Qwen 团队发布 Qwen3.8-Omni-Flash 全模态模型
Qwen 团队新出的全模态模型，能干视频编辑、长音频翻译这些活，还配了两个开源框架，玩智能体的可以试试。
Qwen 团队发布 Qwen3.8-Omni-Flash，一个原生多模态模型，面向文本、音频和视频的长程智能体任务，如视频编辑和长音视频翻译。模型采用 Qwen3.8-Next 的稀疏 MoE 架构，上下文窗口达 100 万 tokens。通过共训练策略在扩展智能体能力到音视频的同时保持文本性能。同时开源两个框架：Qwen-MM-Plugins 为现有智能体工具添加音视频支持，Qwen-Live-Harness 支持实时多模态交互、上下文记忆管理、工具调用和子智能体委派。
Era of the omni models is upon us.
This is a great report by the Qwen Team on their omni model.
They present Qwen3.8-Omni-Flash, a natively multimodal model trained for long-horizon agent tasks across text, audio and video, such as video editing and long-form audio and video translation.
It uses the sparse mixture-of-experts design of Qwen3.8-Next with a context window of one million tokens. A co-training strategy keeps text performance while carrying agent skills over to audio and video tasks.
Two open-source frameworks come with it. Qwen-MM-Plugins adds audio and video support to existing agent harnesses, and Qwen-Live-Harness handles real-time multimodal interaction with context and memory management, tool use and sub-agent delegation.
Paper: https://t.co/PxFrmGc5R1
