# Qwen 团队发布 Qwen3.8-Omni-Flash 全模态智能体模型报告

- 来源：DAIR.AI (@dair_ai)
- 发布时间：2026-09-26 03:14
- AIHOT 分数：69
- AIHOT 链接：https://aihot.news/items/cmuhctws709c9ro3bc9io6um2
- 原文链接：https://x.com/dair_ai/status/2103563695381209417

## AI 摘要

Qwen 团队发布 Qwen3.8-Omni-Flash 报告，这是一个原生多模态模型，面向跨文本、音频和视频的长时程智能体任务，如视频编辑和长音频视频翻译。模型沿用 Qwen3.8-Next 的稀疏 MoE 架构，上下文窗口为 100 万 token，并通过协同训练策略在保持文本性能的同时把智能体能力迁移到音频和视频任务。

## 正文

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://academy.dair.ai/papers/qwen3-8-omni-towards-native-omni-modal-agents-2609.25611