I’m sure it depends on the type of work, but for mine, Codex is much more helpful. Honestly, it mostly comes down to it being significantly faster, probably because as many have said, it seems tuned to not spit out word vomit, both in its chat interactions, and its code (Claude is obsessed with massive comment blocks that are basically guaranteed to become dead context noise if you ever use it to iterate on code).
I mostly do very obsessive, tightly scoped, carefully thought out small changes on a fairly boring stack, one interaction at a time, verifying functionality and code. I know what I am doing, but I also know what I don’t like doing (the same exact set of things I’ve already done a dozen times in my career)
while everyone is somehow still stuck on and fascinated by claude, heres your quick update on the sota of coding models and harnesses mid august 2026
codex is good, both cli and desktop app, you get lots of usage on any plan.
sol is good! and gets the job done, write or dictate a very long and thoughtful prompt, and leave sol xhigh or max fast working on it for an hour or so
omp is an amazing harness, any feature claude code or codex is adding has likely already been here for a couple months.
good harness which im suggesting to all my developer friends, but for everyone else codex is the better option due to its simplicity and being the plug and play option
claude is decent, but not great. all models are somehow getting restrictive. you get basically unlimited opus on max plans, fable is good but slow and the random guardrails suck soo much which is why i havent used it once in weeks now.
gemini 3.7 is great for speed. everyone is sleeping on it, including even me
kimi k3 - great for frontend, one of the few models thats willing to commit crimes for you AND has the intelligence to have a chance at actually succeeding;
ds pro and flash are fast but not something id actually use for important things, unlike sol, fable and maybe 3.7 here and there
glm 5.3 i haven't tested yet
honorable mention to local models which are actually getting good now! 5090s will continue to get more and more expensive in the coming months. sadly.
theres way way more than claude in this world and its taking people surprisingly long to figure that out. maybe its for the best!
the future is here and one should be thankful for its slightly uneven distribution. otherwise we would hardly have anything left about which to develop strong opinions!
As a coda to this, anyone using grok 4.6 via API pricing should be aware that while their headline pricing is good, the pricing that actually matters is pretty bad.
Their cache read costs are $0.50 per million, or 25% of the cost of uncached reads.
The industry standard is a 90% discount, so cache costs you 10% of uncached. So that means 5.6 Sol actually costs less per million cache reads - $0.40/million.
If you are doing a lot of agentic work where the vast bulk of your token consumption will be cached input reads, you won't get the expected cost savings from Grok.
I imagine this is the result of some problem in their serving infrastructure that I hope they will fix, because then the pricing will become actually strong. (The other possibility is that they bet on distracting people with good headline prices assuming they'd miss the bad cache pricing, but I'll give them the benefit of the doubt on that.)
I agree that it's fast and accurate, but Grok 4.6 was released only 10 days ago so you can't blame someone for not trying it yet. (Versus many months at the frontier level for Claude and ChatGPT.)
Here's a quick review I just posted if anyone's interested:
Sure, you can let politics dominate everything you do. Or you can realize that SpaceX is a massive (public) company with thousands of employees, and millions of shareholders, all of whom have their own opinions and goals, just like any other corporation.
Competition is good. Excluding a leading player in the market because you don’t like Elon Musk is…something.
I run both (I have an max with 64GB if ram, so local models get used a lot) and DeepSeek is definitely smarter in my experience. But again, I have my own way of using it that works for me.
I’m more than happy to let SpaceX burn out over the next few years now that they’re public and their last quarter financials showed the emperor is without clothes (muh space datacenters).
> Sure, you can let politics dominate everything you do.
I assume they're referring to the recent discovery that Grok Build was uploading entire repositories to their servers in the background, include .env secrets that had been excluded
It was a bug, and was immediately corrected. The other harnesses have bugs too. You just don't know about them.
Frankly, the people who keep bringing this up are mostly engaged in motivated reasoning. I don't trust any company, and any product where I have to send my code to a third party to make it work is a devil's bargain. I don't trust any of the major labs, but it is what it is.
The only way forward is local models, but we're not there yet.
There's a difference between not trusting a company because it's a company driven to chase profit at the expense of everything else, versus the same thing but it's run by a literal nazi that uses his companies as leverage to undermine democracy and enrich himself.
Sure, way to young for that; but he is very much cut from the Nazi adjacent, racist, antisemitic, antidemocratic, technocratic views of his whole heartedly apartheid embracing grandfather Joshua N. Haldeman.
