The latest cross-modal model from Alibaba Cloud's Qwen team, Qwen3-Omni, is expected to be officially released soon. According to reliable information, the model has submitted a PR to the Hugging Face Transformers library, marking the upcoming open-source integration of this end-to-end multimodal AI system. This advancement is based on the continuous iteration of the Qwen series, aiming to further improve the model's deployment efficiency on resource-constrained devices.

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Qwen3-Omni is the third generation of the Omni series, which is known for its end-to-end architecture. It can seamlessly process multiple input modalities such as text, images, audio, and video, and generate text and voice outputs. Similar to its predecessor, it adopts a Thinker-Talker dual-track design: the Thinker is responsible for understanding multi-modal inputs and generating high-level representations, while the Talker synthesizes natural speech in real time. This architecture ensures efficient streaming processing during training and inference, making it particularly suitable for real-time interactive scenarios.