Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models
Authors: name: Lianghua Huang, name: Zhifan Wu, name: Wei Wang, name: Yupeng Shi, name: Mengyang Feng, name: Junjie He, name: Chenwei Xie, name: Yu Liu, name: Jingren Zhou, name: Ang Wang, name: Bang Zhang, name: Baole Ai, name: Chen Liang, name: Cheng Yu, name: Chongyang Zhong, name: Jinwei Qi, name: Kai Zhu, name: Pandeng Li, name: Peng Zhang, name: Wenyuan Zhang, name: Xinhua Cheng, name: Yitong Huang, name: Yun Zheng, name: Zoubin Bi
Organization: Wan-AI

We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex audio-visual interaction. Wan-Streamer seamlessly models language, audio, and video as both input and output within a single Transformer, where the sequence is represented as interleaved visual, audio, and text input tokens together with visual, audio, and text output tokens, coordinated by block-causal attention for incremental streaming. Unlike cascaded interactive systems that rely on separate VAD, ASR, language, TTS, audio-driven animation, or video-generation modules, Wan-Streamer does not rely on external language, speech, avatar, or video-generation modules: perception, reasoning, generation, response timing, turn management, and cross-modal synchronization are learned jointly within one unified model, reducing pipeline latency and error accumulation. To support natural audio-visual responsiveness, we redesign the entire stack around streamability, including causal encoders, causal decoders, block-causal attention, and low-latency multimodal token scheduling, enabling streaming units as short as 160 ms at 25 fps. Wan-Streamer achieves approximately 200 ms model-side response latency and approximately 550 ms total interaction latency when combined with 350 ms bidirectional network latency, supporting sub-second duplex audio-visual communication. These results position Wan-Streamer as a unified, end-to-end, multimodal interactive foundation model for low-latency streaming interaction.