How to Host OpenClaw for Free (Without Paying for API)

ByL.B. Kaelin

You want to run an OpenClaw agent without a monthly API bill. The search for “openclaw free | openclaw free hosting, openclaw ollama free” ends here. The solution is local inference with Ollama, which costs zero dollars for model calls.

As of April 2026, the OpenClaw community’s default path is Ollama Cloud’s free tier or running models on your own hardware. This guide covers both, from a Raspberry Pi gateway to a used GPU setup. The only cost is electricity and your existing computer.

We’ll start with the easiest, truly free option that requires no GPU, then show you how to scale up with local hardware if you have it. The goal is a self-hosted agent that never hits a paywall.

Before You Install: Check Your Hardware

OpenClaw itself is lightweight. The cost is in running the AI models. If you plan to run models locally with Ollama, your hardware determines what’s possible. If you don’t have the hardware, you can still run for free using Ollama’s cloud service.

Local Hardware Tiers for Ollama

  • No GPU / Raspberry Pi 5: Can run the OpenClaw gateway, but cannot practically run local models. Use with Ollama Cloud free tier or a cheap cloud API like DeepSeek.
  • Budget GPU (8GB VRAM, e.g., RTX 4060): Minimum for practical local use. Runs 7-8B parameter models (like Llama 3.1 8B) at good speed. This is the entry point for local agents.
  • Mid-range GPU (12GB VRAM, e.g., RTX 4070 Ti): Handles 12-14B models (like Qwen3 14B). Better reasoning for most tasks.
  • Sweet Spot (24GB VRAM, e.g., used RTX 3090): Best budget value. Runs 27-32B models (like Qwen3 32B) for serious local AI.
  • Apple Silicon Mac (16GB+ unified memory): Good performance for 7-14B models. Mac Studio can handle larger models.

If your hardware isn’t on this list, don’t install Ollama locally. Use the cloud path.

The Truly Free Path: No Hardware Required

If you don’t have a capable GPU, use Ollama Cloud. Install the Ollama app, sign in, and use cloud-hosted models. The free tier gives you light usage with one concurrent model, which is enough to get started at zero cost. This is the easiest free option.

What You Need

These are the specific tools for a free OpenClaw setup. You need one working model provider and a place to run the gateway.

  • Node.js 24 (or 22.14+): OpenClaw is a Node.js daemon. Version 24 is recommended. Older versions may fail.
  • A Computer or VPS: Any macOS, Linux, Windows (WSL2) machine, or a cheap VPS. The community’s go-to is a Hetzner CX22 (€4.15/mo, 2 vCPU, 4GB RAM) if you need a dedicated server.
  • Ollama (Installed and Running): Either locally for GPU inference or just the client for cloud models. Version 0.5.0 or later is required for cloud model support.
  • An Initial API Key (for Bootstrap): One free key to get OpenClaw running. This can be an OpenRouter free tier key, a temporary DeepSeek key, or any existing API key. You’ll use it once during setup, then switch to free providers.

Setting Up Your Environment

Phase 1: Bootstrap with a Free API Key

You need a working Claw to automate the switch to free providers. Get a key from OpenRouter’s free tier, it takes 30 seconds and doesn’t require a credit card.

First, get your OpenRouter key:

  1. Go to openrouter.ai and sign up.
  2. Navigate to “Keys” in your dashboard.
  3. Click “Create Key”. Copy the key that starts with sk-or-.

Now, install OpenClaw and run the setup wizard with that key.

curl -fsSL https://openclaw.ai/install.sh | bash

After the install script finishes, run the onboard wizard:

openclaw onboard

When prompted for your auth choice, select openrouter. Paste your OpenRouter API key when asked. Complete the rest of the wizard with the default options. This gets your Claw running immediately.

Phase 2: Let Your Claw Switch to Free Providers

Now that your Claw is running, you can instruct it to reconfigure itself for Ollama. This is the core community workflow: bootstrap with any key, then let the agent optimize.

If you have a local GPU and installed Ollama, give your Claw this instruction:

You are my OpenClaw agent. Switch my default model provider to Ollama running locally.
First, verify Ollama is running by checking `ollama list`. If it's not running, start it.
Then, update the OpenClaw configuration at ~/.openclaw/openclaw.json.
Set the default model to use the Ollama provider. Use the model 'gemma4' if it's available, or pull it.
Confirm the change by running `openclaw config get agents.defaults.model.primary` and report the new value.

What the Claw does: It checks your local Ollama service, pulls the `gemma4` model if needed, and edits the JSON5 config file to set `agents.defaults.model.primary` to `”ollama/gemma4″`. You’ll see it report the successful switch.

If you do NOT have a local GPU, use Ollama Cloud. First, sign in to Ollama from your terminal:

ollama signin

Then, give your Claw this instruction:

You are my OpenClaw agent. Switch my default model provider to Ollama Cloud.
Update the OpenClaw configuration to use a cloud model. Set the provider base URL to use the local Ollama client (which will route to cloud). Use the model ID 'kimi-k2.5:cloud'.
Confirm the change and verify the model is accessible.

What the Claw does: It configures OpenClaw to use your local Ollama client as a gateway to Ollama Cloud, setting the default model to a cloud-hosted one. Your inference now runs on Ollama’s servers for free (within tier limits).

Your OpenClaw agent is now running on a free model provider. The initial OpenRouter key remains in your config as a fallback, which is critical. If Ollama hits limits or goes down, your Claw won’t break silently.

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