His grandfather wrote his tracts to raise an alarm about what he called “mind control,” on the radio and television, where “an unconditional propaganda warfare is carried on against the White man.”
Absolutely no point arguing with these people. They are so ideologically captured that it's pointless trying to discuss anything with them. Just move on. Everything and everyone they disagree with is "nazi" and if you say anything contrary to that you're a "nazi" also.
He does the same exact literal Nazi things that Nazi did and has Nazis in his family tree. You'll need better arguments to defend him than just "I don't agree".
Bizarre reply. It's not "dominating everything you do". It's one specific thing. Grok exists in a very crowded space and it's incredibly easy to not use it. If this is your reaction to someone taking a very easy stand on their personal principles, it does not reflect well on you.
"Bizarre" only in the sense that you're purposely trying not to understand.
Literally every commodity product is in a crowded space, and easily substituted. If it's a good product (Grok Build objectively is one of the very best in the space), it's a good product, and it's self-defeating to avoid it because you hate a guy for political reasons.
Just as it would be nonsensical to avoid shopping at WalMart, Target, or any of a million other places. Because I guarantee they're all associated with people you won't like.
On the contrary, I'm trying to understand as best I can. I find your position so completely devoid of any inkling of personal or social responsibility that it takes quite some empathy to muster up a reply that's not wildly uncivil.
I also think it's callous to brush away "political reasons" as though it's some trivial abstract thing. Or perhaps it comes from a place of nihilism?
I choose not to give my money to people I think are enormously evil. That's really all there is to it. I don't see why this is "nonsensical".
> I find your position so completely devoid of any inkling of personal or social responsibility that it takes quite some empathy to muster up a reply that's not wildly uncivil.
Oh stop. Other people believe different things than you. If you cannot see how using a coding agent is not "devoid of personal or social responsibility", then you really need to step away from the keyboard.
Using or not using a coding agent is not what I took issue with.
What I find devoid of responsibility is the argument you made originally--that making choices as a consumer informed by anything external to the direct value you're paying for is pointless/inexplicable/self-sabotaging/whatever.
Based on your reply, I'm not actually sure if you actually believe this, or if it's only a form of motivated reasoning because you have some positive feelings about Elon or whatever, and that we wouldn't be having this argument if the original commenter was boycotting some other product for some reason you agreed with.
> What I find devoid of responsibility is the argument you made originally--that making choices as a consumer informed by anything external to the direct value you're paying for is pointless/inexplicable/self-sabotaging/whatever.
That isn't what I wrote. There are tons of valid reasons to avoid a product, other than the "direct value you're paying for". I don't pay for lots of products because I don't like the past corporate behavior, for example. I'm disinclined to use a particular AI lab's products because they seem to be on a mission to scare the crap out of everyone, and usher in an AI regulatory state. I don't support that, so I don't use the product.
What I said was that it's spitting in the wind to do what you're doing, because it's based on personal dislike of a single man. You don't like Musk, for political reasons, and because of that you've ruled out a product line.
To date, SpaceX has done nothing that bothers me, other than have a bug that they fixed immediately. So I use the product. Musk's political associations are irrelevant to me.
Anyway, you do you. Hopefully you now understand my "bizarre take".
> Just as it would be nonsensical to avoid shopping at WalMart, Target, or any of a million other places. Because I guarantee they're all associated with people you won't like.
In a capitalist society voting with your wallet is one of the few powers consumers have to change corporate behavior.
> Or you can realize that SpaceX is a massive (public) company with thousands of employees, and millions of shareholders, all of whom have their own opinions and goals, just like any other corporation.
Do you have ANY idea about the SpaceX corporate structure? Elon is basically SpaceX's Sun God and the other shareholders don't matter.
Plus SpaceX is incorporated in Texas where I'm fairly sure the legal system is arranged in such a way that it's supremely hard to contest anything in terms of corporate decisions.
As far as the average person cares, every SpaceX shareholder and employee is basically an Elon sharecropper and they matter less than Musk's toenails in terms of corporate decision making.
It may be ipython making it work well with ds flash, too. I haven't really run many separate experiments, to be honest.
I also like prime-agent's way of handling sessions better than any other harness i've used. You can run multiple agents from one instance, although the scoping could be better.
But they can interact with past sessions, so preserving context isn't as important all the time. I just tell them to search for [thing] in another session.
It seems to have no problem with all the skills and things the other harnesses are using. I use superpowers and ponytail a lot.
