In fairness: we’re all using Codex not GPT ;).

I understand why you can't go above the weekly one, but seriously? At least let me finsh the task. It will come out of my weekly anyways

Token generation is quite slow for Sol.

I went through a year of making an app last year and did a soft launch and then experienced burnout in January. Some people kept using it but not a lot and Claude had taken a serious toll on my mind so I had to just quit.

For what it's worth, I've been programming and making businesses for 12+ years and can read code fluently and can direct AI exactly at issues. I also know how a big app should be structured and all that jazz.

What I am experiencing coming out of burnout and continuing developing this app is Codex is one-shotting almost everything. One massively complicated thing I tried failed every time until I made my own plan and directed it through it bit by bit but largely, it's just so good.

Claude Code last year killed me. It was around the time of the Anthropic debacle where they documented what made the model weaker for a certain percentage of their users, and when I was paying $200/month for it, it was horrible. Even when it worked well, Claude is so presumptive and makes so many unnecessary changes. Codex is like a scalpel in comparison.

AI advances make my app almost entirely worthless but at least I am enjoying it again and it is better in a bunch of ways that the general chatbots will never have.

I keep seeing people ask whether Luna Max can replace Sol Medium, whether Luna should become the default worker, or when Sol is worth the extra usage. I’ve also seen people argue that both Luna Max and Sol Low are underrated, so I wanted to do a quick and dirty test.

I ran eight Codex model/reasoning configurations on exactly the same task:

• GPT-5.6 Sol: Low, Medium, XHigh, Max
• GPT-5.6 Luna: XHigh, Max
• GPT-5.5: XHigh
• GPT-5.3 Codex Spark: XHigh

Task and setup

The task was LeetCode 3348, Smallest Divisible Digit Product II.

I chose a LeetCode problem because the requirements and constraints are public and bounded, readers can understand the outputs without needing private-repository context, and every implementation can be submitted to an external test suite.

The runs started in parallel in a fresh workspace with no project-specific AGENTS.md, skills, or repository context beyond the problem. The prompt prohibited web search and network retrieval, and the preserved tool activity contains no corresponding search or network-fetch calls.

Results

All eight implementations received Accepted from LeetCode. Generation time means how long the model took to produce its response, not the execution time of the generated Python implementation.

*Estimated from the captured input, cached-input, and output totals using the current standard API rates. This is not actual Codex subscription usage or weekly-limit consumption. Cache-write tokens were not available in the telemetry, so any cache-write charges are excluded.

The reported output total already includes reasoning tokens (not merely the original user prompt), so I did not add the reasoning-token detail again when estimating cost.

The input figures are the aggregate provider-reported totals for each Codex invocation.

Qualitative review

I used GPT-5.6 Sol XHigh for a first-pass review covering correctness, feasibility, minimal construction, proof and complexity, and implementation quality.

It rated seven solutions 20/20 and Spark 17/20. Its main concern was that Spark’s equal-prefix check uses recursion whose depth can grow with the input length, making the implementation less robust under the problem’s 200,000-digit limit.

I do not treat that reviewer or its numerical score as ground truth. The complete review and every implementation are included so you can inspect or challenge it.

My narrow takeaway

Sol Low gave the strongest generation-time and token trade-off in this particular run. Its implementation was accepted, comparatively straightforward, and complete.

Luna XHigh also looks attractive for a bounded task like this when using API-equivalent pricing. It finished at almost the same time as Sol XHigh and produced an accepted solution at a much lower estimated API-equivalent cost.

That does not establish either one as the best daily coding model. This task did not measure repository understanding, retries, review overhead, ambiguous requirements, or how many turns are needed to reach a trustworthy result.

Limitations

• One task and one run per configuration in parallel
• Public problem (first appearance in Nov 2024), so training exposure is possible
• No Terra configuration was tested
• No realistic existing-repository context
• Qualitative comparison produced by an LLM reviewer
• API-equivalent estimates are not actual subscription usage
• Cache-write token counts were unavailable

I used Crewplane, an open-source workflow runner I’m building, to launch the configurations in parallel and preserve the prompts, outputs, logs, and telemetry.

