How to run OpenClaw agents for free using cloud APIs or local models

✍️ OpenClawRadar📅 Published: April 14, 2026🔗 Source
How to run OpenClaw agents for free using cloud APIs or local models
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This guide covers practical methods for running OpenClaw AI coding agents without spending money, based on a Reddit user's experience running one for over a month at zero cost.

Free cloud model setup

For users without dedicated hardware, free cloud API tiers provide the easiest starting point. The source mentions three main options:

  • OpenRouter: Sign up without a credit card for access to 30+ free models including Nemotron Ultra 253B (262K context), Llama 3.3 70B, MiniMax M2.5, and Devstral. Configuration uses JSON:
    {
      "agents": {
        "defaults": {
          "model": {
            "primary": "openrouter/nvidia/nemotron-ultra-253b:free"
          }
        }
      }
    }
    Alternatively, use OpenRouter's free router: "primary": "openrouter/openrouter/free"
  • Gemini free tier: Get an API key from ai.google.dev, then run openclaw onboard and select Google. The free tier is generous enough for casual daily use.
  • Groq: Fast inference with rate-limited free tier. Sign up, get an API key, and set GROQ_API_KEY.

The source notes that free cloud models train on your data, making them unsuitable for sensitive information. Rate limits become noticeable with 10-20+ daily interactions.

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Local models via Ollama

Ollama became an official OpenClaw provider in March 2026. Setup involves:

# install ollama
curl -fsSL https://ollama.com/install.sh | sh
# pull a model based on your hardware
ollama pull qwen3.5:27b # 20GB+ VRAM (RTX 3090/4090, M4 Pro/Max)
ollama pull qwen3.5:35b-a3b # 16GB VRAM (MoE model)
ollama pull qwen3.5:9b # 8GB VRAM (most laptops)
# run openclaw onboarding and pick Ollama
openclaw onboard

If auto-discovery fails or Ollama runs on a different machine: export OLLAMA_API_KEY="ollama-local"

Three critical configuration tips from the source:

  • Use the native Ollama URL (http://localhost:11434), NOT the OpenAI-compatible endpoint (http://localhost:11434/v1). The /v1 path breaks tool calling.
  • Set "reasoning": false in manual model configs. When enabled, OpenClaw sends prompts as "developer" role which Ollama doesn't support.
  • Set "api": "ollama" explicitly in provider config to ensure native tool-calling behavior.

The source notes that local models work well on beefy machines (Mac Studio, 3090/4090, 32GB+ RAM) for basic agent tasks. On laptops with 8GB running 9B models, performance is slower with lower quality ceilings. Qwen3.5 handles tool calling adequately for daily tasks.

Hybrid setup

The author's actual setup uses Ollama/Qwen3.5 27B locally for about 70% of daily tasks (file reads, calendar, summaries, quick lookups), with OpenRouter free tier as fallback for complex multi-step reasoning. Total monthly spend remains under $3.

The approach is specifically for users who want to spend literally nothing or close to it. For those wanting "cheap" rather than free, the source mentions DeepSeek V3.2 (~$1-2/day), Minimax ($10/month sub), and Kimi K2.5 as dirt-cheap alternatives that work well with OpenClaw.

📖 Read the full source: r/openclaw

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