Memory Tensor Open-Sources Memory-Native MemT 1.0 Models
10/20/2026 — 10/21, 23:27·2 sources (all)·2 reports (all)
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- Memory Tensor released and open-sourced MemT 1.0, comprising MemT-1.0-Flash at 288B parameters and MemT-1.0-Nano at 36B, with 17B and 3B act…
Memory Tensor released and open-sourced MemT 1.0, comprising MemT-1.0-Flash at 288B parameters and MemT-1.0-Nano at 36B, with 17B and 3B active. The models build persistent, updatable internal memory into the computation itself, so past information and task experience are recalled automatically in later tasks without resupplying the original history.
Latest turnResearchers introduced MemT-1.0, a new foundation model architecture that internalizes memory as part of model computation for continuous learning. Built on Metis, MemT-1.0 employs Gated DeltaNet-2 with stable token-level memory updates and uses Mixture-of-Storage to scale native capacity.
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Researchers introduced MemT-1.0, a new foundation model architecture that internalizes memory as part of model computation for continuous learning. Built on Metis, MemT-1.0 employs Gated DeltaNet-2 with stable token-level memory updates and uses Mixture-of-Storage to scale native capacity.
Reddit · LocalLLaMAAI score 55
The MemT 1.0 series has been released and open-sourced, with a 288B Flash model and a 36B Nano model using 17B and 3B active parameters respectively. The models build persistent, updatable internal memory into computation, so prior context and task experience are recalled automatically instead of being resent as raw history.
36氪AI score 67
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