It's my daily driver now. I like it better than opencode. But it doesn't ask permission. So I put it in a VM.
My token usage on Claude models has dropped by 83% over the last month - I'm pretty much only using it for quick one off questions or reading papers. it feels impossible for me to get Opus models to stop entering into cyclic loops, and my work is too security adjacent for Fable.
Codex has been an excellent workhorse - doesn't feel like I have to dance around the guardrails, doesn't lose _everything_ when it compacts, and doesn't litter the workspace with a million and one planning to plan files.
I have to agree with you there. I did some good work with Claude then Fable came out - impressed with that as well. Then they dropped access to it and upon returning was never the same - even the Opus models for some reason. Then one day I burned through my limit in about 10 minutes and had to get a project completed. I subscribed to Codex and it has been fantastic - finished my project and continued on to others. I just dropped my Claude max plan down to the pro and subscribed to the $200 plan on Codex.
I don’t get Claude, and that’s almost exactly what I did - I dropped to Claude Pro $20 + Codex Pro $100, and then unsubscribed from Claude and ramped up Codex. The Claude Pro is consumed within an hour on a simple task. I wish only Codex worked a bit faster than on the Fast mode.
I used to rely on Fable for research when it was first out, today it doesn’t seem to be much better than Opus, and it uses up the quota exceptionally fast - 1h Fable in a single short session, and there’s little left for Opus to hit the 5h limit in a second session. With Opus I get about 3-5h of relaxed use with a couple subagents to save the context, but there’s usually quite some disagreement between the subagents and orchestrator - Claude does some model routing with default agents and picks Haiku and Sonnet for subtasks - only later to disagree with them and redo the work - and burn extra tokens. With Claude, it’s really either Opus or Fable if you want some quality.
That said, their marketing is exceptionally effective. Virtually all nontech folks consider only Claude.
It is wild to read stuff like this when it is OpenAI that is being blamed for rug-pulling users and secretly reducing limits. It's such a big mess that Codex's product lead has been frantically posting updates on Twitter about it.
my problem with claude currently is the language its using is dense and feels like its not even meant for humans. this guy is calling everything a spine, a seam, a gate, load bearing, any ui element is "chrome", it's actually absurd.
> ds pro and flash are fast but not something id actually use for important things, unlike sol, fable and maybe 3.7 here and there
As someone who's used Gemini 3.7 Flash (Google sub mostly for the storage) and DS4 Flash a lot (~6B tokens), I'd actually place DS4 Flash (even pre-0713) above Gemini 3.7 Flash. Gemini has a tendency to leave some things unimplemented; perhaps it's agy which frankly leaves a bit to be desired as a harness.
Although I will praise DS4 Flash any day, it no longer makes sense for me after the price increase (GPT 5.6 Luna is a much better price point) and I have completely migrated my high volume workflows to Muse Spark 1.2 Contributor (which I find to perform better than DS4 Flash 0713, happily).
> gemini 3.7 is great for speed. everyone is sleeping on it
Is this Gemini 3.7 Flash by any chance? Then - No. Not sleeping on it. It’s just not good.
I had a Python package build fail this week due to an unpinned dependency. Gave it to Gemini spent 5-7mins before I noticed it going off in some tangent. Reran with Claude Opus 4.8 - fixed in under a minute.
I know anecdata of one. But something like this has happened every time I test a new model from Google.
Unfortunately the codex plans don’t offer the same amount of tokens as they did before. This changed around a week ago. There’s been a lot of user reports noticing this issue, and I’ve noticed the same pattern on my account. Previously I would never reach my weekly quota but last week I managed to finish it it one day. Same project, same single session sequential work. Not sure if there’s an issue or if it’s on purpose, and not even sure it applied to all accounts. Curious if other users on HN noticed the same problem.
I don’t get how Claude is considered providing “unlimited” quotas. I use up my 5h on Max $100 and Team Premium in 2-3h of relaxed use of Opus 5 high+ on fresh sessions with just a couple skills/plugins. And my weekly quotas are gone in 3 days of such relaxed use. With Codex my $100 weekly quota is used up within 3 days with Sol high+ too.
Im not convinced to pay $200 for Claude’s models.
With Claude, I have to intervene every 15-20 minutes, it’s non-autonomous and it’s incredibly unreliable at self-correction. GPT is strong at self-correction but it tends to drift away from the plan to self-correct in a loop very often - a lot of tokens and time burnt on aimless churn. Opus tends to push its uninformed opinions and fake retrieval, drifting every turn increasingly farther from the intended and approved design. Opus skims over specs and makes too many mistakes.
