OpenClaw is free, open-source software released under the MIT license — there are no licensing fees or subscriptions. However, running it requires paying for server hosting and AI model API calls. For most users, the total monthly cost falls between $6 and $200+, depending on server specs, AI model selection, and how many automated workflows you run.
OpenClaw logo on the project’s title page.
Key Takeaways
- OpenClaw itself is 100% free (MIT license) — all costs come from infrastructure and AI usage.
- Basic personal setups cost roughly $6–$13/month (cheap VPS + budget AI model).
- Small business workflows run $25–$50/month with mixed model routing.
- Heavy automation with premium models can exceed $200/month.
- AI token spend — not hosting — is the largest and most variable expense.
- Unmonitored or forgotten automations can silently inflate costs by 10–30%.
- Tools like ClawRouter and local models (via Ollama) can significantly reduce API costs.
Personal users running light automations typically spend $6–$13/month. Small teams land around $25–$50/month. Scaling operations with tens of thousands of AI calls per month push into the $50–$100 range, while heavy automation setups processing complex multi-agent workflows can exceed $100–$200/month — or significantly more if left unmonitored.
What You Actually Pay For
OpenClaw has no built-in charges. The two main expense categories are server hosting (keeping the software online 24/7) and AI model API calls (every automation step consumes tokens from external providers like OpenAI, Anthropic, or Google).
A common misconception is that “open source” means “zero cost.” The software is free, but the compute and intelligence behind it are not.
Hosting and Infrastructure Costs
OpenClaw needs a continuously running server or VPS to monitor triggers and execute workflows around the clock. Your server specifications directly set your baseline monthly bill.
| Server Tier | Specs | Typical Monthly Cost | Best For |
|---|---|---|---|
| Entry-level | 1–2 vCPU, 2–4 GB RAM | $5–$10 | Personal projects, light automation |
| Mid-range | 2–4 vCPU, 8 GB RAM | $10–$20 | Small teams, multiple workflows |
| High-performance | 4+ vCPU, 16+ GB RAM | $20–$40+ | Browser automation, multi-agent setups |
Several factors push hosting costs up or down beyond raw specs. Shared VPS plans are cheaper but can slow down under neighbor load. Dedicated resources guarantee consistent performance. Daily backups, higher uptime SLAs (above 99.9%), and failover configurations all add to the bill.
For most personal and small-team deployments, a $5–$15/month VPS is more than sufficient.
AI Model and Token Usage Costs
This is where the real variability lives. Every conversation, decision, and automation step OpenClaw performs triggers an API call to an external language model, consuming tokens. You pay separately for input tokens (your prompt and context) and output tokens (the model’s response), with output tokens typically costing 2–5× more.
Here’s how popular models compare:
| Model | Input Cost (per 1M tokens) | Output Cost (per 1M tokens) | Category |
|---|---|---|---|
| GPT-4o-mini | $0.15 | $0.60 | Budget |
| Llama 3.1 8B | $0.05 | $0.08 | Budget |
| Claude Haiku 4.5 | $1.00 | $5.00 | Mid-tier |
| GPT-4o | $2.50 | $10.00 | Mid-tier |
| Claude Opus 4.5 | $5.00 | $25.00 | Premium |
A single typical OpenClaw interaction — roughly 1,000 input tokens and 500 output tokens — costs about $0.00045 with GPT-4o-mini or $0.0075 with GPT-4o. At 1,000 interactions per month, that translates to $0.45 versus $7.50.
For light experimentation (a few dozen messages per week, simple automations), expect under $1/month in token costs. Heavy automation with thousands of multi-step workflows, browser sessions, and complex reasoning can reach $50–$150/month in API spend alone.
Model choice matters more than server size. Routing 80% of routine tasks to a budget model like GPT-4o-mini while reserving premium models for complex reasoning can cut API costs by 60–80%.
Monthly Cost by Usage Tier
| Usage Tier | AI Calls/Month | Hosting Cost | AI Token Cost | Total Monthly Cost |
|---|---|---|---|---|
| Personal | Under 5,000 | $5–$10 | $1–$6 | $6–$13 |
| Small Business | 5,000–10,000 | $7–$15 | $15–$35 | $25–$50 |
| Scaling Teams | 10,000–50,000 | $10–$20 | $35–$80 | $50–$100 |
| Heavy Automation | 50,000+ | $15–$25 | $80–$150+ | $100–$200+ |
Personal users running email triage, daily summaries, or occasional web research with GPT-4o-mini on a basic VPS stay comfortably under $13/month — less than a single Zapier Professional subscription.
