How to Cut OpenClaw Agent Costs by 80% with Model Switching

A Reddit user spent two weeks manually logging every OpenClaw agent interaction to figure out where their money was going. The results are a clear blueprint for optimizing spend on AI agents.

The Breakdown

Over 14 days on a Telegram + Discord agent, token usage broke down as follows:

• Heartbeats (30-min polls) — 38% of usage. Running on Opus at ~$6.75/M tokens. Complete waste for a status ping.
• File reads and summaries — 29% of usage. Also on Opus. Flash handles these identically.
• Actual conversations — 22% of usage. Here model quality matters.
• Complex tasks — 11% of usage. Where Opus genuinely outperforms Flash.

In total, 67% of spend went to tasks where DeepSeek V4 Flash ($0.14/M) would deliver identical quality to Opus ($6.75/M effective after tokenizer).

The Fix: Default to Flash, Escalate Only When Needed

Set your primary model to deepseek/deepseek-v4-flash in openclaw.json:

"agents": {
  "defaults": {
    "model": {
      "primary": "deepseek/deepseek-v4-flash"
    }
  }
}

Then use /model anthropic/claude-opus-4-7 mid-session when you hit something truly hard. The switch is instant — no restart, same session. Type /model deepseek/deepseek-v4-flash when you're done to drop back to cheap.

Results

Costs dropped from ~$170/month to ~$35/month. The quality difference on heartbeats, file reads, and simple questions was literally zero.

The user notes that BetterClaw's free tier (with BYOK) now shows per-task API spend, which would have caught the heartbeat waste immediately. But the core move — switching primary to Flash and /model-ing up to Opus only when needed — is the real takeaway.