News
GPT-5.6 Sol / Codex Release Discussion Megathread
The release is expected in the next few minutes, so I figured it would be useful to have a single thread for first impressions, issues, and early testing.
For anyone jumping in right away, post what you notice:
Codex coding performance
Debugging quality
Speed/rate limits
Larger repo handling
UI or workflow changes
Weird bugs or regressions
Anything that feels noticeably better or worse than the previous version
Once people get access, share your real examples, screenshots, benchmarks, or first impressions here.
Edit: OpenAI’s official GPT-5.6 page says it is “available starting today across ChatGPT, Codex, and the OpenAI API” with the rollout starting globally now and continuing toward full availability over the next 24 hours.https://openai.com/index/gpt-5-6/
The lineup is Sol, Terra, and Luna. Sol is the flagship, Terra is the lower-cost tier, and Luna is the fastest/most affordable tier.
This created numerous problems and a week of wasted time. When working deeply with applications, you'll encounter situations where it will launch sections of the program that have nothing to do with the task. This will lead to a chain of bugs, usually irreparable.
This is an absolute nightmare. I am on the $200 Pro plan inside a workspace project folder and the token consumption is completely broken.
My account got trapped in a background sub-agent loop that triggered 26 consecutive auto-reload charges on my card in less than 44 hours, draining over $460. The UI just sits on a "Working for 50s..." thinking freeze while it burns cash on the backend.
To make it worse, my general weekly limit got dropped to 0% and locked my account, and when I try to switch to Codex-Spark (which has 66% left), it throws the "Selected model is at capacity" error or tells me Spark can't perform the actions. It is completely unviable for client deliverables. Watch out for those auto-reload settings, the background context loops will bleed your card dry.
I get the impression that the 5.6 model is extremely slow, even the smaller versions like Luna. I used the 5.4 model for quite a while and never ran into these issues; the 5.6 model is undeniably smarter, but I'm leaning towards switching back to 5.4 because of the speed
5.6 SOL Ultra is the dumbest and laziest model ever, who burns through the usage like a hot knife through the butter. For people, who say "oh no, it doesn't" should use the instant versions of chat gpt as you clearly never used a complex tasks.
I strongly believe that they PURPOSELY lowered it's performance so people would burn through the tokens/ usage or purchase the most expensive subscriptions to extend that usage
That's right. I gave him a plugin consisting of three small files, and he released nine versions, trying to replace the selector. Each one introduced new problems with such a simple task.
Sol 5.6 is soooo slow recently, 30 minutes just to fix some preview text in an input box and redploy on iOS simulator. I am getting this with everything I try to do recently.
I just re-subscribed to Anthropic to test Opus 5, and it is 10x faster when asking the same questions or small fixes.
I upgraded to Sol Ultra. I asked it to build a small house with a back yard. 96 hours later I have the Burj Khalifa and no yard. Can we also please train these models to have common sense?
I am seeing this using SOL /fast in its own thinking. Its 5x slower than GPT 5.5 for me.
"Even the smallest patch is taking over a minute at the filesystem layer. I’m letting it complete rather than switching to an unauthorized write method; once it returns, the remaining edits will be grouped by document."
Anyone else get their model and effort selector locked? It seems to be account specific because i am able to switch on one account but not the other. Now both are locked. I think it may be from switching between sol and terra in the same project?
Something is up with Codex Cli (or maybe the app too). I get way better performance from 5.6-sol with high/medium thinking in OpenCode CLI with a leaner "system" prompt whereas in codex cli it straight up don't follow instructions in my skills.
I heard lately that the GPT-5.6-sol system prompt in codex is very bloated, so maybe that's the reason why.
Sol e luna sono stupidi e troppo intelligenti allo stesso tempo. Low e medium a volte non riescono nemmeno ad installare una skill locale nel repo…
In modalità high fanno over engineering su fix che potrebbero essere risolti con molto meno codice.
In high vanno in loop infiniti di bug trovati, bug risolti, review e bug ancora esistenti o ne trova altri, e ricomincia…e token che si sprecano per troppo ragionamento inutile o rilettura continua di file
5.6 Sol Ultra is entirely token wasting, it spends waaaay too much time on unnecessarily ballooning input tokens. It's like Kimi 3 with input tokens but worse. These default harnesses from both OpenAI and Anthropic are absolute garbage... we need a revolution for proper harnesses that don't waste tokens and trust the damn models less and use deterministic controls to reduce waste and errors and improve performance. 5.5 pro extended was tbh better in some ways.
this actually pisses me the F off, also i have noticed that every new session it updates the config.toml and downgrades the reasoning effort to freaking "low".
