By moving AGI from the cloud to the edge, CTONE is challenging the latency and privacy limitations of modern AI interaction.
The Shenzhen-based CTONE Group has launched the first production-ready "Agent Computer," a hardware lineup dedicated to local-first agentic AI. Unlike traditional laptops or smartphones that use AI as an application feature, the CTONE system is built from the ground up to be navigated and managed by an autonomous agent. The device is designed to handle up to 90% of user daily tasks entirely on-device, without phoning home to a cloud-based LLM.
The CTONE Agent Computer utilizes a custom **ASIC (Application-Specific Integrated Circuit)** optimized for 4-bit and 8-bit quantized models. It ships with a proprietary model, Core-1, which is a 12-billion parameter multimodal agent optimized for low-latency reasoning. The hardware features 128GB of unified high-bandwidth memory, allowing the model to keep massive chunks of a user's local filesystem and conversation history in its active context window.
This "local-first" approach eliminates the 500ms–2s latency typical of cloud-based agents. In demonstrations, the CTONE agent was shown refactoring code, synthesizing meeting notes from local audio, and organizing complex travel itineraries in sub-100ms response times.
One of the most radical departures in the CTONE design is the optional "Screen-Free" mode. The device features an advanced beam-forming microphone array and a haptic touch-surface, encouraging users to interact with their agent via voice and ambient gestures. The goal is to move AI from a "destination" (a website or app) to an ambient utility that exists in the background of the physical workspace.
By processing data locally, CTONE addresses the growing enterprise anxiety over data sovereignty. Since the agent never sends raw data to a central server, it can be granted access to highly sensitive documents, private keys, and internal communications that would typically be off-limits for cloud-based providers like OpenAI or Microsoft. This "private brain" model could define the next decade of personal and professional computing.