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[GPT-5.6 Luna xhigh] Severe weekly quota drain, long stalls and capacity errors since Sep 14 #45733

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Description

@ZMConcepts

Summary

Since September 14, 2026 (Europe/Warsaw), Codex using GPT-5.6 Luna with Very High / xhigh reasoning has behaved very differently from my normal baseline.

In roughly one day, I have consumed almost my entire weekly Codex allowance. Under my normal workflow, the same weekly allowance usually lasts me about a full week.

At the same time, Luna xhigh has become much less reliable: it can spend a long time reasoning without producing useful progress, tasks stall or disconnect, and I sometimes receive Selected model is at capacity. Please try a different model.

Subscription

  • ChatGPT Plus
  • Codex access through my ChatGPT subscription

Model / reasoning

  • Model: GPT-5.6 Luna
  • Reasoning effort: Very High / xhigh

What issue are you seeing?

Starting on Sep 14, 2026, I observed all of the following while using Luna xhigh:

  • Luna can remain in a reasoning/thinking state for a very long time without making proportional progress.
  • Tasks sometimes stall, stop responding, or disconnect.
  • Requests can fail with:
Selected model is at capacity. Please try a different model.
  • The weekly usage allowance is being depleted dramatically faster than before.
  • In approximately one day, almost the entire weekly allowance was consumed.
  • Historically, with my normal development workflow, the weekly allowance lasted around seven days.

The sudden change in both reliability and quota consumption started at approximately the same time.

Why this looks abnormal

My workflow has not intentionally changed from a week-long usage pattern to one that should consume nearly the entire allowance in one day. The scale of the difference is large enough that normal run-to-run variation does not seem like a sufficient explanation.

Because Luna xhigh is also stalling and producing capacity errors, I am concerned that usage may be amplified by one or more of the following:

  • repeated retries after backend/capacity failures;
  • repeated reasoning/model turns while a task appears stalled;
  • context replay or compaction loops;
  • incorrect model weighting;
  • incorrect quota attribution/accounting;
  • account-specific routing/provisioning problems.

I cannot determine the root cause from the client side.

Steps to reproduce / observed sequence

  1. Sign in to Codex with a ChatGPT Plus account.
  2. Select GPT-5.6 Luna.
  3. Set reasoning to Very High / xhigh.
  4. Use Codex for normal development work.
  5. Observe some requests spending a long time reasoning or stalling.
  6. In some cases observe Selected model is at capacity. Please try a different model.
  7. Check weekly usage before and after the work period.
  8. Observe the weekly allowance falling dramatically faster than the historical baseline.

Expected behavior

  • Luna xhigh should complete or fail requests cleanly rather than remain stuck for long periods.
  • Capacity failures should not trigger hidden/repeated work that consumes disproportionate quota.
  • Weekly usage should remain broadly consistent with comparable historical usage.
  • A workload that normally fits within approximately one week should not suddenly consume almost the entire weekly allowance in about one day without a clear explanation.

Actual behavior

  • Long reasoning periods with little/no visible progress.
  • Stalled/disconnected tasks.
  • Intermittent capacity errors.
  • Nearly the entire weekly allowance consumed since Sep 14 despite a historical baseline of roughly one week for comparable usage.

Requested investigation

Please correlate my account's server-side telemetry for the affected Sep 14-15 window and check:

  1. quota charged specifically to GPT-5.6 Luna xhigh;
  2. retries caused by capacity/backend errors;
  3. hidden/background model calls;
  4. repeated context replay or compaction;
  5. model weighting and cached-input treatment;
  6. whether any requests were routed to the wrong quota bucket or entitlement state;
  7. whether stalled/failed requests were still consuming quota repeatedly.

If the server-side accounting shows that quota was consumed incorrectly because of retries, routing, background work, or another bug, please restore the incorrectly consumed allowance.

It would also be very useful to expose per-task/per-model quota attribution so users can see exactly what consumed the weekly allowance.

Related reports

This report may overlap with those issues, but I am filing it because the combination of Luna xhigh stalls + capacity errors + near-total weekly quota depletion within about one day appeared together beginning Sep 14, 2026.

Activity

  1. added
    bugSomething isn't working
    rate-limitsIssues related to rate limits, quotas, and token usage reporting
    model-behaviorIssues related to behaviors exhibited by the model
    connectivityIssues involving networking or endpoint connectivity problems (disconnections)
    on Sep 15, 2026
  2. github-actions commented on Sep 15, 2026

    @github-actions
    Contributor
  3. ZMConcepts commented on Sep 16, 2026

    @ZMConcepts
    Author

    Additional diagnostics / environment

    I submitted diagnostic feedback from the affected Codex environment so the issue can hopefully be correlated with server-side telemetry.

    Feedback ID: 01a08fc8-2905-7431-9b54-2c0094417cc9

    Environment

    • Codex App: 26.905.11957
    • Codex CLI: codex-cli 0.142.5
    • Operating system: Windows 10 Home 22H2
    • OS build: 19045.7725
    • Subscription: ChatGPT Plus
    • Model: GPT-5.6 Luna
    • Reasoning effort: Very High / xhigh

    Current usage state

    At the time of submitting the diagnostic feedback:

    • 5-hour usage limit: 77% remaining
    • Weekly usage limit: 10% remaining
    • Weekly reset: Sep 19, 2026 at 20:14 (Europe/Warsaw)

    This is consistent with the issue described above: my weekly Codex allowance has been depleted far faster than my historical baseline while using GPT-5.6 Luna with Very High/xhigh reasoning.

    Observed error

    I have also repeatedly encountered:

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

    The diagnostic feedback was submitted with Codex diagnostic logs attached.

    Please correlate Feedback ID 01a08fc8-2905-7431-9b54-2c0094417cc9 with the affected account/session and check whether quota was consumed by:

    • repeated backend/capacity retries;
    • stalled or failed requests;
    • hidden/background model calls;
    • repeated context replay or compaction;
    • incorrect model weighting;
    • incorrect quota attribution/accounting.

    If possible, please also verify whether the affected Luna xhigh requests were repeatedly charged while stalled or failing due to capacity.

  4. anipatke commented on Sep 23, 2026

    @anipatke

    I'm seeing what appears to be the same regression today (Sep 24, 2026, Australia/Sydney).

    • Model: GPT-5.6 Luna
    • Reasoning mode: Max
    • Workload: only a couple of normal code-review prompts
    • 5-hour usage consumed: approximately 20%
    • Historical baseline for comparable work before the recent update: approximately 1–2% of the 5-hour allowance

    That represents roughly a 10–20x increase in quota consumption for similar review work.

    There was no unusually large implementation task here — these were review prompts. Historically, this kind of workload barely moved the 5-hour meter. The current burn rate feels closer to what I would normally associate with substantially more expensive Sol-heavy usage.

    This may help distinguish the issue from long-running agent sessions: I'm seeing severe quota depletion even from a very small number of review requests.

    Please investigate whether there has been a recent change/regression in quota accounting, Luna Max model weighting, cached-context charging, repeated context processing, or retries/background calls.

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    bugSomething isn't workingconnectivityIssues involving networking or endpoint connectivity problems (disconnections)model-behaviorIssues related to behaviors exhibited by the modelperformancerate-limitsIssues related to rate limits, quotas, and token usage reporting

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