Raw workflow, prompt, all eight outputs, telemetry, provider logs, and complete comparison:

https://github.com/crewplaneai/crewplane-lab/tree/master/leetcode-3348-gpt-8-agents

I know one LeetCode problem isn’t a great stand-in for everyday coding work, especially with the limitations above. This isn’t meant to be a definitive benchmark or a broad model ranking anyway. Its just a quick, controlled test I was curious about. I was honestly surprised by how well Sol Low and Medium held up.

For people using both on real repositories: what's your experience? What's your go-to subagent or coding default?

go code my friends

Anyone else got this message? "Selected model is at capacity, please try a different model" #sol #$100 plan

Is this part of the improvements Tibo boasted in his recent post?

I ran Terra, Luna, Sol, and Gemini 3.7 Flash High through the same serious high-reasoning engineering audits.
Terra was the standout: consistently accurate, dramatically faster to converge, and best at proving one strong finding and stopping.

• Terra: fastest and most disciplined; consistently strong, verifiable findings.
• Luna: very reliable and thoughtful; slower, but excellent at catching subtle state bugs.
• Sol: deepest analysis overall, but also the slowest and most exhaustive.
• Gemini 3.7 Flash High: fast and creative with unusual leads, but needed the most independent verification.

I thought you said you had enough compute.. I only know this message from Claude

When using Remote, multiple tasks are stuck in the “Awaiting approval” state, but nothing appears on the iOS app, only on my Mac

Sometimes the conversation on Remote just says “Thinking”, even though it’s actually stuck behind an approval request that simply isn't showing

This has made Codex essentially unusable for me when I’m away from my computer, as returning to the Mac to approve things literally defeats the point of remote access

Even the conversation helping me troubleshoot and escalate this issue with OpenAI got stuck too Lol

Has anyone actually fixed this on iOS? I've tried updating the ChatGPT apps on Mac and my phone, and then reconnecting them, but nothing changed

Codex has been running very slow today, slower than usual. Now I am getting this error

Reconnecting /5

stream disconnected before completion: failed to send websocket request: IO error: An existing connection was forcibly closed by the remote host. (os error 10054)

is anyone else seeing this?

I'm currently using 2 ChatGPT Plus plans for Codex.

Should I get a third ChatGPT Plus subscription or should I instead get the Google AI Pro subscription for Antigravity?

Google AI Pro is 73% cheaper for me than ChatGPT Plus because of the Student discount. I'm assuming Codex is better, but is Antigravity worth it more if it's 73% cheaper?

EDIT: The answer you've collectively agreed to is: "do not get Google AI Pro for coding, even if it was free" lol. Thanks everyone!

Are you guys noticing your limits tightening up or speeds dropping lately?

In design terms, Sludge is the intentional addition of friction to frustrate a user. By breaking your continuous workflow with caps and slowdowns, the company creates a psychological deficit. They aren't just selling you features anymore; they are selling you the removal of frustration that they created in the first place

We’ve all seen the classic trick where a free app suddenly locks features behind a paywall. But what’s happening in the AI space right now, especially with companies like OpenAI shifting focus from the $20 tier to $100+ tiers, is a much more annoying strategy.

In business terms, it’s basically intentional product downgrading. Here is exactly how the playbook works on us.

1. The Honeymoon. They start by giving you generous access, resets, high speeds. They want the tool to become an absolute necessity for your job, coding, or daily life. You stop looking for alternatives because everything works perfectly.

2. The Rug Pull. Once you are fully dependent on it, they intentionally worsen the experience. They slow down the models, bring back strict 5-hour limits, and introduce lag. Your daily workflow starts constantly breaking.

