@jinfizzbuzz: Based on my several days of actual testing, Codex will automatically downgrade Astra to 5.6 Luna during crowded times. …

X AI KOLs Following Tools

Summary

The article introduces is-gpt-nerfed, a macOS tool that monitors Codex to detect automatic AI model downgrades, such as from Astra to 5.6 Luna during crowded times, without user notification.

Based on my several days of actual testing, Codex will automatically downgrade Astra to 5.6 Luna during crowded times. Some accounts will even be directly downgraded globally by default, with no notifications whatsoever, and it will likely charge according to Astra's pricing. If you have the same concerns, you can use the monitor I wrote, which checks every half hour by default. https://github.com/kiyoakii/is-gpt-nerfed…
Original Article
View Cached Full Text

Cached at: 09/17/26, 08:24 PM

Based on my several days of actual testing, Codex will automatically downgrade Astra to 5.6 Luna during crowded times. Some accounts will even be directly downgraded globally by default, with no notifications whatsoever, and it will likely charge according to Astra’s pricing. If you have the same concerns, you can use the monitor I wrote, which checks every half hour by default. https://github.com/kiyoakii/is-gpt-nerfed…


kiyoakii/is-gpt-nerfed

Source: https://github.com/kiyoakii/is-gpt-nerfed

is-gpt-nerfed: shrinkflation detector for Codex

English · 简体中文

You pick a model in Codex. This tells you whether that model is actually the one answering. If it isn’t, you get this:


🎉 Congrats! You've been nerfed! You asked for gpt-6-astra; the fingerprint says gpt-5.6-luna (91%). Enjoy the discount you didn't ask for.
Example output, not a real verdict.

Menu bar panel: status, active sessions with verdicts, fresh-session probe A session opened in place: fingerprint, earlier probes, evidence
The panel, and a session opened in place. Sample data, not real sessions.

all clear suspicious nerfed
All clear · Suspicious · Nerfed

What it checks

Everything runs on your Mac. Nothing is uploaded.

Codex records, for every turn, which model and reasoning effort it asked for. The plugin reads those records after each turn and flags what changed without you changing it: a model swap, a lower reasoning effort, a hidden internal model such as gpt-reserve, a smaller context window. A move to a newer or larger model is reported as well, since a rollout can go either way. This costs no tokens.

On a schedule, the plugin also forks your session three times, ephemerally, through the same app-server call the desktop uses for a side chat, with the session’s own model and reasoning effort. Each fork is asked for about 300 “random” numbers. A language model picks random numbers with a bias that is characteristic of the model. ModelTrace’s calibrated bank turns the three answers into a fingerprint (100 % accuracy with three answers in cross-validation), and the verdict compares that fingerprint with the model you selected:

verdictmeaning
Matchthe model you selected answered
Suspiciousthe fingerprint leans elsewhere, but not confidently; it stands until the next probe
Downgrade / Upgrade / Rerouteda confident mismatch: top candidate at 80 % or more, your model at 20 % or less, at least two answers
DowngradedCodex’s own records show a silent switch; no fingerprint needed
UpgradedCodex’s own records show a move to a newer or larger model
Unlistedyour model is not in the fingerprint bank yet
Invalidno usable answer (tool use, refusal, network); not a verdict, the row keeps its last one and offers Retry

A mismatch reaches you as a macOS notification, a message in the session, and a red face in the menu bar. A match is not announced.

Install

macOS 26. One line in Terminal installs the latest release and opens it:

curl -fsSL https://raw.githubusercontent.com/kiyoakii/is-gpt-nerfed/main/install-app.sh | sh

You can also download the disk image from Releases and drag IsGPTNerfed to Applications. The app is not notarized yet, so macOS blocks that first launch until you allow it under System Settings → Privacy & Security.

Click the face in the menu bar and press Install. That registers the bundled plugin with Codex and trusts its hooks. When a newer release is out, the footer says so and a notification arrives once; click it and the app downloads the new build, checks its checksum, replaces itself and relaunches.

