MemT-1.0 Bakes RAG-Level Memory Into Model Parameters

MemT-1.0 is a memory-native architecture that internalizes agent experience into model states via gated DeltaNet-2 and mixture-of-storage instead of external RAG, claiming RAG-level accuracy with 1.86x faster inference and 66x less storage on 128K context.

2026-10-25 ~ 2026-10-25 · 2 related posts

• MemT-1.0 claims RAG-level accuracy in parametric memory: 1.86x faster inference at 128K history — Alternative-Pay-447 · 2026-10-25
• memt-1.0's memory-native architecture: 1.86x faster, 66x smaller storage at 128k context — Mrs-Grumpy23 · 2026-10-25