Predicting the next layer's routing one token ahead serves a 35B MoE from SSD at 20 tok/s in 3GiB.

Edge0 attacks why naive SSD offloading fails for MoE: layer N+1's experts must be chosen before layer N's output exists, so reads can't start early enough to hide behind compute. A per-layer prerouter predicts the next layer's routing one token ahead and then uses that prediction as the routing, so the staged expert set equals the routed set and nothing is dropped, with an unmerged recovery LoRA paying back int4 quantization loss. On a single 24GB machine: 20 tok/s inside 3GiB peak active memory, within a few points of its fp16 teacher across five benchmarks. Framework, checkpoints and adapters open sourced.