No More Token Anxiety: Build an “Unlimited-Use” Local AI Assistant with GPUStack + OpenClaw

Over the past two years, more and more teams have integrated AI into their daily workflows. But soon, a practical issue emerged: The more the model is used, the faster Tokens are consumed, and both costs and psychological pressure rise accordingly. Many people rely on AI to improve efficiency, while at the same time having to “use it sparingly” and “let it think less.” In the end, AI instead becomes a carefully budgeted consumable. If AI can run on your own GPU, without being billed by Token, available for conversation at any time, and running long-term inside collaboration tools, then it truly feels like a real “work assistant.” Based on the local model capabilities provided by GPUStack, combined with OpenClaw (supporting multiple collaboration platforms such as WhatsApp, Telegram, Discord, Slack, Lark, etc.) and Telegram, this article will walk through step by step how to build a truly usable, sustainably running, and almost Token-worry-free local AI assistant. 📌 What This Article Co