Two $0 OpenClaw setups using free cloud models or local Ollama

An OpenClaw user reports running an agent for free for three weeks, handling about 70% of tasks previously paid for with Claude. The setup offers two paths: free cloud models with rate limits or local models via Ollama with zero ongoing costs.

Path 1: Free cloud models (no hardware needed)

This approach requires only an existing OpenClaw installation and free API tiers:

• OpenRouter free tier: Sign up at openrouter.ai with no credit card. Offers 30+ free models including Llama 3.3 70B, Nemotron Ultra 253B (262K context), MiniMax M2.5, and Devstral. Configuration example:

{
  "env": { "OPENROUTER_API_KEY": "sk-or-..." },
  "agents": {
    "defaults": {
      "model": {
        "primary": "openrouter/nvidia/nemotron-ultra-253b:free"
      }
    }
  }
}

For automatic model selection: "primary": "openrouter/openrouter/free"

• Gemini free tier: Google provides 15 requests per minute on Gemini Flash for free. Get an API key from ai.google.dev and run openclaw onboard, selecting Google as the built-in provider.
• Groq: Fast with rate-limited free tier suitable for basic agent tasks.

The catch: rate limits. For light to moderate daily use (10-20 interactions), pauses are barely noticeable. For 100+ tasks daily, this won't work.

Path 2: Local models via Ollama (truly $0, forever)

Ollama became an official OpenClaw provider in March 2026. This setup has no API keys, accounts, rate limits, or data leaving your machine.

Setup steps:

1. Install Ollama: curl -fsSL https://ollama.com/install.sh | sh
2. Pull a model based on your VRAM:
   • 20GB+ VRAM (RTX 3090, 4090, M4 Pro/Max): ollama pull qwen3.5:27b
   • 16GB VRAM: ollama pull qwen3.5:35b-a3b
   • 8GB VRAM (most laptops): ollama pull qwen3.5:9b
3. Run openclaw onboard and select Ollama, or use manual setup with export OLLAMA_API_KEY="ollama-local"

Qwen3.5 27B is noted as the current sweet spot for OpenClaw, handling tool calling well for daily agent tasks. The 35b-a3b mixture-of-experts variant runs at 112 tokens/second on an RTX 3090 by activating only 3B parameters at a time.

Manual configuration example:

{
  "models": {
    "providers": {
      "ollama": {
        "baseUrl": "http://localhost:11434",
        "apiKey": "ollama-local",
        "api": "ollama",
        "models": [
          {
            "id": "qwen3.5:27b",
            "name": "Qwen3.5 27B",
            "reasoning": false,
            "contextWindow": 131072,
            "maxTokens": 8192
          }
        ]
      }
    }
  },
  "agents": {
    "defaults": {
      "model": {
        "primary": "ollama/qwen3.5:27b"
      }
    }
  }
}

Important debugging notes:

• Use the native Ollama API URL (http://localhost:11434), NOT the OpenAI compatible one (http://localhost:11434/v1). The /v1 path breaks tool calling, causing raw JSON output as plain text.
• Set "reasoning": false in the model configuration.