Persistent "Selected model is at capacity" error prevents Codex usage

Description

I am consistently receiving the following error when trying to use Codex:

Selected model is at capacity. Please try a different model.

The issue is persistent rather than intermittent and is currently preventing me from using the selected model normally.

I would appreciate it if the team could confirm whether this is caused by model capacity, an account-level model access restriction, or another Codex-side issue.

Actual behavior

When I attempt to start or continue a Codex task, the request fails with:

Selected model is at capacity. Please try a different model.

Repeated attempts continue to produce the same result.

Expected behavior

The selected model should be available normally, or the UI should clearly indicate whether the issue is caused by:

• temporary model capacity
• usage/rate limits
• account eligibility/access restrictions
• another service-side limitation

Impact

This currently prevents me from using Codex normally and significantly affects my workflow.

Additional information

I can provide the following privately to OpenAI Support if needed:

• account email
• exact timestamps
• screenshots
• selected model
• Codex client/version
• request or diagnostic IDs

Please let me know what diagnostic information would be most useful for investigating this issue.

Screenshot

I have attached a screenshot showing the error.

The report does not identify a repository file, test, or entry point; it describes a persistent service-side capacity or access error. Start by determining whether this repository handles the reported error, and use the supplied model, client version, timestamps, and diagnostic IDs to reproduce or classify it. Done would require a confirmed cause and a repository change, but no such change is specified.