multimodal

Qwen2.5-Omni is a new generation of end-to-end multi-modal flagship model launched by Alibaba Cloud Tongyi Qianwen team. Designed for all-round multi-modal perception, the model can seamlessly process multiple input forms such as text, images, audio and video, and simultaneously generate text and natural speech synthesis output through real-time streaming responses. Its innovative Thinker-Talker architecture and TMRoPE positional encoding technology enable it to perform well in multi-modal tasks, especially in audio, video and image understanding. The model outperforms similar-sized single-modal models on multiple benchmarks, demonstrating strong performance and broad application potential. Currently, Qwen2.5-Omni is open source on Hugging Face, ModelScope, DashScope and GitHub, providing developers with rich usage scenarios and development support.

VITA-1.5 is an open source multi-modal large language model designed to achieve near real-time visual and voice interaction. It provides users with a smoother interactive experience by significantly reducing interaction latency and improving multi-modal performance. The model supports English and Chinese and is suitable for a variety of application scenarios, such as image recognition, speech recognition, and natural language processing. Its main advantages include efficient speech processing capabilities and powerful multi-modal understanding capabilities.