How to Use ChatGPT in OpenClaw (and Reduce Your Cost)
If you're already paying for ChatGPT, you might be paying twice without realizing it.
A lot of builders run OpenClaw with token-based API billing while also keeping a ChatGPT subscription active. The smarter move? Connect OpenClaw to ChatGPT Codex via OAuth and use your subscription-backed access first, with fallbacks only when needed.
Why this setup helps reduce cost
- You avoid defaulting to per-token API spend for day-to-day coding tasks.
- You keep your existing OpenClaw channels, memory, and cron jobs intact.
- You can set fallback models only for overflow scenarios (quota/rate limit windows).
Prerequisites
- OpenClaw installed and running
- Active ChatGPT subscription (Plus/Pro/Team)
- Terminal access (SSH if hosted remotely)
Step 1 - Start onboarding with Codex OAuth
openclaw onboard --auth-choice openai-codex
When prompted with the risk acknowledgment, continue. It's informing you about potential behavior differences between providers, not a failure condition.
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Step 2 - Keep your current config (critical)
When the wizard asks how to handle existing values, choose:
- Use existing values
Do not choose reset unless you intentionally want to wipe channels/memory/cron settings.
Step 3 - Complete OAuth correctly
- Copy the OAuth URL printed in terminal
- Open it in your browser
- Sign in to your OpenAI/ChatGPT account and authorize
- After redirect to
localhost:1455, copy the full URL from your browser bar (including?code=...) - Paste it back into your terminal
That callback URL is what finalizes token exchange for OpenClaw.
Step 4 - Set Codex as primary model
openclaw models set openai-codex/gpt-5.3-codex
Then verify:
openclaw models status --plain
You should see openai-codex/gpt-5.3-codex as active and token status healthy.
Step 5 - Add fallback for uninterrupted usage
If you hit subscription quota windows, fallback models keep automation alive:
openclaw models fallbacks add openrouter/google/gemini-3-flash-preview
This hybrid strategy is where most teams squeeze the best cost/performance ratio.
Troubleshooting (fast fixes)
OAuth opens but authorization fails
Revoke OpenClaw from your OpenAI connected apps, then rerun onboarding:
openclaw onboard --auth-choice openai-codex
Model appears unavailable after auth
Check model catalog:
openclaw models list --all
If needed, clear stale fallbacks and set primary again:
openclaw models fallbacks clear
openclaw models set openai-codex/gpt-5.3-codex
Token expired / stopped working
Re-authenticate:
openclaw models auth login --provider openai-codex
Important operational rule
Don't ask an active OpenClaw agent session to reconfigure OpenClaw itself (onboarding/model/auth changes). Run those commands in a separate terminal to avoid circular dependency failures.
Final take
If your goal is to reduce OpenClaw cost without sacrificing output quality, this is one of the highest-leverage config changes you can make: subscription-backed Codex as primary plus smart fallback strategy for edge cases.
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