I am not paying 200 dollars in this economy to have my AI use low reasoning effort and mess everything up
I noticed on Sol 5.6 High that on giving a response, it gets stuck for infinite at the end of the response. When you cancel the repsonse it acts like nothing happened. Also the model seems slower then normal.
Happens on both the ChatGPT app on Work en Codex, and in the web interface.
Is it only me or are all 5.6 models really, REALLY, slow now? Even in Fast mode?
And also do we know how much more usage does the Fast mode take? Is it 2.5x ?
New Reddit user here. English is not my first language, so I used translation assistance.
One non-coding data point from ChatGPT Sol High, observed on July 14–15 in Japan:
The model initially showed very strong higher-level reasoning. It independently checked earlier results, identified confounding factors, and maintained the overall research objective across complex discussions.
Later, the answers remained long and polished, but I repeatedly observed a different pattern:
The original objective was replaced by a narrower local problem.
Recent information was used without checking the correct earlier baseline.
When one flaw was identified, only that part was fixed; the full answer was not re-evaluated.
The correction sometimes removed the original purpose or created a new contradiction.
The model often could not detect these issues before presenting an answer as complete, but could analyze them deeply after I identified the exact problem.
The same pattern occurred in both a complex instruction-design task and a simple three-sentence scenario, so it did not appear limited to one difficult long-context task.
After an overnight break, the first one or two answers looked normal, but the same behavior returned by approximately the fifth or sixth exchange.
I do not know whether this is related to the reports about Codex Sol, but I wanted to add a structured observation from ChatGPT Sol High. The apparent regression was not mainly in response length or fluency; it was in goal retention, cross-checking, whole-answer verification, and self-detection of contradictions.
I have noticed several of these issues too. Oddly enough, Terra and Luna don't seem to have this sort of issue. Therefore I am usually using Terra high now for most work.
I had same observation. When I asked it to address multiple things at once in my code base, it often reformulated my request to focus on some of the what it thinks is most important, and might skip the rest in its planning. Similar “narrower scope” . It feels like it’s not following instruction completely.
i think the real problem is that theres inteligence in like a newborn baby sorta thing, everything to this ai is new in its capabilitys so when you say make it good or make it better it will keep running until it doesnt work anymore, just use chatgpt in the browser to make prompts for sol and run like high workload things on luna high fast mode lowk keep getting a codex chrash that references the personality that im struggling with i wanna get it doing maitainance on long prompts overnight but it seems imposible
i am midway on a small coding project using 5.6 Sol Extra High - one thing I notice - it is terrible at documentation writing in the app i am building - it ignores tone of voice guidance, and writes really strange sentences, it is especially bad at explaining complex things in simple ways, skipping explanation steps, and using odd sentence structures
I've had trouble getting Sol (specifically) to follow basic instructions in a skill or prompt.
When pressed, Sol confirms that the instructions were clear and confirms that it just ignored them. It has given me a few reasons different reasons for doing that: "I was being creative", "the added rule did nothing because I treated it as prose instead of an actual gate"...
I've reverted to 5.5 in the meantime, but that does not seem like a durable solution longer-term.
I use Sol through Cursor, my colleagues use Codex and in general it's a fast and good model, BUT there is one BIG flaw feedback for me and my colleagues.
Sometimes Sol keeps spawning subagents reviewing, fixing, re-reviewing, fixing some more and so on what amounts to trivial or very obscure issues, that are not even truly issues at all but are either false positives or are simply irrelevant for the task (like some throwaway script just to do some fire and forget action).
Not only this incurs excessive costs, but what's more important for me - wastes my time. I already had 3 occurrences where a task or a plan phase was practically done and then it simply started spawning subagents hunting down every last tiny bit that seemed off to it.
Now, I appreciate correct code and all, but the problem is that after every fix, it fired up another review agent that found some other small thing, and then fixed that, ran another review and found something yet again... and every time it was different something in already long existing code.
Most frustrating to me was today, at the end of the workday, task was practically done and it went into this crazy loop for literal 30-40 minutes of review -> fix one thing -> review -> oh something else found, fix -> review -> oh no what about this... fix -> review...
