OpenClaw Hosting

Self-host autonomous AI agents on cheap VPS and GPU

Complete RunPod Guide for OpenClaw Hosting

This guide shows you how to deploy OpenClaw on RunPod — a GPU cloud for AI provider with plans starting at $0.20/hr (RTX 3090). We cover plan selection (RTX 3090, 4090, A100, H100 on demand and spot), regions (Community Cloud and Secure Cloud), the install steps and the price-to-performance ratio you should expect.

Why RunPod for OpenClaw?

RunPod's key strength for OpenClaw is lowest GPU $/hour for OpenClaw LLM inference. Combined with RTX 3090, 4090, A100, H100 on demand and spot, it is a strong choice for operators who want to run autonomous AI agents without overpaying for managed services.

RunPod pricing for OpenClaw

Plans on RunPod start at $0.20/hr (RTX 3090). For a single OpenClaw agent doing text-only work (Telegram, WhatsApp, support), the entry plan is sufficient. Heavier workloads with browser automation or local model inference should jump to a mid-tier plan with more vCPU and RAM.

Step-by-step OpenClaw install on RunPod

1) Provision a RunPod instance with Ubuntu 24.04. 2) SSH in and install Docker. 3) Pull the OpenClaw container and mount a persistent volume. 4) Configure your model API keys or local LLM endpoint. 5) Open the agent port behind a TLS reverse proxy. End-to-end setup on RunPod typically takes 25 minutes.

Benchmarks and gotchas

In our benchmarks, RunPod delivers consistent performance for OpenClaw workloads. Watch for: bandwidth caps on entry plans, snapshot pricing if you run frequent backups, and region selection — pick a datacenter close to the LLM API endpoint or your end users to minimize latency.