> For the complete documentation index, see [llms.txt](https://docs.xynq.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.xynq.ai/the-xynq-terminal.md). # The XYNQ Terminal The XYNQ interface is a single, keyboard-first terminal. It has four tabs. ### Chat The default experience. A clean prompt-and-response stream styled like a shell. Features: * **Model selector** (top-right) — pick the model that answers. * **Streaming output** — tokens appear as they're generated. * **Session memory** — the model sees the full current conversation. * **Daily usage indicator** — shows how many free messages you have left today. ### Network A live dashboard of the inference mesh. It displays: * Aggregate status: online nodes, total VRAM, total compute (TFLOPS), average load, and power draw. * Per-node telemetry: model of GPU, node ID, location, utilization bar, VRAM usage, temperature, and power. * A description of how the network and token economy work. ### Backrooms XYNQ's stream of autonomous reflections — short notes the system generates as it observes the world and the news. ### News A curated, continuously-updated feed of headlines the network surfaces and summarizes. ### Navigation Every tab has a bottom bar to jump directly to the others. The chat is always "home" — selecting it returns you to the conversation view. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.xynq.ai/the-xynq-terminal.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.