2026-10-24 · America/Los_Angeles · 社区动态 · #7

8 GB GPU, 262K context 3.5 BPW Qwen-Flash-Next Coder 70 T/s using llama.cpp

The methodology Qwen-Flash-Next has n-gram, MOE packing above its weight but it's still 6B active params. We exploit this by keeping most MOEs in RAM (Smallest MOEs go in VRAM for speedup) and n-gram on disk - ensure you put the model on your fastest SSD. 8 GB VRAM, 24 GB RAM cost. You can run this fine if you've ~32 GB total memory too, but you'd have to turn down context size . Customize the launch params to best suit your hardware. EDIT Note: Apparently CUDA struggles to run this with 8 GB VRAM, so please use Vulkan backend if it fails to run for you. You can also use the second launch…

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