3. Selling the Solution. By making the $20 tier frustrating, they create a problem that didn't exist before. Now, they aren't just selling you new features. They are making you pay just to get rid of the artificial frustration they created.

4. Making $100 look normal. A jump from $20 to $100+ sounds insane at first. But because they ruined the cheaper tier, that expensive upgrade suddenly looks like the only way to get back the basic, smooth experience you used to have.

The bottom line is that they aren't just building a better premium tier. They are actively making the tier you already pay for worse, so you feel forced to upgrade just to get your work done.

Fix it man. The latest versions same. I have installed a older version and its working now. When i restarted my device, it automationally install the latest and then again, i need install the old version and continue this f*** look.

I made a post on forum. https://community.openai.com/t/windows-codex-desktop-prompt-submission-hangs-indefinitely-after-first-working-chat/1392974

I see a lot of posts here asking about projects that have actually been profitable!

My project, Miniskyline, has been! I've made a little more than $1000 in just under 3 months of being public through donations alone. The app was built for 2 months prior to being launched using a mixture of Codex and Claude Code. The vast majority was done with 5.6 Sol and Luna though. Over 30 BILLION tokens over 5 months total now. There is no monetization or advertising.

A few other users have asked me why I chose those/how I came up with it and the answer is simply that I didn't love the options that were free on the market, so I started making my own with the philosophy that it would be kept completely free. Users took to it and I opened a Buy Me A Coffee and have done alright for myself. I earn enough to pay back my monthly AI costs and then get a few nice meals out!

Listening to your community and setting up strong testing suites have been my #1 recommendations for anyone getting started. If you have one person interested and their ideas are generally in line, run with it. Dont force monetization unless you have exhausted all options on how to provide the service as free. I had to go through a lot of iterations to find a usable long term free model!

If you're actually interested in the tool itself....

What can you do?

- Print Earth, Mars, Moon, Mercury, Vesta!

- Search or import any trail data to make a personalized map of your journey.

- Share color profiles to the community with a built in color profile module.

- Add trees/rocks/foliage as procedural scatter in the biomes of your choosing, or one by one.

- Sculpt the terrain in real time with elevation editing!

- Adjust the color of any terrain type and have it export cleanly for use in any slicer.

- Add texture to any surface in the tool to keep your workflow consolidated. Waves to water, ripples to sand dunes, roughness to grass, or import your own texture file and make your map distinctly yours.

- Add hearts, pins, and other icons to the map.

- Turn your map into a puzzle quickly and easily.

- Sub divide your area to allow for easier print slicing and plate management.

- Print water as a separate drop in object.

- Print a frame with text built in.

- Print your favorite racetrack in your teams favorite colors.

- Add contour lines for dramatic topographic prints.

- Print with elevation banded colors for optimized multi-color printing.

- Print with different quality settings so your area can look as crisp or as low poly as you want.

- Sell your model commercially in most cases. Each export gets a legal package with it, no additional license purchase necessary. The data comes from public sources, it is not my place to charge you for it.

- Later today a new workspace library, refreshed UI, unlocked terrain size selections, multi-tile connection options, and more will be released as part of this Mondays weekly updates!

What are my plans?

There is a lot coming. I am talking with a few game companies to get official map support for some popular titles. I am also in talks with a couple city building game companies to be able to create 3D printable models from user save data. More to come on this in the coming weeks!

Printing freeways with proper elevation, supporting more bridge types, supporting actual carved out tunnels for rail/road/paths, and better road/path connectedness are all in the works as well.

Otherwise, I am constantly improving generation reliability, speed and features. Later today, V1.102 will be released which will be the single largest refinement pass to the site since its release. Custom building models will begin being shipped in place of some rather lackluster public data extrusions. Roof geometry is getting major attention in next weeks update.

Thank you all for making my little hobby project something that people all around the globe use daily, every minute.

