Research
Meta publishes MemT-1.0, a memory-native model family with Nano and Flash variants
MemT-1.0 internalizes memory into model computation using Gated DeltaNet-2 and Mixture-of-Storage, trained on 34B tokens. At 128K history, Nano reports about 1.86x inference speedup and 66x lower persistent storage than a full KV cache.