What this error means
Model not found gpt-5.2 causes WebSocket reconnection loop in Codex CLI is a OpenAI Codex failure pattern reported for developers trying to fix openai codex cli crash and websocket loop when model is not found. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub issue #22368 reports that an invalid model reference causes the CLI to crash and reconnect via WebSocket infinitely rather than failing gracefully. Affects CLI stability when model availability changes on the backend.
Common causes
- When an invalid or unavailable model reference (e.g., gpt-5.2) is used, the Codex CLI enters an infinite WebSocket crash/reconnect loop instead of failing gracefully. This causes the CLI to become unresponsive and requires manual intervention. Backend model availability changes trigger this instability.
- GitHub issue #22368 reports that an invalid model reference causes the CLI to crash and reconnect via WebSocket infinitely rather than failing gracefully. Affects CLI stability when model availability changes on the backend.
Quick fixes
- Confirm the exact error signature matches
Model not found gpt-5.2 causes WebSocket reconnection loop in Codex CLI. - Check the OpenAI Codex account, local tool state, and provider configuration involved in the failing workflow.
- Compare the failing environment with a known working setup, then change one configuration value at a time.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.