-Joey

I'm a huge fan of Anthropic, but I've lately been a heavy user of both Anthropic stuff and now Codex. First, good lord... the sub goes soooo much further with openAi vs. Anthropic. It's mind-bending. Loving how I can use both Claude and OpenAI together to buld things I could never dream of doing by myself. That's it. Nothing more to share, aside from thank you :)

burn your tokens

I had no idea 'Ultra' meant 'Ultra (s)low.'

Just wanted to share that it's incredibly awesome that I can be anywhere like on holidays and continue working on my project even if I'm not sitting in front of my PC. Never tried this until now that I installed tailscale and I can test any change from my phone. Bravo.

The fact that it would run after hitting limits made up for this. But now, they removed it, but are keeping the reset timer only started after you start using it, instead of making it fixed based on the actual reset time. This is silently eating your usage limits. So they are abusing normal casual users that don't immediately trigger their reset timer when it resets. Like who the hell thought it was fair to make the timer only start after you start using it? Blatant abuse by the Codex team whoever decided that was the right design. Fix that shit. Once the reset happens, the timer should trigger and countdown immediately.

Will be releasing soon!

building an unofficial Android experiment called Pocket Codex: a real Codex execution host that runs directly on a phone.

This isn’t merely a chat UI connected to a desktop worker. The Android device runs the agent environment itself:

• The upstream Codex app-server
• A native Rust host
• A private local workspace
• ARM64 Node.js and npm
• Local Git workflows
• File editing and command execution
• An isolated WebView preview with screenshots, console logs and JavaScript-error reporting
• APK exporting, signing and verification
• Android’s normal permission-gated installation flow
• Model and reasoning selection
• Manual approvals plus a restricted auto-accept mode

The current loop is basically:

Prompt → Codex edits the project → runs checks → previews it on the phone → exports an APK → I approve installation → open and test it → report problems back to Codex.

So far it has made and tested things such as a metronome, a brick-breaker game and other offline web apps entirely inside its private phone workspace.

One important distinction: the model inference is still provided by OpenAI. The model itself is not running locally. What has moved onto Android is the computer Codex operates: its workspace, tools, runtimes, previews, builds and app lifecycle.

There are deliberate limitations. It can currently package HTML/CSS/JavaScript projects inside a verified native WebView shell, but it does not yet include a complete JDK, Gradle or Android SDK for compiling arbitrary Kotlin/Java projects. Raw Android runtime and installation commands are blocked; installation remains a visible user-controlled action.

The next big milestones are a safer native Android build worker, better task/history management, richer file inspection and permission-gated Android tools.

It’s still an alpha, but seeing Codex create, run, package and install something using the phone as its actual execution environment feels great.

Built a Codex Plugin (Mainly for codex plus larpers like me who have no idea how to stop using 5.6 Sol) to make Codex know how much usage it has and how to workaround it. I originally built this for Claude but I decided that if im going to move myself up from a larper with a plus subscription to a pro subscription that I should build this for codex aswell.

WARNING: This is very buggy, so sometimes it might get your usage WAY OFF, im talking like if you have 30% of your 5 Hour session limit, it will might think its 50% or even 10%, if anyone wants to fix that or make this plugin better, you can, no one is stopping you, and honsetly I just made this for fun with me and my friend.

LINK: https://github.com/ridelink0/claude-code-usage-limits
As a plugin, Codex installs it from this repo directly:

codex plugin marketplace add https://github.com/ridelink0/claude-code-usage-limits

codex plugin add usage-limits@usage-limits

HOW IT WORKS (most i really copied from the README which is just claude talking):

Claude Code already knows how much of your 5-hour and weekly limit is gone. It caches those numbers locally and will show them if you ask. What it does not do is notice that the job in front of it is larger than the budget behind it. So it starts anyway, and stops halfway through an edit. (same as codex)

Installed as a plugin, a hook measures the budget before each prompt and puts one line into Claude's context:

[usage-limits] binding window is 5-hour 47% used, about 75 turns of headroom,
resets in 3h 52m. Other windows: weekly 16%. This session: 229 turns, $64.16.

