> ┌─────────────────────────────────────────────────────────────────────────────┐
│ 之前:API Key 方式 │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ openclaw.json │
│ ┌─────────────────────────────┐ │
│ │ apiKey: ${AWS_BEARER_TOKEN} │──────┐ │
│ └─────────────────────────────┘ │ │
│ ▼ │
[Update 2026-02-02: nemotron-3-nano also performs well on same setup; see comment below]
This is a guide to setting up Clawdbot/Moltbot with a local Ollama model that actually works -- meaning it has good tool use and decent speed. The main requirement is 48GB of VRAM. I have yet to find a model that fits on less than this and still works on Moltbot.
The setup involves creating a tool-tuned variant of qwen2.5:72b and modifying a range of configs in Moltbot. At the end you'll get a local Moltbot instance that can use tools (exec, read, write, web search), read skills, and perform agentic tasks without any cloud API dependencies. On my system I get ~16 t/s and have yet to come across a tool/skill that my bot can't use.
Claude Opus wrote the first draft of this Gist, then I (a human) checked and edited it.
Run OpenCode as a persistent background service, accessible from any device via Tailscale.
- Access from anywhere — Start a task from your phone, check results from your laptop
- Sessions persist — Close the browser, come back later, your session is still there
- Multiple clients — Terminal TUI and browser can connect to the same session simultaneously
- Survives crashes — systemd restarts the server automatically