How to Run OpenClaw for Free: Complete Zero-Cost Setup Guide (2026)

Why Run OpenClaw for Free?

Before diving into setup, let's be clear about what "free" means here. OpenClaw itself is open-source and always free to install. The cost comes from the AI models it uses — specifically, the API calls to providers like Anthropic, OpenAI, or Google. Every method in this guide eliminates those API costs, either by running models locally or by using provider free tiers.

The good news: OpenClaw's architecture was designed for model flexibility from day one. Switching between free and paid models is a one-line config change.

• Evaluation: Testing OpenClaw's capabilities before committing to a paid model
• Privacy: Keeping all data on your own hardware with zero cloud dependency
• Budget constraints: Students, hobbyists, or users in regions where API payments are difficult
• Development: Building and testing skills or integrations without burning tokens
• Offline use: Running an AI agent on air-gapped or intermittently connected systems

The Four Free Paths: Overview

Here's a quick comparison before we go deep on each method:

Ollama (Local): No internet required, needs 8GB+ RAM (ideally GPU), quality 6-8/10, speed 15-55 tok/s, no rate limits. Best for privacy and offline use.

OpenRouter Free: Internet required, minimal hardware needs, quality 7-9/10, speed 30-80 tok/s, 20 req/min limit. Best free quality overall.

Google Gemini Free: Internet required, minimal hardware needs, quality 7-8/10, speed 40-100 tok/s, 15 req/min limit. Best for large context tasks.

Groq Free: Internet required, minimal hardware needs, quality 7-8/10, speed 280-1000 tok/s, 1K req/min limit. Best for speed-critical tasks.

Let's set up each one.

Path 1: Ollama — Completely Free, Completely Private

Ollama lets you run open-source LLMs directly on your hardware. No API key needed, no internet required after initial model download, and zero usage limits. This is the most popular free path for OpenClaw users.

On Linux (including VPS), install with a single command. On macOS, use Homebrew. After installation, verify with ollama --version (expected 0.6.x or later).

Choose a model based on your RAM. llama3.1:8b (4.7GB, 6GB RAM) and qwen2.5:7b (4.4GB, 6GB RAM) are excellent all-rounders rated 4/5 for OpenClaw. phi3:mini (2.3GB, 4GB RAM) works on low-RAM devices. gemma2:9b (5.5GB, 8GB RAM) excels at reasoning. For complex tasks, llama3.3:70b (40GB, 48GB+ RAM) rates 5/5 but needs serious hardware.

Pull your chosen model (downloads once, works offline forever), then configure OpenClaw with the ollama/ prefix and localhost baseUrl. No API key needed — OpenClaw auto-detects the Ollama provider.

Restart the gateway and send a message through your configured channel. If you see responses, you're running OpenClaw for free.

curl -fsSL https://ollama.com/install.sh | sh

brew install ollama

ollama pull llama3.1:8b

ai:
  model: "ollama/llama3.1:8b"
  baseUrl: "http://localhost:11434"

openclaw gateway restart

Ollama Performance Reality Check

Let's be honest about what local models can and can't do compared to Claude or GPT-4o.

What works great locally: summarizing articles and emails, draft replies and rewrites, simple code generation and debugging, classification and tagging tasks, casual conversation, filling templates and forms.

What struggles locally (on 7-8B models): complex multi-step reasoning, long document analysis (context window limitations), advanced coding tasks (system design, large refactors), nuanced creative writing, tool use with many parameters.

Actual benchmarks: Mac Mini M2 (16GB) runs llama3.1:8b at 22 tok/s (great). RTX 3060 (12GB) hits 48 tok/s (excellent). Raspberry Pi 5 (8GB) manages phi3:mini at 4 tok/s (slow but works). VPS 4-core (8GB) runs qwen2.5:7b at 8 tok/s (acceptable). Mac Mini M4 Pro (24GB) handles gemma2:27b at 18 tok/s (great).

For a deeper dive on the Ollama setup specifically, see our OpenClaw + Ollama guide.

Path 2: OpenRouter Free Tier — Best Quality at Zero Cost

OpenRouter aggregates 300+ AI models through a single API, and as of 2026, it offers 29+ models completely free. This is the best quality-to-cost ratio you'll find because you get access to Llama 3.3 70B, DeepSeek R1, and Gemini Flash — models that genuinely compete with paid options.

Sign up at openrouter.ai (no credit card required), create an API key, and configure OpenClaw with the :free suffix on the model ID. The :free suffix is critical — it tells OpenRouter to route to free inference endpoints.

Best free models on OpenRouter for OpenClaw: meta-llama/llama-3.3-70b:free (best all-rounder, 30 tok/s, 128K context), deepseek/deepseek-r1:free (top reasoning and coding, 20 tok/s), google/gemini-flash-exp:free (long documents with 1M context, 60 tok/s), qwen/qwen3-coder-480b:free (code generation, 15 tok/s), and google/gemma-3-27b:free (multimodal and image understanding, 40 tok/s).

