Qwen3.8-Omni-Flash
Qwen3.8-Omni-Flash is Qwen’s next-generation native omni-modal model supports context lengths of up to 1M tokens and natively accepts text, image, audio, and video inputs. Built on the Qwen3.8-Flash-Next architecture, it is designed for…. It is ranked #20 on the AI Radar, in Frontier models, first seen 1 days ago and shared in 12 posts (427.6k views).
What people said about Qwen3.8-Omni-Flash on X
🚀 Meet Qwen3.8-Omni-Flash, Qwen's first omni-modal model built around agentic capabilities! Native audio-video understanding, reasoning, and tool use come together in one model: understand the content, plan the task, execute with tools, and deliver the result. Highlights: 🥳 - Audio-video intelligence that gets…
— @Alibaba_Qwen, 1 days ago · 3.4k likes · see the post
Meet Qwen3.8-LiveTranslate, Qwen's next-generation real-time simultaneous interpretation model! 📢 Built on an Interleave architecture, it improves faithfulness, fluency, and conciseness while reducing average lagging (LAAL) from 2.8s to 2.3s across 60 languages. New capabilities: 🙌 - Real-time speaker diarization —…
— @Alibaba_Qwen, 9 h ago · 1.3k likes · see the post
It doesn’t just watch and listen. It figures out what to do next and uses tools to get it done. Meet Qwen3.8-Omni-Flash.
— @QwenDevs, 1 days ago · 418 likes · see the post
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Qwen3.8-Omni-Flash in numbers
- Rank on the AI Radar: #20 of 1181
- Shared in 12 posts by 9 accounts: @Alibaba_Qwen, @QwenDevs, @ItsmeAjayKV, @loktar00
- 427.6k views on those posts
- First seen 1 days ago, last shared 3 h ago
- Pricing seen by Jev: not stated
- Market: Frontier models
FAQ
What is Qwen3.8-Omni-Flash?
Qwen’s next-generation native omni-modal model supports context lengths of up to 1M tokens and natively accepts text, image, audio, and video inputs. Built on the Qwen3.8-Flash-Next architecture, it is designed for… It was first shared on X 1 days ago and is ranked #20 on the AI Radar.
Is Qwen3.8-Omni-Flash free?
Pricing is not stated on the page we read.
Who shared Qwen3.8-Omni-Flash?
9 accounts on X, including @Alibaba_Qwen, @QwenDevs, @ItsmeAjayKV, in 12 posts totalling 427.6k views.
Every post is read and classified by Jev (TypeSafe): what it is, which market it belongs to, and whether the link is a real tool. 27k posts from 4.8k X accounts over the last 14 days, 1.2k tools, 19 markets. Collected every 5 minutes, fully re-ranked every hour — last update 2026-09-19 16:11 UTC. Full method.