MemTensor's MemT-1.0 makes persistent memory part of model compute: 1.86x faster inference, 66x less storage
_akhaliq · x · 2026-10-21
MemTensor unveiled MemT-1.0, a memory-native foundation model architecture that embeds persistent memory directly into the model's forward pass rather than bolting on external retrieval. The design includes native memory blocks within transformer layers plus local/hyper memory blocks with erase/write/forget gating. Reported results: 1.86x inference speedup and 66x storage reduction at 128K context history.
Related event: MemTensor Open-Sources MemT-1.0, a Memory-Native Foundation Model(8 posts)→
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