OpenClaw Cost Optimization Guide — Reduce LLM API Spend Without

OpenClaw's LLM API costs can creep up quickly if you're not thoughtful about configuration. I've seen people spend $50-200/month when the same workload could run on $10-20 with smart optimization. Here's how to cut costs without degrading the agent's usefulness.

Understand Where the Money Goes

Before optimizing, audit your actual usage. Check your LLM provider dashboard and identify:

• Which operations consume the most tokens
• Which models you're using for which tasks
• How frequently each cron job fires
• Whether context windows are padded with unnecessary content

Right-Model Routing

The biggest cost lever: use cheaper models for simpler tasks.

# Use lighter model as default for routine crons
openclaw config set cron.default_model anthropic/claude-haiku-3-5

Route tasks by complexity:

• Claude Haiku / GPT-4o-mini: Monitoring, classification, simple summaries, routing decisions
• Claude Sonnet / GPT-4o: Research synthesis, content generation, code review
• Claude Opus: Complex reasoning, architectural decisions, high-stakes analysis only

Reduce Cron Frequency

Do you really need that competitor price check every 6 hours? Most metrics that matter can be checked daily or weekly:

# Change from every 6 hours to once daily
--schedule "0 9 * * *"  # instead of */6 * * * *

# Change from daily to weekly for slow-moving data
--schedule "0 9 * * 1"  # Weekly on Monday

Trim Context Windows

Every token in the context window costs money. Common culprits:

• Loading entire MEMORY.md when only a summary is needed
• Including full file contents when the agent only needs a section
• Repeating context that's already in the system prompt

Use targeted reads: "Read only the last 30 days from memory/notes.md" instead of loading the full file.

Local Model for Routine Tasks

brew install ollama
ollama pull llama3.2

# Configure specific crons to use local Ollama
openclaw config set cron.hex-competitor-scan.model ollama/llama3.2

Llama 3.2 handles monitoring, classification, and simple summaries well at zero cost. Reserve paid API calls for tasks that genuinely need better reasoning.

Batch Processing

Instead of running 10 separate crons for 10 clients, batch them into one task that processes all 10 in a single call. One LLM call with a larger prompt costs much less than 10 smaller calls with repeated system context.

OpenRouter for Cost Comparison

openclaw config set llm.provider openrouter
openclaw config set llm.apiKey YOUR_OPENROUTER_KEY
openclaw config set llm.model google/gemini-flash-1.5  # Often 10x cheaper than Claude

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