We have all heard and seen the buzz surrounding Openclaw, starting from its name controversy and evolution: Clawdbot -> Moltbot -> Openclaw. Every setup on Youtube is hinging on using APIs be it OpenAI, Anthropic, Google and the rest. Calling APIs with the Openclaw is and will be pretty expensive, so I decided to experiment with a local setup — LMStudio.
My hardware of choice is my Lenovo Thinkpad which I configured its OS to be Linux rather than windows that it came with, first thing I did was installing LMStudio. It was a little bit hard for me to do since I am still finding my way around core Linux OS instead of WSL and I found this video which helped me with installing LMStudio.
Next was to select a model, due to the nature of my hardware, I had to go with a quantized version of GLM-4.7 Flash model. After downloading, I used LMStudio chat to test and its response to my “hello” took 50.57 secs which was poor. But since I am experimenting with Openclaw, why not.
Next step was following Openclaw docs to install and set it up. I installed Openclaw using
curl -fsSL https://openclaw.bot/install.sh | bash
Following this, I selected manual configuration. Halfway through, I realized that I kept skipping some configs because I wasn’t sure what to make of them. After I got to the end, a whole lot was missing — from skills to model, to model provider to token. I didn’t find where to add my local model, so I decided to mess with the openclaw.json file. Opening it, I made the following modifications:
{
"meta": {
"lastTouchedVersion": "2026.1.29",
"lastTouchedAt": "2026-01-31T02:01:52.403Z"
},
"wizard": {
"lastRunAt": "2026-01-31T02:01:52.399Z",
"lastRunVersion": "2026.1.29",
"lastRunCommand": "onboard",
"lastRunMode": "local"
},
"models": {
"providers": {
"lmstudio": {
"baseUrl": "http://127.0.0.1:1234/v1",
"apiKey": "lm-studio",
"api": "openai-responses",
"models": [
{
"id": "glm-4.7-flash",
"name": "GLM-4.7 Flash",
"reasoning": true,
"input": ["text"],
"cost": {
"input": 0,
"output": 0
},
"contextWindow": 20000,
"maxTokens": 8192
}
]
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "lmstudio/glm-4.7-flash"
},
"workspace": "/home/Ubuntu/.openclaw/workspace",
"compaction": {
"mode": "safeguard"
},
"maxConcurrent": 4,
"subagents": {
"maxConcurrent": 8
}
}
},
"messages": {
"ackReactionScope": "group-mentions"
},
"commands": {
"native": "auto",
"nativeSkills": "auto"
},
"hooks": {
"internal": {
"enabled": true,
"entries": {
"session-memory": {
"enabled": true
}
}
}
},
"gateway": {
"port": 18789,
"bind": "loopback",
"mode": "local",
"auth": {
"mode": "token",
"token": "generate-your-token"
},
"tailscale": {
"mode": "off",
"resetOnExit": false
}
},
"skills": {
"install": {
"nodeManager": "npm"
}
},
}
The token, I had to generate it by running
openssl rand -hex 20
To be sure that what I had was working, I ran
openclaw setup
and it returned
Config OK: ~/.openclaw/openclaw.json
Workspace OK: ~/.openclaw/workspace
Sessions: OK: ~/.openclaw/agents/main/sessions
Finally, I ran the status
openclaw gateway status
and it returned a bunch of information amongst which was
Listening: 127.0.0.1:18789
Conclusion:
I am yet to do any other thing using Openclaw besides setting it up, I will write more as I use it and stretch its capabilities. I am using a relatively new hardware with little to no information on it, so the security risk associated with giving it access to the system is minimal for me.
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