Looping provides parameter-free FLOPS, whereas MoE architectures provide FLOPS-free parameters
Mostafa Dehghani · AI is Already Building AI — Google DeepMind’s Mostafa Dehghani · Apr 2, 2026 · at 39:22
Mostafa Dehghani, research scientist at Google DeepMind, contrasts the compute tradeoffs of Mixture of Experts (MoE) models with depth-looping neural network architectures.
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“In mixture of experts, you have flops free parameters. So, so parameters that they're not actually bringing any flops. And in, in like looping, you have parameter free flops where you don't have extra parameters for the extra flops that you're throwing on this. So it goes the other direction of the sparsity and it's quite effective.”
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