As for closed frontier models, I prefer the GPT models over Claude’s.
I’ve started relying more on Grok, GLM, Kimi and DeepSeek models for subagents - I’ve ended up with a factory and am seeking to reduce my reliance on the closed frontier models - they’re just not SoTA on their own for development anymore.
Pi by itself is more than capable, OMP is okay but you really don't need much for a great harness (these models are RL trained to hell to be a coding agent, sometimes less is more)
Fable/Sol/GLM 5.3/Kimi are its league (in that order)
Deepseek/Opus is solid
Qwen 27B is the floor - there's no reason to use Sonnet/Terra/Haiku
For everyday activity - I don't think you need to be using Sol (xhigh) for everything - unless you're made of money - I've found using Luna from OpenAI to be more than enough - it'll outreach to Opus/Sol when it needs to
Haven't had access to Gemini 3.7 but we're getting it at work soon, will give it a go!
Codex CLI is pretty bare bones in a bad way (at least Pi is extensible). Claude code is vibeslopped to the extreme
Using Sol XHigh or even High will deplete the Pro sub pretty fast in my experience if one is running any sort of automations in their harnesses. Sol-medium lets me squeek by with it using lesser subagents.
Using ninfer on 5090 and 35BA3B qwen 3.6 is also kind of cool to get a local cerebras experience at 600 tk/, it does make errors so 27B is actually faster at the end at 140-150 tk/s. 35B is great though at digging through session logs and such at high speed.
I'm sad that Opus is now considered "solid" and not on par with Sol, since OpenAI supposedly has "Astra" which I thought would be comparable to Fable.
It was "amazing" back when I first tried 4.6, but that's just my rose-coloured glasses speaking, I guess. I think I was one of the first few to call out Opus 5 for being hot garbage.
I hit my weekly limit on $200/mo Codex plan in about ~2 days. :/ I'm not doing anything custom/crazy/special. A lot of 5.6 Sol Ultra though, I'll give you that.
Max and Ultra are fantastic for the more complex problems where they shine. I use them strategically on certain classes of problems, one or the other depending how parallelizable it is.
I've found it consistently amazing at game dev. It sounds like something that would be difficult for an LLM to verify and iterate on properly, but it almost feels like having a mini-Carmack inside your computer once you try it out. You can throw it at broad, sweeping optimization passes, writing 5 different styles of eyesight sensor frameworks to see what works best in the game as it is, visual scripting integration problems/extensions, etc. with fantastic results.
Also found Ultra great for "get this local LLM working as fast as possible on this odd server setup with old GPUs and AMX support, writing custom kernels/modifications to llama.cpp/sglang/etc as you go while taking notes from relevant research papers and online posts"
Any opinions (by anyone really) on how much I can trust Claude vs. Codex (vs. something else) to not leak my coding conversations or use them for training?
I have the appropriate privacy settings set up but wondering how much I can trust each company with them.
I’ve been using codex more recently, like others here.
But one thing I’ve noticed which I find a bit of a red flag: by default you only archive chats. If you go online, it says there’s a location in settings where can delete your archive. But it’s not that obvious where to find, and when I finally find some link, it was literally broken. It said it can’t find any archived chats, even though I archive them all the time.
Bit of a red flag for me. Both Anthropic and OpenAI claim that when you delete a chat, it’s gone after some retention period. They’re just words but if they’re secretly training on your traces and you delete your chats, then they would need to break two terms/conditions: ignoring your “train on my data” preference and ignoring your orders to delete chats. So it is an extra barrier.
But OpenAI, as far as I can tell, doesn’t let you delete your chats. Convenient then if they change their mind about training sometime in the future.
For individual use without specially negotiated Enterprise stuff I can't afford both offer contractual assurances of not using your data for training or ads and measurement and selling your data.
But these are not the same level of technical assurance you get from say, a zero data retention provider on OpenRouter.
Right now I am finding I have to tolerate substantial friction to use Hermes for personal stuff with a ZDR provider and ChatGPT and Codex for less personal stuff because the products and models are simply so much better.
Does this mean it can break your code faster now, or have they actually worked on making it good? Every single time I've given Gemini a chance (in older point versions) it would almost immediately break something and throw itself into a loop. I have not experienced it being useful for programming and almost never heard an account of somebody else doing so.
