How to Optimize OpenClaw Costs: Cut Your Bill by 70% With This 2-Step Fix

This is Day 4 of the OpenClaw Bootcamp. Yesterday you connected cloud and local models to your agent. Today you will learn exactly where your token costs are going and how to cut them by 70% or more — without downgrading the quality of your agent's responses.

Watch the full video walkthrough with real cost breakdowns:

The $70 vs $17 Problem

An unoptimized OpenClaw deployment running 24/7 with a premium model can easily cost $70 or more per month. The same agent, doing the same work, with the same quality of conversation — optimized — costs around $17. The difference is not about what model you use. It is about how you use it.

Understanding Token Costs

Every interaction with an AI model costs tokens. There are two types:

• Input tokens — everything you send to the model: your system prompt, conversation history, memory files, and the current message.
• Output tokens — everything the model generates in response.

Input tokens are cheaper than output tokens, but they add up fast because your agent sends its entire context on every single API call. This is where most of your bill comes from.

Step 1: The Two-Tier Model Strategy

The biggest cost lever is using different models for different tasks. OpenClaw supports a primary and secondary model configuration:

• Primary model — your premium model (Claude Sonnet, GPT-4o) handles conversations, complex reasoning, and user-facing interactions.
• Secondary model — a cheaper model (Gemini Flash, GPT-4o-mini, or a local model) handles background tasks like heartbeat checks, memory management, and routine operations.

This single change typically cuts costs by 40-50% because background tasks make up the majority of your agent's API calls, and they do not need frontier-level intelligence.

The Heartbeat Math

Your agent's heartbeat is a periodic check-in where it reviews its state and decides if any proactive actions are needed. This is one of the biggest hidden costs.

Extending your heartbeat from 30 minutes to 60 minutes and routing it through your secondary model can save you $37/month alone.

Step 2: Prune Your Prompt

The second biggest cost driver is prompt bloat. Your agent sends its soul.md (system prompt), memory files, and conversation context with every API call. If your soul.md is 3,000 tokens when it could be 800, you are paying 3-4x more on every single interaction.

How to audit and prune:

• Review your soul.md — remove redundant instructions, verbose examples, and anything the model already knows how to do. Be concise.
• Clean up memory files — remove stale or duplicate memories. Each memory file is sent as context, so every byte costs tokens.
• Check conversation history length — if your agent keeps too many messages in context, old conversations inflate every new API call.

Setting Spending Limits

Never run an agent without spending limits. Both Anthropic and OpenAI let you set caps:

• Anthropic — offers a hard spending cap. Once you hit it, API calls stop. This is the safest option for preventing runaway costs.
• OpenAI — offers an alert threshold but not a hard cap. You get notified but calls do not stop automatically. Set your alert well below your actual budget.

The Advanced Move: Prompt Caching

Anthropic's prompt caching gives you a 90% discount on repeated input tokens. Since your system prompt and memory files are the same on every call, caching means you only pay full price for them once — subsequent calls use the cached version at 10% of the cost.

This is automatic with Anthropic's API and requires no configuration on your end. It is one of the reasons Claude is often more cost-effective than it appears at first glance.

Before vs After

Your Action Checklist

1. Set up a secondary model in your OpenClaw config
2. Route heartbeat and background tasks to the secondary model
3. Extend your heartbeat interval to 60 minutes
4. Audit and prune your soul.md
5. Clean up stale memory files
6. Set spending limits on your model provider account

What is Next

In Day 5, we move from optimization to expansion — connecting your agent to every channel it needs to live on: Telegram, WhatsApp, Discord, iMessage, Slack, and web chat.

Need help optimizing your OpenClaw deployment? OpenClaw Consult is the #1 ranked OpenClaw consulting team. We handle setup, cost optimization, and custom agent builds.