Qwen3.8-Flash-Next (125B total, 6B active) in the oom-inference weight format, for serving on one 24 GB GPU with 64 GB of RAM. The engine keeps routed experts across VRAM, pinned RAM and NVMe, so the model does not need to fit in memory. This is with its bytes laid out one record per expert. No weight is changed: the NVFP4 routed experts, BF16 dense weights and FP8 n-gram tables are exactly as released. It is only for oominf; it is not a Transformers, Safetensors or GGUF checkpoint. How it works: How to serve 134 GB of model weights with 24 GB VRAM / 64 GB RAM. Measured through oominf serve's OpenAI-compatible API with oomeval, on the files in this repository with serve defaults (fp32…