---
license: apache-2.0
library_name: mlx
tags:
- mlx
- continual-learning
- on-device-ai
- neural-imprint
- chronos
pipeline_tag: text-generation
---

# AtomGradient/Qwen3.5-9B-Chronos-4bit

## 中文简介

**Qwen3.5-9B-Chronos-4bit** 是专为 **Neural Imprint Chronos** 打造的端侧原生持续学习（Native Continual Learning）专用基座模型，需搭载 **Chronos 专用内核（Chronos Kernel）** 运行。

### 核心特性
- **端侧原生持续学习**：无需云端训练或反向传播微调，在本地设备运行过程中即可实时吸收、更新与巩固用户的长期偏好、生活习惯、跨事件因果关联及专属工具调用协议。
- **恒定体积记忆与跨端流转**：持续学习产生的用户记忆以恒定超紧凑状态包形式持久化，不随交互轮次线性膨胀，支持在手机、桌面工作站、智能座舱与具身终端之间秒级迁移与恢复。
- **数据不出端与用户资产主权**：所有学习、存储与推理全程在用户本地设备完成；状态资产受机主与内核双重主权保护，确保个人记忆数据的绝对私密性。

> **使用说明**：本模型与 **Neural Imprint Chronos 专用内核** 深度协同耦合，不支持脱离 Chronos 内核直接使用通用推理框架运行。

---

## English Overview

**Qwen3.5-9B-Chronos-4bit** is a dedicated on-device backbone model purpose-built for **Neural Imprint Chronos** native continual learning. It requires the **Chronos Kernel** runtime to operate.

### Key Capabilities
- **On-Device Native Continual Learning**: Continuously learns, updates, and consolidates user preferences, temporal habits, multi-event causal context, and custom tool-calling protocols in real time on edge devices—without cloud retraining or gradient backpropagation.
- **Constant-Envelope Memory & Cross-Device Mobility**: Continual learning states are persisted in an ultra-compact, constant-size state bundle with zero byte growth over time, enabling instant cold-start restoration and seamless migration across smartphones, desktops, vehicle cockpits, and embodied robotics.
- **Strict On-Device Privacy & User Sovereignty**: User data physically never leaves the device. Learned memory states are cryptographically bound to the device owner and the Chronos runtime.

> **Runtime Requirement**: This model is tightly coupled with the **Neural Imprint Chronos Kernel** and is not intended for standalone execution on generic inference runtimes without the Chronos kernel.