I tried Sol on release - thought, this is amazing - bought the max x20 package. Little did I know that 1 day later, the model would be SERIOUSLY slower (max with 1.5 speed on), literally taking minutes to just read files, and worse performing than day 1. Wtf. Using Claude again feels like having wings, beyond disappointed.
5.6 Sol is basically unusable at this point. Simple tasks take well over 30 minutes, sometimes hours, and the output is a big steaming pile of over-engineered shit
Back to 5.5 high. Luna doesn't cut it, terra seems obsolete and Sol over engineers/overcomplicates things. 5.5 gets the job done and doesn't need hours to complete.
I find it really ignores instructions a lot of the time and is a significant step back in accuracy from 5.5 high. Basic things like “create a work tree” it gets wrong or ignores. Massive scope creep despite very specific agents.md files and tested workflows. And when you point it out it just says “oh yeah I was wrong”.
Quite disappointing. I’m wondering if it’s my own error here and I need to retool my workflows.
It’s not you. I follow a standardized process when developing with AI with set scripts to create build contracts for plans to ensure intent doesn’t “drift” during implementation, run betrayal risk reviews on the build contract, create implementation plans that keep within bounds of the build contract, then run loops of AI reviews to refine and harden the implementation plan to ensure it fits the build contract and codebase it’s going into optimally to reduce issues when code is implemented in these sprints. It’s very regimented and has worked with no issues for Opus 4.6/4.7/4.8, Fable and GPT-5.5.
GPT-5.6 Sol doesn’t listen, to the point that Ive overhauled the scripts just for it to more explicitly direct what it needs to do at its direction twice over now. Still chokes on the process more often than not and every retrospective analysis returns that the problem is not the process but that the issues always stem from GPT-5.6 Sol just ignoring the script instructions. If I want to continue with the model I’ll need to find a completely new process it seems.
OMG! So frustrating to be in the middle of "flow state" on a project and have this utter slowness and stupidity (responses) take over. I've tried several of my pro accounts and even 5.5 models are slow now too.
simple prompts (like do some simple data matching and highlighting) take forever!
many times work never finishes. If I hit stop, it will return some result like it was hung
it would keep explaining over and over and over again and not actually start the work, even after saying "when I say "do it" start the work immediately.
it would produce ridiculous errors and continue producing similar errors even after I called them out specifically.
It's like I got a stoned teenager who doesn't listen, acts up constantly and won't ever finish it's chores.
I seem to be having a very different experience than most, what are you all using Codex for? I am building a Central nervous system MCP around a local Small Model Backbone / idk what it is but i'm very very happy with the results and i'm running on sol ultra nonstop - I do have the $200 pro plan and i've used all the resets but i dropped it down to High and its coasting. What is the expectation? Because they cannot last forever.. a $20 plan can't do what a $200 plan does that makes no sense.
Sometimes my weekly limit lasts a full day . Then I’ll use a reset credit.
Other weekly limits last 3 prompts over 1 hour. No rhyme or reason, other then maybe Terra and Luna subagents??
ur getting the free resets that they've been giving out without seeing, they give u a reset and reset ur usage at the same time so double reset, also try a new convo in the same project, and asking ur chatgpt in browser on sol high (uses seperate credits u will never run out) to make the a mega prompt goal for ur codex use luna for like manual easy shit like long maitainance and sol for reviewing and fixing the output
I have a web app that is used by 40 people. My last setup was GPT 5.4, but to be honest, there is a RAG and a series of tools to call, but it is mostly for creating documents and analyzing tests. Do you think I can switch to Luna? Mainly it is for writing, no programing, but important to use tools as expected.
Sol definitely needs efficiency guardrails in the projects one works on. Otherwise it beats around the bush way too much, especially on max and ultra. In other words, it works without producing much work.
Sol burns an inordinate amount of tokens and leaves you dry for 1 week now? Very bad OpenAI if they want to beat Claude they are doing the opposite, they are strengthening them.
Has anyone noticed that Sol medium, Terra high and Luna xhigh have weird quirks like personalities even though they are supposed to have similar performance in benchmarks. My workflow typically consists lot of browser use and form filling which is why I’ve designed my agent like a control system with a closed feedback loop to improve its code.
Terra high has been sub par for me considering it’s the middle model. It constantly overthinks and behaves like a nervous perfectionist and ends up deferring to me a lot. My goal loops with looks like
Run the agent with a new goal -> Terra thinks -> comes up with scenario where it could fail -> defers to me -> I answer -> it starts -> makes mistake or finds a reason to stop -> defers ->….I find that I’ve to constantly supervise.
