Codex models repeatedly return "Selected model is at capacity" / "servers are currently overloaded" on ChatGPT Pro account with usage remaining

What version of Codex CLI is running?

v0.153.4

What subscription do you have?

ChatGPT Pro x20

Which model were you using?

All

What platform is your computer?

No response

What terminal emulator and version are you using (if applicable)?

No response

Codex doctor report

What issue are you seeing?

Selected model is at capacity. Please try a different model.
Our servers are currently overloaded

What steps can reproduce the bug?

Description

I am experiencing persistent Codex failures on a ChatGPT Pro account even though substantial weekly usage remains available.

The issue reproduces when using the official Codex CLI directly, without any custom proxy or third-party model provider.

Multiple Codex models are affected.

Environment
Plan: ChatGPT Pro
Codex CLI: v0.153.4
Platform: macOS
Authentication: Official ChatGPT account login
Weekly allowance at time of testing: approximately 65% remaining
Reproduction steps
Log in to Codex CLI using the ChatGPT Pro account.
Start a new empty session.
Select one of the affected models.
Send a minimal prompt:
reply only OK
The request fails even though there is plenty of usage allowance remaining.
Results
gpt-5.6-sol

The request fails with:

Selected model is at capacity. Please try a different model.
gpt-5.6-luna

The request also fails with:

Selected model is at capacity. Please try a different model.
gpt-5.6-terra

The WebSocket connection fails first:

Falling back from WebSockets to HTTPS transport.

The HTTPS fallback also fails:

stream disconnected before completion: An error occurred while processing your request.
You can retry your request, or contact us through our help center if the error persists.

OpenAI request IDs:

e66d938c-eea0-4e88-bf60-e865cb95e801
2dbe8a9a-9bee-4896-a313-22c0489cf01f
Additional upstream evidence

The same ChatGPT Pro account is also used through a self-hosted gateway for testing.

The gateway captured the raw upstream error response returned by the OpenAI backend:

Our servers are currently overloaded. Please try again later.

Another OpenAI-generated request ID associated with an upstream failure:

66496861-1782-4847-ae50-39b75ffb420b

The upstream responses observed include:

429
502
503

The gateway is not the root cause because the same failures can be reproduced directly using the official Codex CLI.

Usage status

/status reports that the ChatGPT Pro account still has substantial weekly allowance remaining:

Weekly limit: 65% left

At one point, /status also showed:

GPT-5.3-Codex-Spark

5h limit: 100% left
Weekly limit: 100% left

However, gpt-5.3-codex-spark later disappeared from the model selection list even though its allowance was still shown in /status.

Expected behavior

Codex should process requests normally while usage allowance remains available, or return a clear account/rate-limit message if an account-specific restriction is being applied.

Actual behavior

Multiple models repeatedly return capacity, overload, stream-disconnection, and HTTP 429/502/503 errors.

The behavior appears to be account-specific, model-routing-specific, or related to a backend capacity pool rather than exhausted weekly usage.

Request

Could the Codex team please check the backend traces associated with these OpenAI request IDs?

e66d938c-eea0-4e88-bf60-e865cb95e801
2dbe8a9a-9bee-4896-a313-22c0489cf01f
66496861-1782-4847-ae50-39b75ffb420b

It would be helpful to know whether this account is affected by:

an account-level temporary restriction,
a model entitlement/routing issue,
an overloaded backend pool,
or another Codex service-side issue.

What is the expected behavior?

No response

Additional information

No response

Start by reproducing the failure in the official Codex CLI with a minimal prompt and review the reported 429, 502, and 503 responses. Use the three OpenAI request IDs in the issue to investigate the backend traces; done means identifying the account, entitlement, routing, or capacity cause and providing a clear resolution.