You can optionally set up model routing to send different task types to different free models for best-in-class quality across the board — all for free.

ai:
  model: "openrouter/meta-llama/llama-3.3-70b:free"
  apiKey: "sk-or-your-key-here"

ai:
  model: "openrouter/meta-llama/llama-3.3-70b:free"
  modelRouting:
    coding:
      model: "openrouter/qwen/qwen3-coder-480b:free"
    reasoning:
      model: "openrouter/deepseek/deepseek-r1:free"

Path 3: Google Gemini Free Tier — 1M Token Context for Free

Google offers a genuinely generous free tier for Gemini models through AI Studio. You get access to Gemini 2.0 Flash — a capable model with a massive 1 million token context window — without spending a cent.

Visit aistudio.google.com, sign in with any Google account, click Get API Key, and copy your key (starts with AIza). No credit card or billing account required.

Google's free tier limits as of March 2026: Gemini 2.0 Flash allows 15 requests per minute, 1M tokens per minute, 1,500 requests per day, with a 1M context window. Gemini 2.5 Pro (Experimental) offers 5 req/min, 250K TPM, 50 req/day, with a 2M context window.

15 requests per minute is tight for heavy use, but for a personal agent handling messages throughout the day, it's more than adequate. Most users send 30-80 messages per day — well within the 1,500 daily limit.

Gemini 2.0 Flash's killer feature at the free tier is its 1M token context window, making it uniquely suited for reading entire books, analyzing large codebases, processing long email threads, and working with extensive conversation histories. No other free option gives you this much context.

ai:
  model: "google/gemini-2.0-flash"
  providers:
    google:
      apiKey: "AIza-your-key-here"

Path 4: Groq Free Tier — Blazing Fast Inference

Groq offers the fastest inference speeds in the industry thanks to their custom LPU (Language Processing Unit) chips. Their developer plan provides free access with generous rate limits — perfect for OpenClaw users who value snappy responses.

Visit console.groq.com, sign up (no credit card required), create an API key (starts with gsk_), and configure OpenClaw.

Groq's free developer plan includes: Llama 3.1 8B at 560 tok/s, Llama 3.3 70B at 280 tok/s, GPT OSS 120B at 500 tok/s, GPT OSS 20B at 1000 tok/s, and Llama 4 Scout 17B at 750 tok/s. All with 128K context and 250-300K tokens per minute limits.

The speed difference is dramatic. Where Ollama on a mid-range laptop gives you 20 tok/s, Groq delivers 280-1000 tok/s. Responses feel nearly instant.

Groq's developer plan allows 1,000 requests per minute — far more generous than OpenRouter or Gemini free tiers. The bottleneck is tokens per minute (TPM), typically 250K-300K. For a personal agent, this is essentially unlimited.

ai:
  model: "groq/llama-3.3-70b-versatile"
  providers:
    groq:
      apiKey: "gsk_your-key-here"

The Hybrid Approach: Combining Free Tiers

The real power move is combining multiple free providers. If one hits a rate limit, OpenClaw falls back to another. Here's a production-tested hybrid config:

This gives you: Groq as primary for speed (1000 RPM limit), OpenRouter as first fallback for quality diversity, Gemini as second fallback for large context, and local Ollama as last resort (always available, no limits).

With this setup, you'd need to send hundreds of messages per minute before running out of free capacity. For any realistic personal use, this is genuinely unlimited and free.

ai:
  model: "groq/llama-3.3-70b-versatile"
  fallbackModels:
    - "openrouter/meta-llama/llama-3.3-70b:free"
    - "google/gemini-2.0-flash"
    - "ollama/llama3.1:8b"

Step-by-Step: Complete Free OpenClaw Setup from Scratch

If you're starting from zero, here's the full path from nothing to a running free agent.

Install OpenClaw via npm (recommended) or Docker. Run the onboarding wizard which walks you through initial setup — when it asks for a model provider, choose any free option from this guide.

Connect a channel. For Telegram (most popular free channel), get a bot token from @BotFather (free), then add it to your config with your Telegram user ID.

Configure your free model — pick any method from this guide. The simplest start is Groq with a free API key.

Start the gateway and send your first message. If you see a response, congratulations — you're running OpenClaw for free.

Total time: about 10 minutes. Total cost: $0.

# Option A: npm (recommended)
npm install -g openclaw

# Option B: Docker
docker pull ghcr.io/nichochar/openclaw:latest

openclaw onboard

channels:
  telegram:
    botToken: "your-bot-token-from-botfather"
    allowedUsers:
      - your_telegram_user_id

ai:
  model: "groq/llama-3.3-70b-versatile"
  providers:
    groq:
      apiKey: "gsk_your-key-here"

openclaw gateway start

Cost Comparison: Free vs Paid

Let's put real numbers on what "free" saves you. A typical personal OpenClaw user sends 50-100 messages per day, generating roughly 100K-300K tokens.