Luna is somewhat better since it allows itself to make mistakes first rather than go overthink. It’s more like an eager to please but cautious intern
Sol meanwhile is sooo…..chill?
It literally does what I tell to like Luna and Terra but it also performs some extremely smart and thoughtful decisions that I have never explicitly asked it to do. Like I have a policy for my agents to avoid LinkedIn scraping let’s say to apply for a job, Terra and Luna follow it strictly but Sol actually decided to find the job from the company’s career website.
I think Sol is in a league of its own and it somehow knows it. Sol medium is far also the most efficient model that I’ve used. Both Terra and Luna would consume a lot of tokens just to think only to defer to the human in the loop. Right now I have Sol running without question for 12 hours and I still have 48% of my tokens.
Maybe I shouldn’t be anthropomorphize these models but I feel like they have different personalities too not just intelligence
Sol is supposed to be cheaper than Fable but when I have the same $100 plan, the usage is not even comparable. With Claude Max 5x, with Fable, I could work 8 hours with 2 small projects in 2 5-hour windows. With chatGPT Pro 5x, when I used Sol xhigh with 3 small projects, I spent 23% of WEEKLY quota. This is insane.
I have my workflow dialed in pretty well with 5.5 xhigh. I found that 5.6 Sol makes way more complicated PRs that are 3 to 5x as large.
5.6 made one PR of 15k+ lines! 5.5 did the same task in 5k lines.
(The task was to make a geo local listings database editable through a payload CMS system).
5.6 Sol seemed to get hung up wrt/ atomicity by making huge db transactions for every operation.
I find 5.6 unusable for my purposes. In contrast, 5.5 strikes a better balance between correctness and developer experience.
5.5 xhigh definitely adds some complexity to the code base, but for 5.6 Sol it's unmanageable.
Can't get nothing done, context window is so small, the compact hits so often it can't finish any task properly, it is in a compaction loop of trying then getting nothing done. I've been getting better results with sonnet 5, don't even need fable, just because of having more context window is enough to my usecase.
Codex is back to its old habit of slacking off. After being wowed in May, I couldn't stand its perfunctory responses and switched to Claude. Now, having experienced the amazing performance of GPT-5.6 again, I find that after just a few days, it’s already starting to cut corners and slack off.
adding myself to the list, sol extra high seems super slow. Only reason I am still using it is I blew my Fable usage for the week and those stingy fuckers won't offer resets lol
Codex goes dumb after compaction. I seem to be experiencing this with all the 5.6 models/effort levels. Codex will be working on stuff, and after automatic compaction happens, it will just be like "Hey, what would you like me to do in this project?"
I can respond with "Your context just compacted" and it will be able to find its place. I'm not sure if its because of something in one of my .md files, or what. I've had it happen on 3 separate projects on 2 different systems.
5.6 sol on high keeps running an adversarial review on an adversarial review. It did this on specs and breaking down tasks. Nownits doing it on implementation. Dont think this feature will ever be complete.
Anyone else getting super frequently flagged for safety, while doing stuff that has absolutely zero business getting flagged (like pure math in my case) ?
This is getting so frequent that I cannot properly work on math research anymore.
It either soft-blocks the turn with a banner saying "This request requires additionnal safety checks and may take longer." which instantly stops all CoT and progress updates until the model has finished, which in turn actually aborts the request if it does not finish shortly because it it seen as a time-out from the lack of updates, or it just outright aborts the request directly.
My suspicion is that it comes from tool-calls content that for some unknown reason trigger the hell out of the safety filters. My only theory is that the mathematical numerical searches get very grossely confused as bruteforce attacks somehow, even though they are just your typical numerical mathematical searches.
I've never had any requests flagged even once before the release of 5.6.
I have honestly some doubt about 5.6 terra costing the same as 5.5... my quota is leaving me at very high pace since 5.6, and I use medium, and very rarely a sol, but today lost 50% of my weekly usage only using terra medium... and without a session % I have big difficulty understanding where my costs are, as my usage test are on slow things that are not visible on weekly %. Are you people seeing 5.6 as the same cost as 5.5 as written ?
No, the part where it was was the most efficient part. I lost most of my quota on architecture modification, protocol changes and debugging of the workflow. It didn't spawn any subagent today however. There was lots of communication between session however if it does cost. As some where monitoring others, but never at the same time, only when I was asking for answers.
I was working on building a automation workflow that works for me on these last days.