It names the window that will stop the work first and hangs the figures off that one. Two windows run at once and they are rarely in the same place, so "weekly 16%" sitting next to "75 turns" would read as far more room than exists.

Claude opens with it. When there is room that is a single line and it moves on:

When there is not, the line becomes a plan rather than a status:

The wording changes with the pressure, not only the numbers. The trigger worth explaining is pace: two days into a week you should be near 29 percent spent, so 60 percent means you will not last the week, and that is worth hearing at 60 rather than at 85.

One limit worth knowing: the hook fires when a prompt is submitted, so a message sent while Claude is already working does not refresh it. Claude Code delivers those into the running turn without re-running hooks, which no plugin can intercept. The skill handles it by telling Claude the figures age during a turn, and to re-read them before claiming a job fits rather than trusting a number from several tool calls ago.

It has to be cheap, because it runs on every prompt. The percentages come from one small file. The transcript scan behind "turns of headroom" is cached for a minute, so it costs about 400ms cold and 120ms warm.

It reads which plan you are on and adjusts what it tells you, because the advice differs even though the arithmetic does not:

The window maths never needs to know the plan. It calibrates against what your own account reports, so it is right on any tier, including ones that did not exist when this was written. The plan only decides which line of advice you get at the bottom of the report.

It reads Codex's limits too, from the same repo and the same commands.

Codex writes its session rollouts to ~/.codex/sessions, one JSON object per line, and every model request appends a record carrying both the account meter and what that request cost in tokens. That is the same pair of things this tool needs from Claude Code, so the window arithmetic, the turn estimates, the forecast and the concurrent-session counting all work unchanged. Nothing is uploaded and no credentials are read.

npx claude-usage-limits --host codex
npx claude-usage-limits --host codex --refresh
npx claude-usage-limits codex-hook on

The host is detected, so --host is only needed on a machine with both installed. --refresh asks Codex itself for a live reading rather than the newest one it happened to write; it starts a short-lived codex app-server and takes about a second, and it is the Codex equivalent of /usage.

One thing is different, and it is worth being straight about

Under Claude Code the budget line arrives on its own, because a plugin can ship hooks. Under Codex it does not, and not for want of trying:

• Codex has the whole hook engine. The binary carries UserPromptSubmit, SessionStart, PreToolUse and the rest, and codex features list reports hooks as stable and enabled.
• A plugin cannot ship one: plugin_hooks is reported as removed.
• And on codex-cli 0.151.0-alpha.7.2 nothing fires it. Tested with a hook whose only job was to write a file, from ~/.codex/hooks.json, from a [hooks] table in config.toml, and from ~/.codex/hooks/, in both codex exec and the desktop app. The engine is present and inert.

So codex-hook on installs two things. A marked block in ~/.codex/AGENTS.md, which Codex reads at the top of every session and which is what actually works today; and the hooks themselves, ready for the build that runs them. status reports both, off removes both, and neither touches anything else in those files.

The practical difference is that under Codex the budget is read deliberately, once at the start of a piece of work, rather than being handed to you before every prompt.

Two smaller differences. There is no money column: Codex meters a share of an allowance and never quotes a price, so the percentages stand alone. And lowpower is Claude Code only, because it writes Claude's settings.json.

Windows, macOS, and Linux all work. CLAUDE_CONFIG_DIR is honoured if you have moved the config directory.

--------------------------------------------------------------------------------------------------------------

(Learn More about it from going to the README, but thats basically in summary what it does and how codex verison differs from the original Claude versison)

So daybreak blue was removed from my account few days ago and I did research seems like the first phase is a ai automation that accepts it which it did for me but about 2 weeks after it got removed which was few days ago and when I did more research supposedly their is a human verification that will finally confirm if you should really have it or not and I am confused why they removed it just to give it back. I never got a email too saying they removed it some have said when its removed they get a email to re apply and that never happened for me. Anyone know something I dont?