders for understanding and generation, Janus overcomes the limitations of previous models that relied on a single encoder, which often resulted in suboptimal performance for multimodal understanding. This decoupling strategy allows Janus to independently select the most suitable encoding methods for each task, leading to improved performance across various benchmarks, even exceeding that of task-specific models with significantly more parameters. This architecture makes Janus highly flexible and extensible, capable of accommodating additional modalities and potentially serving as a powerful generalist model for the next generation of multimodal AI.