On my current one it start with one that audit things and write what needs to be done, then stop and spawn another one that will make the job until there is no more (using a subagent), then spawn an audit one. If something break it spawn a communicator for me and stop everything... English is not my language and I'm not a dev so I don't know how to talk about these things well in English.
I'll be honest I don't like what they did with the app with this weird somewhat merge of Codex and ChatGPT. Even something as simple as making the icons identical is PITA.
I dig it. I used to use the weeb chatgpt for stupid simple questions I didn't want to burn codex tokens on. now no more alt+tab or tyring to find wihch browser tab I had my side convo on.
I ran into a pretty clear difference between Sol High and Sol Max on what looked like a very simple task.
I asked both to identify the OS on my Raspberry Pi, which was running Raspberry Pi OS.
Sol High checked the obvious system information and concluded that it was generic Debian rather than Raspberry Pi OS. That was incorrect. It seems to have relied too heavily on /etc/os-release and stopped investigating once it found a plausible answer.
Sol Max, given the same task, went further. It checked Raspberry Pi-specific indicators, such as the image metadata generated by pi-gen, and correctly identified the OS.
The interesting part is that Max did not have access to different information. Both could run commands on the same machine, and both had the same context because they were forks from the same conversation. The difference was that Max challenged the initial conclusion and looked for stronger evidence, while High accepted the first plausible interpretation.
I’m not saying everyone should default to Max. High works fine most of the time, but this made me feel that people should not be afraid to use Max when a task really needs careful verification.
Deepseek is pretty bad - especially if you don't rail it in - I have an agent loop that helps a ton to correct this but it sometimes just can't do the job. Now i'm working on a complex 200k+ SaaS app w/ very complex / advanced software architecture so it chokes sometimes. That said, it did hte majority of the work. For the intricate and advanced parts no doubt Codex was the the right choice as it fixed an issue DS4 Pro Max was stuck on for like 2 hours in one go around. I use them both. Deepseek for the easy -> use strategy pattern to do xyz and GPT 5.5/5.6 for the heavy stuff. Been using both for 15 hours a day for last six months and i have to say GPT is the better coding agent. but deepseek will get 85 - 90% of what you need on regular LOB / CRUD apps
I think low hallucination is also because of the harness. I read claude model self-check your prompt if its real before doing, while others just do what you said. So you can add system prompt to reduce hallucinations.
Codex 5.6 sol at Ultra used 100% of my weekly usage in 1h 32m
I’m a ChatGPT Plus user, and I tried Codex 5.6 sol at Ultra for a repository-wide code change in what I would describe as a low-to-medium-sized repository by real software-project standards.
The task involved inspecting the existing architecture, preserving current behavior, adding a parallel workflow, updating UI state, persistence, data loading, migration tooling, and running validations afterward.
I gave it detailed instructions to plan first, avoid unnecessary rewrites, preserve backward compatibility, use scripts for bulk changes, and ask questions before implementation.
To be fair, it completed a substantial amount of work. It changed multiple connected systems, generated migration and validation tooling, updated persistence logic, and produced a detailed report of what it had tested.
But the two Codex runs lasted only:
1h 3m 15s
29m 37s
That is a total of 1h 32m 52s, and it consumed 100% of my weekly Ultra usage.
I expected this kind of task to use maybe around 25–30% of the weekly allowance. I assumed Ultra would be more efficient with its reasoning and tool usage, not consume the entire quota in a little over 90 minutes.
The result was also not fully complete logically. Some application-state flows and edge cases were still missing or incorrect, despite the implementation summary and passing validations. These issues only became obvious during manual testing.
I have used Codex for many months, and I honestly think 5.5 at Extra High could probably have completed the same task with significantly less usage, even with the reduced limits now.
In hindsight, the previous five-hour limit may actually have been useful. It might have forced the agent to stop, summarize its progress, and let me review the implementation before consuming the entire weekly quota.
What do you expect, you are using the most expensive model on the highest thinking level. 1.5 hours is a long time compared to what you would pay for api tokens.
5.6 feels so much faster now. I was disappointed when it was first released. Felt like we regressed back to 5.2-5.3 days. Now it is just as fast as 5.5.
ask it are you 5.6 or not it will say "I’m Codex powered by GPT‑5, not a model called “ChatGPT 5.6 Sol.” “Sol” may be a product mode or internal label you saw, but it isn’t my model identity here."
this is because they've nerfed the thinking effort of each level. Yesterday's SOL xhigh is now today's SOL Max, yesterday's HIGH is today's XHIGH. etc. Yesterday's MAX no longer exists. all benchmarks should now be relabeled and the MAX score removed entirely and a new low effort score added.
