AI agent desktop workbench built on the Kun runtime. Code mode for project automation, Write mode for document editing, phone connection for IM and scheduled tasks — every token goes where it matters.
DownloadDeepSeek GUI is a local desktop workbench for developers and frequent AI users. It uses Kun as the only runtime and turns the terminal agent experience into an easier, longer-lived application. Choose a workspace, start a task, watch reasoning and tool calls stream in, review file changes, and approve sensitive actions when needed.
The goal is not to ship another chat wrapper. The goal is to make DeepSeek feel like a reliable desktop partner for real project work. Kun's core advantage is high token ROI: the same context budget spends less on repeated prefixes, giant tool catalogs, and runaway output, and more on the information that actually moves the task forward.
Three modes that turn DeepSeek into a full-project agent.
Choose a project directory, start a task, and watch Kun read, edit, and create files. Every change is reviewed inline before it lands.
A dedicated writing workspace with Markdown file tree, live preview, inline completion, and selection-based agent actions for document work.
Connect Feishu, Lark, or WeChat. Run independent IM agents, local webhooks, relays, and scheduled tasks that execute while your computer is awake.
Kun makes token economy the default behavior of the agent loop, not a cleanup step after the fact.
Stable system prompts, tool schemas, and immutable prefixes make DeepSeek-native cache hits more likely. Long sessions stop paying for the same background.
When MCP catalogs are large, Kun searches for relevant tools first, then describes and calls the target tool instead of sending every schema on every turn.
Long tool results, lengthy arguments, base64 payloads, repeated tool loops, and low-value history are bounded. Code, paths, errors, decisions, and open tasks are preserved.
Runtime telemetry tracks cache hit/miss, token usage, and estimated savings. The GUI surfaces Token economy savings so cost return is observable over time.
A complete desktop workbench around the Kun local runtime.
Multi-session streaming chat with reasoning traces, tool calls, approval requests, and file diffs in one interface.
Select a local directory per task, manage sessions by workspace, preview files, open in editor, and switch Git branches.
Inline diffs and a side review panel capture every file change the agent makes. Review, approve, or roll back in-app.
Create Skills, save MCP configurations, add common tools, and open the config directory for further management — all from the GUI.
Draft requirements with background, goals, and acceptance criteria. Let AI clarify and research, then generate an implementation plan.
Review uncommitted changes, specify base branches or commits, and view results as actionable finding cards.
The fastest answers to the questions people ask first.
Kun is the only active local agent runtime. It is a standalone TypeScript package that starts a local HTTP/SSE service as the boundary between GUI and agent loop.
macOS (.dmg/.zip), Windows (.exe), and Linux (.AppImage). Source builds are also available.
Yes. Model calls use your own DeepSeek API Key. Everything else stays local — settings, session state, logs, and runtime config.
Token ROI measures how much useful work each token accomplishes. Kun optimizes by stabilizing prefixes, compressing low-value context, and searching tools on demand instead of sending every tool schema.
Every claim on this page is grounded in the GitHub repository or linked documentation.