Free (Groq + OpenRouter): $0/month, quality 7-8/10, fast speed, rate limits only. Free (Ollama local): $0/month (plus ~$1-3 electricity), quality 6-7/10, moderate speed, no limits. Budget (DeepSeek V3): $2-5/month, quality 8/10. Standard (Claude Sonnet 4): $15-40/month, quality 9/10. Premium (Claude Opus 4): $50-150/month, quality 10/10. DoneClaw Managed: $29/month, quality 9-10/10, everything included.

The free tiers are surprisingly capable for personal use. You lose cutting-edge reasoning (Claude Opus, GPT-4.5 territory), but for 80% of daily tasks — email drafting, scheduling, research summaries, casual chat — free models handle things perfectly well.

For users who want premium quality without self-hosting headaches, DoneClaw's managed service at $29/month includes everything: hosting, models, updates, and support. But if you're the hands-on type, free works.

Troubleshooting Common Issues

Ollama "Connection refused" error: Ollama isn't running. Start it with 'ollama serve' or 'sudo systemctl start ollama'.

Ollama model runs but responses are garbage: Usually means the model is too large for your RAM and is swapping. Check with 'free -h' — if available RAM is less than model size, use a smaller model like phi3:mini (only needs 4GB).

OpenRouter "Rate limit exceeded" (Error 429): You're hitting 20 req/min on the free tier. Add a $1 credit to get 200 req/min, add a fallback model in config, or wait 60 seconds (OpenClaw auto-retries).

Gemini "API key not valid" (Error 400): Google AI Studio keys are region-restricted. Verify your Google account isn't a Workspace account with API restrictions, you're not in a restricted region, and the key wasn't revoked.

Groq slow responses: Check your internet connection (Groq requires cloud access), try a smaller model, or check Groq's status page for outages.

OpenClaw "No model configured": Your config is missing the model field. Run 'openclaw config edit' and add the ai section with your chosen model.

Docker: Ollama not accessible from container: Add 'host.docker.internal:host-gateway' to extra_hosts in docker-compose.yml, then use 'http://host.docker.internal:11434' as the baseUrl in OpenClaw config.

ollama serve
# Or if using systemd:
sudo systemctl start ollama

# In docker-compose.yml
services:
  openclaw:
    extra_hosts:
      - "host.docker.internal:host-gateway"

ai:
  model: "ollama/llama3.1:8b"
  baseUrl: "http://host.docker.internal:11434"

Optimizing Free Tier Performance

Getting the most out of free models requires a few tweaks. Here's what experienced users do.

Keep SOUL.md concise: Every character in SOUL.md gets sent with every message. On free tiers with rate limits, this matters. Aim for under 500 words.

Disable unnecessary features: Features like web search, heartbeats, and proactive checks consume tokens. Disable or set long intervals for heartbeats on free tiers.

Use model routing strategically: Send simple tasks to fast free models, complex ones to your best free model.

Limit context history: Fewer conversation turns means fewer tokens per request. Set maxContextMessages to around 10.

heartbeat:
  enabled: false  # Or set a long interval like 3600000 (1 hour)

ai:
  model: "groq/llama-3.1-8b-instant"  # Fast, simple tasks
  modelRouting:
    reasoning:
      model: "openrouter/deepseek/deepseek-r1:free"  # Complex reasoning

ai:
  maxContextMessages: 10  # Default is usually higher

When to Upgrade from Free

Free tiers are great for getting started, but be honest about their limitations. Consider upgrading when:

The beauty of OpenClaw's architecture is that upgrading is a single config line change. You can try paid models for a day, see the difference, and decide.

• Response quality isn't cutting it: If you're regularly disappointed with output quality, paid models like Claude Sonnet 4 or GPT-4o are a significant step up
• You need reliability: Free tiers can have outages, rate limits, or model changes without notice
• You're using it professionally: If OpenClaw saves you hours per week, $15-30/month for a better model is a no-brainer ROI
• You need advanced features: Some OpenClaw features like vision (image analysis), function calling reliability, and long-context reasoning work significantly better with premium models

Conclusion

Running OpenClaw for free in 2026 is not a compromise — it's a legitimate starting point that covers 80% of what most personal users need. The combination of Groq's speed, OpenRouter's model variety, Gemini's massive context window, and Ollama's privacy creates a free stack that would have been unthinkable even two years ago. Start with any single method from this guide. If it works for you, great — you've got a free AI agent. If you want more, upgrade one config line at a time. That's the beauty of OpenClaw's modular design. The best AI agent is the one you actually use. Don't let cost be the reason you don't start.

Frequently asked questions