Skip to main content

​
Local models

Local is doable, but OpenClaw expects large context + strong defenses against prompt injection. Small cards truncate context and leak safety. Aim high: ≥2 maxed-out Mac Studios or equivalent GPU rig (~$30k+). A single 24 GB GPU works only for lighter prompts with higher latency. Use the largest / full-size model variant you can run; aggressively quantized or “small” checkpoints raise prompt-injection risk (see Security). If you want the lowest-friction local setup, start with Ollama and openclaw onboard. This page is the opinionated guide for higher-end local stacks and custom OpenAI-compatible local servers. Best current local stack. Load MiniMax M2.5 in LM Studio, enable the local server (default http://127.0.0.1:1234), and use Responses API to keep reasoning separate from final text. 
{  agents: {  defaults: {  model: { primary: "lmstudio/minimax-m2.5-gs32" },  models: {  "anthropic/claude-opus-4-6": { alias: "Opus" },  "lmstudio/minimax-m2.5-gs32": { alias: "Minimax" },  },  },  },  models: {  mode: "merge",  providers: {  lmstudio: {  baseUrl: "http://127.0.0.1:1234/v1",  apiKey: "lmstudio",  api: "openai-responses",  models: [  {  id: "minimax-m2.5-gs32",  name: "MiniMax M2.5 GS32",  reasoning: false,  input: ["text"],  cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },  contextWindow: 196608,  maxTokens: 8192,  },  ],  },  },  }, }
Setup checklist
  • Install LM Studio: https://lmstudio.ai
  • In LM Studio, download the largest MiniMax M2.5 build available (avoid “small”/heavily quantized variants), start the server, confirm http://127.0.0.1:1234/v1/models lists it.
  • Keep the model loaded; cold-load adds startup latency.
  • Adjust contextWindow/maxTokens if your LM Studio build differs.
  • For WhatsApp, stick to Responses API so only final text is sent.
Keep hosted models configured even when running local; use models.mode: "merge" so fallbacks stay available.

​
Hybrid config: hosted primary, local fallback

{  agents: {  defaults: {  model: {  primary: "anthropic/claude-sonnet-4-6",  fallbacks: ["lmstudio/minimax-m2.5-gs32", "anthropic/claude-opus-4-6"],  },  models: {  "anthropic/claude-sonnet-4-6": { alias: "Sonnet" },  "lmstudio/minimax-m2.5-gs32": { alias: "MiniMax Local" },  "anthropic/claude-opus-4-6": { alias: "Opus" },  },  },  },  models: {  mode: "merge",  providers: {  lmstudio: {  baseUrl: "http://127.0.0.1:1234/v1",  apiKey: "lmstudio",  api: "openai-responses",  models: [  {  id: "minimax-m2.5-gs32",  name: "MiniMax M2.5 GS32",  reasoning: false,  input: ["text"],  cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },  contextWindow: 196608,  maxTokens: 8192,  },  ],  },  },  }, }

​
Local-first with hosted safety net

Swap the primary and fallback order; keep the same providers block and models.mode: "merge" so you can fall back to Sonnet or Opus when the local box is down.

​
Regional hosting / data routing

  • Hosted MiniMax/Kimi/GLM variants also exist on OpenRouter with region-pinned endpoints (e.g., US-hosted). Pick the regional variant there to keep traffic in your chosen jurisdiction while still using models.mode: "merge" for Anthropic/OpenAI fallbacks.
  • Local-only remains the strongest privacy path; hosted regional routing is the middle ground when you need provider features but want control over data flow.

​
Other OpenAI-compatible local proxies

vLLM, LiteLLM, OAI-proxy, or custom gateways work if they expose an OpenAI-style /v1 endpoint. Replace the provider block above with your endpoint and model ID: 
{  models: {  mode: "merge",  providers: {  local: {  baseUrl: "http://127.0.0.1:8000/v1",  apiKey: "sk-local",  api: "openai-responses",  models: [  {  id: "my-local-model",  name: "Local Model",  reasoning: false,  input: ["text"],  cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },  contextWindow: 120000,  maxTokens: 8192,  },  ],  },  },  }, }
Keep models.mode: "merge" so hosted models stay available as fallbacks.

​
Troubleshooting

  • Gateway can reach the proxy? curl http://127.0.0.1:1234/v1/models.
  • LM Studio model unloaded? Reload; cold start is a common “hanging” cause.
  • Context errors? Lower contextWindow or raise your server limit.
  • Safety: local models skip provider-side filters; keep agents narrow and compaction on to limit prompt injection blast radius.