Small business setups handling lead processing, content generation, and CRM syncing with a mix of 80% budget and 20% mid-tier models land in the $25–$50 range.
Scaling teams running automations across marketing, support, and internal ops with regular browser steps typically spend $50–$100/month, with most of that going to AI tokens.
Heavy automation — multi-agent orchestration, RAG pipelines, extensive browser automation — pushes past $100/month and can climb significantly higher. One reported extreme case of unmonitored “runaway” workflows hit $3,600/month.
How Automation Scope Drives Costs Up
The more tasks you automate, the more API calls OpenClaw makes. Each workflow trigger, each step in a multi-step process, and each tool invocation fires a separate request.
Particularly expensive patterns include browser automation sessions, parallel task execution, batch document processing, multi-agent orchestration, and large-context retrieval workflows. Browser automation is especially costly — even though OpenClaw reduces token usage by roughly 90% by parsing accessibility trees instead of sending screenshots, navigation still requires repeated model decisions.
A critical point beginners often miss: a workflow that triggers 10 times per day during testing may trigger 500 times per day once connected to live inputs. Start small, monitor daily for the first week, then scale gradually.
Hidden Costs to Watch For
Several expenses tend to sneak up on OpenClaw users after initial setup:
Backups ($0–$6/month): OpenClaw stores conversation history, memory files, and configurations. Weekly backups are often included free; daily backups typically cost around $6/month.
Storage growth ($2–$5/month): JSONL transcripts and Markdown memory files accumulate over time. An active deployment might generate 20–50 GB over six months at roughly $0.10/GB/month.
Monitoring tools ($0–$15/month): Free options like Grafana Cloud, Uptime Robot, and self-hosted Netdata cover most needs. Paid services like Datadog start around $15/host/month.
Idle automations (10–30% of AI spend): Forgotten test workflows quietly calling APIs are one of the most common cost leaks. Community reports indicate unused automations regularly account for 10–30% of monthly AI spend.
Phone integration (~$5/month): Adding a dedicated number for SMS or calling features adds a small but recurring charge.
How to Keep Costs Under Control
The most effective strategies for managing OpenClaw spending are straightforward.
Route tasks by model tier. Send classification, extraction, and short summaries to budget models. Reserve premium models for complex reasoning only. This alone can cut API costs by 60–80%.
Monitor token usage weekly. Set hard spending limits and enable alerts at 50%, 75%, and 90% thresholds. Use separate API keys per workflow to track exactly where costs originate.
Enable prompt caching. When the same instructions are reused, caching can reduce repeated input token costs by up to 90%. Structure frequently used prompts with static instructions first and variable input at the end to improve cache hit rates.
Use cost-reduction tools. ClawRouter can automatically direct simple queries to cheaper models. Running local models through Ollama eliminates API costs entirely for suitable tasks.
Audit active automations regularly. Disable or remove test workflows you’re no longer using. This is one of the simplest ways to stop budget leaks.
Development vs. Production: Is a Separate Environment Worth It?
Running a separate dev environment roughly doubles infrastructure costs — adding $5–$20/month for a test VPS plus the tokens consumed during development. But the safety net is significant: if a misconfigured automation calls GPT-4o 5,000 times instead of 50, you want that caught in a test environment running budget models, not in production with premium ones.
Solo developers and small projects often skip separate environments to save money, accepting the risk. A practical middle ground is using production hardware but switching to cheaper AI models during testing.
Bottom Line
OpenClaw’s actual monthly cost depends almost entirely on two decisions: which AI models you use and how many automations you run. The software itself costs nothing. For personal projects, $6–$13/month covers everything. For business use, expect $25–$100/month depending on scale. Heavy automation users should budget $100–$200+ and invest time in model routing and usage monitoring to keep spending predictable.
If you are interested in this topic, we suggest you check our articles:
- Can You Use GenAI Models Without Ever Needing a Subscription?
- AI Models and Their Features: ChatGPT vs Grok vs Claude
Sources: Hostinger, DEV, 1bcMax on GitHub,
Written by Alius Noreika