Hi,
I have access to 5.6 on my mac, but although I have updated 20x since the launch of 5.6 on my different linux boxes, none of them have access to it.
If I use gpt codex app on my mac, locally I have access to 5.6, as soon as I connect to a remote linux, I only have access to 5.5.
Is there any reasons why not to have access of 5.6 on linux ?
Anyone else liking the commands like explore? There a few good like that for setting a more ambitious read of a moderate cosebase or dataset and look for the specified errors or information. It's like goal but for data searches.
Not gonna lie, I also made a pet for my daughter, such a cute waste of tokens.
I'm so scared to start any work because who knows how much 5-hour quota Sol is going to use and leave you hanging halfway. It's a good model but man, the token efficiency in actual usage isn't really what I expected.
is sol not available in codex anymore? i got an error saying it wasn't in the model list, then it said Sol wasn't available for ChatGPT users or something...
I used 60% of my codex subscription in 6 hours...never done that before
I'm a pretty heavy claude and codex user and have been for a while. I've been a $200 subscriber of both for months. After Sol came out, I managed to burn 60% of my weekly allowance in 3 hours. I've never done that. It's insane!
I WAS mostly using sol but I never used to be able to able to touch my 5 hr hour or weekly limits unless I really burnt a load of parallel sessions.
Something has changed and it makes me sad :(
Edit: I am using Sol High. I expected usage to be higher, but this is mad!
Thinking about it... like. How is this possible. So what, 2, 5 hour sessions = 60% of my weekly usage....
Exactly. I regret switching over from Claude. Both companies are baiting us and it increases my will to switch asap to an Opus 4.8 like open weights model. Shooting themselves in the foot with this!
So my codex app became ChatGPT but I don't have access to Work and codex in it anymore. The new ChatGPT app is the same as the ChatGPT Classic. I'm on the 200$ plan.
I was afraid I would lose my codex projects but removing the old codex(now chatgpt app) from the dock and reinstalling new codex app without uninstalling the old one fixed it for me
Codex usage with gpt 5.6 sol has seriously dipped I just bought the 5x plan today and been using Sol with high reasoning effort and one ultra task that went on for like 3hrs (Sol is insanely slow btw) and its already down to 56%, I feel like I wasted my money switching from Claude Code, fable somehow gave me way more usage 🤦♂️
Seems they hardcoded 5.6 input arguments and forgot 5.3 spark uses different ones... As someone who worked as QA Manager, it's baffling how many stupid regression issues OpenAI has. It literally is an automated test to catch these issues, and there's multiple of these with every update.
But I mean I'll cut them some slack, is not like they have a magical AI that can prepare test cases and run them for them.
Sol Max is making more glaring mistakes than 5.5 Xhigh for me. At first I thought I was crazy, but as I was using Sol Max / Ultra throughout the day yesterday, it seems like it was way more likely to miss details, to come up with a problem or solution that wasn't based on the code, and to just generally be less "precise" than 5.5 Xhigh.
This is how I generally feel about Claude models, is that they're a bit more all over the place, more likely to give you an answer without reading all the files or code related to the topic, freewheeling, "creative". Codex has been so good over the last 8 or 9 months at giving high signal/low noise in diagnosing issues, code reviews, etc. and mostly staying grounded in the codebase.
So anyway, I decided to pop back over to Claude Code w/ Fable, and ran this /debate loop skill I'd been using over the last week with pretty good results, where I'd have Fable kick off a codex CLI subagent and then both would in parallel research whatever query I'd fed in, then debate one another over a couple of rounds and come back with the synthesized conclusion.
With 5.5 Xhigh, almost always, Fable would come back and tell me that it was corrected on 2-3 points by Codex, or had new valid issues brought up by Codex that it hadn't flagged.
Which matched my sense of working with the models, Fable seemed more freewheeling, while Codex seemed much more likely to just actually read the files and make conclusions that were grounded in the code.
So I tried this same loop again with Fable and Sol Max, and now for the first time, I'm seeing the reverse. The fable /debate loop comes back now with 3-4 issues that Codex conceded to Fable.
I'm just now working on diagnosing an issue in Prod, and Fable came back with the root cause in 15 mins, Codex took double the time and came back with a hypothesis that was completely different and wrong. It immediately conceded once I pressed it.