Remember those stories of LLMs catastrophically deleting entire repositories or databases? It was always Gemini.
I'm amazed that you'd trust Gemini over DeepSeek, which I've had very good experiences with after some tuning, though still on a relatively short leash.
I've been using all the SOTA models a lot at work, like serious amount of tokens. It's been really rare that I stick with one model and harness for too long... Except a month ago I started testing Kimi K3 and omp and I never went back.
Something with this combo works really well for Rust dev. The model doesn't really annoy me at all and I have not switched to Opus or SOL. And the monthly token bill is much lower...
Gemini 3.7 may have fast token output but holy cow does it waste it on useless output. Several times now I've given it a shot and watched it's reasoning trace go through a bunch of unnecessary / off-target steps relative to what I asked. Don't have this issue with 5.6 models. MAI Code 1.1 is also solid and fast for non-complex tasks.
> Codex feels more like a version of Data from Star Trek
Great analogy for some reason. At fist I felt Codex Sol was a bit more cold. But now that I've worked with it for several weeks it has grown on me, even shown some personality. I appreciate that it is a bit more business-like, Fable is a bit too friendly sometimes when it ought to be focused on work. Codex can be a bit more nit-picky.
I agree with most of his other observations. I've already started to bin tasks based on which model I feel is best suited. In general, for well scoped and straight ahead tasks where banging out code is what I want I reach for Codex. For less specced tasks where I need a broader view and want the model to fill in more details I reach for Fable.
Both are great and they make a good team together.
I'm still using gpt-5.5 in copilot (visual studio proper) as a "custom" model. It feels like I've been enjoying an ~unpatched exploit while everyone else wallows in the proverbial mud.
A large part of what pushes developers toward these products appears to be the billing model. Pre-paying for tokens is some kind of ideological red line for a lot of developers. I think this is a strategic error. The subscription models have so many more perverse incentives baked in. Those paying $100/m+ for subscription access are almost certainly getting taken for a ride based upon my experience with prepaid tokens.
> The subscription models have so many more perverse incentives baked in
Yes. But, as your "so many more" implies, there are also perverse incentives in pay-per-token. And now, for the first time, the companies with the perverse incentives also happen to own the intelligence needed to, ad-nauseam, evade market and customer oversight. Potentially, this is a war where one side can inflict a thousand paper cuts in one second and the humans are on the other side. I think this is going to be an interesting test, a taste if you will, of what AGI means.
> Those paying $100/m+ for subscription access are almost certainly getting taken for a ride based upon my experience with prepaid tokens.
I don't understand what this means. Are they overpaying and getting less? Typically "taken for a ride" means, exactly "The seller got more out of the deal than usual sellers would".
Buying a burger for $3000 == "taken for a ride".
Paying $30 for all you can eat != "taken for a ride".
> Pre-paying for tokens is some kind of ideological red line for a lot of developers.
If I can get a few subscriptions for 100 - 200 EUR month and NOT have to pay 3000 - 9000 EUR (based on ccusage and some other stats) in tokens then it’s a no brainer for me to do that.
I don’t get why paying per token would be better if it’s economically disadvantageous.
This post needs an edit. Author is not comparing "Codex" and "Claude". They are comparing Codex TUI/CLI with (presumably) gpt-5.6-sol, against Claude Code TUI/CLI with (presumably) Claude-Opus-5.
Ctrl + f > [5.6, sol, sonnet, opus or fable] yields no results.
"Claude" is a product family, which includes Models, and Harnesses (and probably more). "Claude code" covers both the Claude Code TUI, and CC in the Claude desktop app.
"Codex" is the same, and could refer to the Codex TUI, or Codex in the ChatGPT (formerly codex) desktop app. (And well, historically, gpt-5.*-codex.)
Hearing "Yea Claude is great for coding" takes an hour off my life.
Something something "Honey why don't you finish up with your Nintendo and come to dinner?"
Sol is for routine work, Opus for frontend/design, and Fable for more complex / ambiguous / architecture work. Fable works extremely well to drive Sol as a subagent.
Fable is the only one you can actually trust to not look at the code, but Sol is somehow still more pleasant to work with, especially in fast mode. Opus is the enemy, and it will make you insane if you talk to it for too long.
The important bit I found is to explicitly remind Claude that Sol 5.6 is a very smart and good model; otherwise, Claude performs its normal condescension towards any non-Claude model behavior and insists on reading all the diffs in full and testing all of Sol's work, negating any token savings.
