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16 SEP 2026 · Paper

The Other Half of the Memory Wall: Serving 35B MoEs from SSD with Trained Routing Prediction

This paper presents a new technique to reduce memory usage and speed up inference for large neural networks, allowing them to run on consumer hardware with limited memory. A practitioner might care about this because it enables the deployment of large models in edge devices and reduces the need for expensive storage.

mixture-of-expertsmemory efficiencydeep learning inferenceneural network pruningsparse models