---
title: MemTensor/MemT-1.0-Nano
url: https://recentmodel.com/models/MemTensor/MemT-1.0-Nano/
status: main board
published: 2026-10-15T03:46:11Z
updated: 2026-10-19T23:17:53Z
source: https://huggingface.co/MemTensor/MemT-1.0-Nano
---

# MemTensor/MemT-1.0-Nano

MemT-1.0 is a new generation of memory foundation models that makes persistent, dynamically evolving memory an intrinsic part of model computation. 35B params. License: apache-2.0. Vendor-reported: "Across 11 memory benchmarks, MemT-1.0-Flash and MemT-1.0-Nano rank first and second among the evaluated parametric-memory methods, respectively."

- Vendor-reported: Across 11 memory benchmarks, MemT-1.0-Flash and MemT-1.0-Nano rank first and second among the evaluated parametric-memory methods, respectively.

- **Org:** MemTensor
- **Released:** 2026-10-15
- **Status:** main board
- **License:** apache-2.0 (permissive)
- **Parameters:** 35.1B
- **Architecture:** MemTQwen3_5MoeForCausalLM
- **Task:** text-generation · text
- **Signal:** 110 HF likes · 18765 downloads

## Runs on

mixed: real files + estimate; sizing calculation, not tested.

- Q4 ~25.1 GB (estimated): 32GB GPU (5090), Mac 36GB, Mac 48GB, CPU only, 32GB RAM (slow)
- Q8 ~41.3 GB (estimated): 48GB GPU (RTX 6000 Ada / A6000), Mac 64GB (M1 Max), Mac 96GB, CPU only, 64GB RAM (slow)
- FP16 ~74.2 GB: 96GB GPU (RTX Pro 6000 Blackwell), 1× DGX Spark (128GB), 2× DGX Spark (256GB), Strix Halo 128GB unified (~96GB usable), Mac 128GB, Mac 192GB, Mac 256GB, Mac 512GB, CPU only, 128GB RAM (slow), CPU only, 256GB RAM (slow)

## Links

- [Hugging Face](https://huggingface.co/MemTensor/MemT-1.0-Nano)