The Inpainting Model That Skipped the Attention
HUST's Moebius (0.22B) matches FLUX.1-Fill-Dev (11.9B) on six image inpainting benchmarks at 15× the inference speed. Two mechanisms make it work: Local-λ Mix Interaction blocks that replace quadratic spatial attention with fixed-size linear matrices, and adaptive multi-granularity latent-space distillation. For inpainting specifically, attention overhead appears to be the actual bottleneck — not parameter count. Weights are out.
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