Without the app, on any macOS:

git clone https://github.com/kiyoakii/is-gpt-nerfed ~/is-gpt-nerfed && cd ~/is-gpt-nerfed && ./install.sh

Say yes when it asks to trust the hooks. Codex runs no hook you have not trusted, and it does not tell you.

Requires a Codex with plugin hooks (desktop app or CLI; tested on 0.154) and the system python3. ./uninstall.sh removes everything.

Using it

The macOS interface supports English and Simplified Chinese, following the system’s preferred languages with English as the fallback. This includes app-generated evidence, progress messages and diagnostics shown by the app. User session titles, model IDs, reasoning-effort values and unrecognized external diagnostics keep their original text. Stored records, CLI output, notifications and ModelTrace’s calibrated probe prompts are unchanged.

Every session you work in is probed in the background after 30 minutes of activity. To probe a session right away, say $is-gpt-nerfed in it.

The menu bar panel lists the sessions of the last 48 hours with their last verdict. Click a session for its report (fingerprint, earlier probes, evidence) and right-click for actions. Each session has Probe and Retry, and the Fresh session row probes a brand-new session to show what a new session gets right now.

From a terminal: nerfed probe now (pick a session), nerfed report, nerfed explain <probe>, nerfed log --since 2h.

Settings are in the app, or nerfed config set <key> <value>:

keydefault
frequency30mper session: every N minutes of activity (30m) or every N turns (turns:8)
fresh_frequencymanualprobe a brand-new session every N minutes, whatever you are doing
modeautoauto probes in the background, nudge only reminds you
halt_on_mismatchfalseblock tools after a mismatch until you say resume
notify_on_ok, announce_okfalsealso report Match
hide_titlesfalsescreenshot mode: neutral session names, no account
check_updatestrueask GitHub for a newer release every 10 minutes

Accounts

Sessions are shared between Codex accounts, and a downgrade may be tied to the account rather than the session. Every probe is therefore tagged with the signed-in account (a hash, never the id). After you switch accounts, older verdicts show as “another account” and those sessions are probed again.

Limits

  • “The model you selected” is the model Codex asked for. If the server swaps the weights and keeps the name, only the fingerprint or a smaller context window can show it.
  • The bank is closed-set: a model outside it is mapped to its nearest look-alike.
  • A probe costs three short answers on your account. A fork that has not answered within five minutes is replaced once, so a slow model does not drop out of the sample.
  • A model or effort change made through Codex’s own settings is shown as a question (“was that you?”), because the plugin cannot tell whether you or Codex changed it.
  • The probes run in a private app-server process that identifies itself as the client it checks for (the desktop app, or the CLI), because the service may route by client. Anything else that differs between the desktop’s own connection and the probe’s is invisible to it.

Privacy

The plugin reads ~/.codex (session records, the models cache, and auth.json only for an account hash and a masked e-mail) and writes to ~/.codex/is-gpt-nerfed (probes, verdicts, log.jsonl). The forks are ordinary Codex inference under your account. The only network request of its own is one to GitHub every ten minutes for the latest release tag, while the app is open; switch it off in Settings and it makes none.

Credits

ModelTrace (xqy2006, MIT) for the fingerprint bank, scorer, prompts and the fork-and-verify sequence; hlwy-ai-checker for the random-number idea; simple-term-menu (MIT) for the session picker.

MIT license. Internals, build and contribution notes: docs/DEVELOPMENT.md.

Similar Articles

OpenAI is silently degrading some Astra / Codex accounts.

Reddit r/singularity

OpenAI is reportedly silently routing some Astra and Codex accounts to less capable models due to account activity restrictions, causing performance issues. The company has acknowledged limiting access based on activity, which some users find unethical, especially affecting a large number of Chinese users.

Okay Astra is insane.

Reddit r/openclaw

The user shares their experience where Astra quickly fixed bugs in a dashboard, outperforming Gemini 3.1 pro, and praises OpenAI's model capabilities.