Goodbye Coding Plans
Summary
作者预言大约一年后,本地模型配合良好的 harness 就能编写 90% 的代码,并点名期待 Qwen 的表现,随后补充说许多人认为 Qwen3.8 Next Flash 已经接近这一水平,自己要去试一试。
Similar Articles
@threerouter_com: Tonight at 23:00, Alibaba is going to open-source Qwen3.8-Flash-Next on ModelScope, and the news is accurate. But honestly, releasing it without benchmarks, I'm skeptical. The official reason is to adapt for the complete Qwen4 family, meaning 'you try it first, and we'll add the report card later.' The architecture looks impressive—Qwen…
Alibaba will open-source the Qwen3.8-Flash-Next model on ModelScope at 23:00 tonight, featuring Qwen4's GDN hybrid layers and sparse attention architecture, but lacking benchmark data.
Qwen/Qwen3.8-Flash-Next
Release of Qwen3.8-Flash-Next, an open-weight AI model introducing architectural innovations like Hybrid Attention with QSA and Gated Residual for improved efficiency and scalability, previewing the future Qwen4 architecture.
@QwenDevs: The next Qwen wave is coming
This announcement teases the upcoming open release of Qwen3.8-Flash-Next, powered by a new next-gen architecture for the Qwen4 model.
@MiaAI_lab: 22 hours to go for Qwen3.8 Flash There is NO sleep in local AI ! https://huggingface.co/Qwen/Qwen3.8-Flash-Next…
The article announces the upcoming release of Qwen3.8-Flash, a preview of the Qwen4 architecture, on Hugging Face with a 22-hour countdown.
Is all the work that's being put into Qwen3.8 Flash Next going to set us up for a very quick uplift to Qwen4?
The author asks whether the extensive inference optimizations going into Qwen3.8 Flash Next will position Alibaba to quickly uplift those gains to Qwen4 when it releases.