Qwen2.5-Omni: An End-to-End Multimodal Model

Qwen2.5-Omni is a unified end-to-end multimodal model capable of perceiving text, images, audio, and video, while simultaneously generating text and natural speech responses in a streaming manner. It utilizes a Thinker-Talker architecture where Thinker handles text generation and Talker produces streaming speech tokens based on Thinker's representations. To synchronize video and audio, Qwen2.5-Omni employs a novel Time-aligned Multimodal RoPE (TMRoPE) position embedding. This model demonstrates strong performance across various modalities, achieving state-of-the-art results on multimodal benchmarks and showing comparable end-to-end speech instruction following to its text input capabilities. Qwen2.5-Omni also features efficient streaming inference through block-wise processing and a sliding-window DiT for audio generation.