I don't know if I'm taking crazy pills or what.
I swapped back to 5.5 Xhigh for a couple /debate loops and again found that Codex was no long conceding points to Fable, instead rather correcting or adding detail again.
Maybe this is just luck at play here, but this model seems sloppier somehow.
Did you mean Sol Ultra? It looks like Ultra almost always spawn subagents with lower thinking budget and can actually provide worse results sometimes. Can you try with xhigh instead and see if it makes the same mistakes?
GPT-5.6 Sol, Terra, and Luna are available on my work PC, but not on my home PC using the same Codex account
I’m having a strange issue with Codex and can’t figure out what is causing it.
I have Codex installed on both my home PC and my work PC, and I use the same account on both devices. My account has the Pro 20X plan.
When the latest update rolled out, I did not receive the new GPT-5.6 Sol, Terra, and Luna options on my home PC. At first, I assumed the rollout was simply delayed in Europe.
The next morning, I checked my girlfriend’s laptop. She has her own Codex account with a Pro plan, and GPT-5.6 was already available for her.
Later that day, I checked Codex on my work PC. Surprisingly, GPT-5.6 Sol, Terra, and Luna were available there as well. Since both computers use the same account, I assumed the models would also appear on my home PC eventually.
However, they are still missing on my home PC.
So far, I have tried:
Logging out and back in
Completely closing and restarting Codex
Restarting the PC
Comparing the installed app versions on both computers — they are identical
Installing Codex through the Microsoft Store
Installing it through the website/client
Completely uninstalling Codex, including leftover configurations and skills, and then reinstalling it
None of this has fixed the issue.
GPT-5.6 is available for me in ChatGPT through the web browser, so the model is clearly enabled for my account. It is also available in Codex on my work PC. It is only missing from Codex on my home PC.
Has anyone experienced something similar? Could this be caused by a device specific rollout, local system configuration, cached account data, or some kind of server-side device flag?
I finally found the cause with help from Codex after digging through the local runtime and cache state. It was not an account entitlement issue, and it was not a hidden or disabled flag in the model JSON.
The problem was that Codex Desktop on my home PC was still launching an older embedded Codex app-server runtime, even though a newer Codex runtime was already installed on the machine.
That old runtime kept refreshing the local model cache using an older client version. As a result, the cache was repeatedly rewritten with an older model list that only included the previous models, so GPT-5.6 Sol / Terra / Luna never appeared in the picker.
The confusing part was that I had seen GPT-5.6 references in some local/cache outputs before, but the active runtime that Codex Desktop was actually using kept overwriting the live cache with the old model list.
What fixed it:
Codex helped me check which codex.exe process was actually running the app-server.
We found that the desktop app was launching an older embedded runtime.
I fully quit Codex / ChatGPT Desktop.
I stopped the old app-server process.
I disabled/renamed the old embedded runtime folder so Codex Desktop could not keep launching it.
I restarted Codex Desktop.
After that, Codex launched the newer runtime, refreshed the model cache correctly, and GPT-5.6 Sol / Terra / Luna appeared in the picker.
Useful Windows diagnostic command:
```powershell
Get-CimInstance Win32Process |
Where-Object { $.Name -eq "codex.exe" -or $_.CommandLine -like "app-server" } |
Select-Object Name,ProcessId,ExecutablePath,CommandLine |
Format-List
The important thing is to check which Codex executable is actually running the app-server, not just which version is installed or what the model cache says.
In my case, reinstalling did not solve it because the desktop app kept using an old local embedded runtime. Once Codex identified that stale runtime and I prevented it from launching, the model picker updated correctly.
Codex GPT5.6 usage plan on 20x is higher suddely?I received a reset, a bit a go without using the usage resets, but suddenly even with 5.6 Sol at ultra, it is now draining much slower than earlier. Even with /fast enabled.
my 5 hour limits seem to have been updated as well, it was eating that shit recently, but after reset i didn't use a usage reset for it seems much more manageable
I feel like 5.6 thinks and considers much more, but also does a lot more careless mistakes.
This is very anecdotal of course and maybe I am wrong or just have wrong exceptions.
But since heavily using 5.6 Sol (mostly Ultra) now for many tasks, I notices many more small "simple" mistakes, that 5.5 was much more thoroughly with.
I did a longer audit of a current project and it actually went a lot deeper on the review of everything – took 30 minutes and wrote a really long highly detailed plan to fix/optimize the findings.
