Wah... ini luar biasa. Qwen 3.8 Flash Next berjalan secara lokal pada satu RTX 6000 Pro.
La receta esta basada en un fork fijado de SGLang, que sirve RadixArk/Qwen3.8-Flash-Next-NVFP4 en una única RTX PRO 6000 de 96 GB y la he limitado a 275 W; driver NVIDIA 610.57.04, CUDA
Kebingungan baru saja memindahkan seluruh agen AI mereka ke mesin Anda sendiri.
Browsing, reasoning, tools, file access. All local. They didn't shrink the cloud version down. They rebuilt the architecture for what a local model does well. Smaller prompts, tools that only load when needed,
Qwen 3.8-27B dari Alibaba gratis untuk digunakan saat ini, dan dapat membaca teks, gambar, dan video.
No GPU. No downloading 55GB of files. You go to Token Harbor, find the free route, and send a prompt. The context window is 262,000 tokens natively. Alibaba's hosted version stretches to 1
Qwen 3.8 Flash Next menampung 125 miliar parameter tetapi hanya menembakkan 6 miliar setiap kali ia berpikir.
Alibaba says it cost roughly a tenth of what their last flagship cost to train. Here's why that works. Most models read the whole book from page one every time you ask about chapter
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