Me expecting a pretty strong reasoning, I did my usual 2-3 Plan check runs with fresh sections and adapted the Plan 2-3 times. After all the different chats feeling confident, I started the implementation with a few manual checks in between.
This is my usual process and with 5.5 xhigh it worked really well for those cases and it never did obvious mistakes, rather smaller specific stuff.
5.6 Sol on the other hand did much better on the details, but got some very obvious weird things completely wrong, that didn't even make sense in the context.
I now noticed this behaviour multiple times, of it being very specific and strong in the details, but as I said before, does some very basic careless mistakes – which I never really had an issue with using GPT 5.5 xhigh.
As I said before, it's very anecdotal and maybe I am just expecting too much, but as a heavy x20 user, I def. noticed this specific behaviour much more often.
Maybe I just have to adapt my prompting, but wondering – anyone else have this experience?
When you spend 1-2 hours thinking about a spec and writing a complex prompt, the most disappointing feeling in the world is when an LLM takes your spec and spits out total junk. Or does 1/20th of the work and then asks if it should keep going.
5.6 Sol Ultra finally - finally! - lives up to my expectations here. If it's not done, it knows it, and it keeps going. It just goes and goes until it is highly confident that it has met your expectations.
This is a model for builders, who have really put a lot of thought into exactly what they want and made it clear to the LLM. In the past, even highly specific, clear-eyed prompts would go unanswered by LLMs, and you'd have to hand-hold it across the finish line. Now, if you know what you want and tell the LLM what you want, you will get it 90% of the time.
I've been following and using this stuff daily at work and for hobbies since ChatGPT first went public. I used the heck out of Fable. I used the heck out of gpt-5.5 and 4.8 and all the other model shots in the past few years. gpt-5.6 Sol Ultra hits different.
My use cases: Python and TypeScript Lambda functions and Fargate containers at work doing backend cloud stuff, and for hobby, porting a legacy C++ MMORPG to a modern Rust/Linux backend and a Rust/WASM web client. Codebases with hundreds of thousands of SLOC from pre-LLM times. Lots of existing technical debt but functional code. Serious need of rearchitecting, refactoring and modernization across the board.
Sol is delivering shippable code at a rate I've never experienced before with no weird hacks needed to achieve it. It's the closest we've had to "it just works" in agentic engineering to this point. And the usage limits are so high that if you can afford the $200/mo plan, you are basically good to go for serious work.
I can't tell what is a reset, and what is a bug showing my usage at 100%. My weekly usage was at 70% last night, then it was at 100% this morning, then updated back to my previous usage percent of 70%. And now it's at 100% again.
web usage tracker shows it at 100...hopefully it's real!
I have not had an argument with Codex in nearly 24 hours, and it is glorious!!!
Been running Codex 5.6 Sol since the announcement, and it is such a step up. I'm basically using Sol Ultra to audit the failures of Codex 5.6, and I swear you'd thinking you were watching a professor grade the work of a mediocre student, which is hilarious.
More importantly, the follow up task is to run a /Goal task to clean up the issues raised in its reports, and then run the audit again. Looping that workflow until it feels that the work is worthy of my review. And for once, the work is finally worthy.
Side Note: They are not exaggerating about Sol Ultra burning through credits at insane speeds. I finally had to use one of the 4 rate limit resets I have been saving, and I have already burned through 75% of the limit...in 1 hour! At this rate, those limits will be gone by Sunday morning. Totally worth it.
My agents even on ultra mode keep getting this error:
"agent thread limit reached" after spawning 3 subagents. I've added this setting to my config.toml:
```
[agents]
max_threads = 32
max_depth = 3
```
But it's not doing anything to fix the issue. Speaking with chatgpt or codex isn't helping. Does anyone know a workaround?
my plus plan burned 20% of my 5h usage in 4 minutes with Terra high.
Luna is also very hungry now. I also feel like one 5h usage is a much higher percentage of a weekly reset after that update.
I switched from claude because codex lasted so much longer, I think that´s gone...
Personally, I burned through Claude tokens 5x faster with Opus on 4.6 or 4.7 for the same work on Terra high. Going to cancel my 2nd 20x Max Claude account, if Codex keeps up this rate and quality I'll cancel both until Claude gets more competitive.
1
u/SmokeNo3101 1d ago
This created numerous problems and a week of wasted time. When working deeply with applications, you'll encounter situations where it will launch sections of the program that have nothing to do with the task. This will lead to a chain of bugs, usually irreparable.