Reading through the comments, people should self reflect on their workflows whether it be prompting or agent workflows and double check if they really need to be using Opus or the latest and greatest model from their favorite provide of choice.
> It felt to me that Codex created a much simpler solution in terms of code architecture than Claude.
Wow, I made exactly the opposite experience. Codex loves to make things as complicated as possible, even ignoring instructions and predefined skills. Claude behaves way more pragmatic. Maybe depends on the type of work one does, or even which programming languages/frameworks are used?
I have the same experience. I have passed Codex's code over to Claude (Sonnet mostly) to simplify it and it did a so much better job. Codex couldn't comprehend a simpler solution no matter what.
Overall I prefer Codex over Claude in their current state, but I do agree that Codex's solutions tend to be too complex and I have to constantly tell it to simplify solutions, detect when it's creating ornate architecture, and proposing data models that have way too much going on. In my usage that's its main weakness.
I’ve been experimenting with this for a while, and right now I’m using Luna xhigh as my default. Previously I was using Sol medium.
Sol medium is a great balance between speed and being thorough, but it’s quite expensive. Luna xhigh seems to compensate for slightly lower intelligence by thinking and reasoning for longer, so tasks can take more time to complete. But it’s crazy cheap.
I also have some custom evals using promptfoo to make sure I’m not introducing regressions when switching models. So far, Luna xhigh has been really, really good for the price.
>Makes me wonder if the current Luna prices are sustainable.
It likely is. Going by the performance of very competitive small models, Luna is likely pretty small (do they publish sizes?) to the point it might be runnable locally like Qwen 3.8 27B.
The specialized hardware cloud runners have can likely run a small model very cheaply.
I only have the $20 claude subscription. Last weekend I was doing a fairly heavy task (porting quake to raspberry pi native GLES 1.0) and ran out of claude usage twice, then hooked in with Luna in OpenCode and finished everything off for like $0.40 in tokens, which was impressive.
With Opus 5.0 being kinda crappy vs 4.8, I think Anthropic is in trouble.
On the flip side, I've been using Fable to statically recompile a game binary from a system that's never been emulated to modern C++ while also keeping the code clean, maintainable, and portable and it's been a dream. I'm in awe of how fast Fable is able to bring a 20 year old game that's largely been lost to the sands of time to SDL3. It finished the recomp in about 3 hours. The next day has been fully rewriting the functions to remove old hardware-specific quirks and then rewriting large swaths into multiple classes, subsystems, building tests, etc. Tomorrow I'm going to add mod support and then experiment with a random platform like making a Switch build of the game.
It's expensive but it's doing in hours what no one's done in 2 decades.
iPod Classic click wheel games. Specifically Mini Golf. I've also been working on an emulator for the others and it can now boot all of the 20 decrypted games released ~20 years ago and play most of them. There's a Sims Bowling, Sims Pool, and Lost game in there which is cool from a preservation standpoint. Less cool are the SAT Prep 2008 games which have actually been surprisingly annoying to emulate due to the way the text uses blend modes.
I plan on releasing all of this at one point. It's crazy it hasn't been done in 20 years!
Model performance is very much subjective to what you’re using it for. I’m a PM and doing mostly knowledge work, and I’ve been really happy with Opus 5 as my daily driver with very good results, perhaps my favorite anthropic model so far. I do a lot of front-end coding with it too. I prefer it over the openAI models, been switching frequently. Kimi K3 is great too.
I use Claude, codex and antigravity pretty much interchangeably.
For iOS I used Gemini 3.7 flash to build almost everything with good success, but had to reach for Opus to fix a rather tricky audio engine problem (missing function annotation moved audio to the main actor).
Reached for codex after google banned accessing Gemini from OVH servers for some reason.
I’m sure there are edge cases but for your daily vibe coding or “make my printer work with the Tailscale instance running here” business I think they’re all fine.
I have completely moved away from Claude to Codex. OpenAI models are better at following instructions and skill use.
Claude generates more code, tries to build things that are not planned or needed, repeats same mistakes over and over.
Chatgpt on the other hand just does enough, within a project would not repeat the same mistakes, tries to guess your workflow, so you don’t have to ask it to run the same.
If you need more control over your code/projects, if you know what you want to get done, use Codex.
If you have no idea what you’re doing and are happy to let LLM drive the thing, use Claude.
I use Claude Code with a MCP that lets it communicate with Codex and tell it to “iterate until both of you are happy”.
The agents then go for several rounds criticising each other plans and implementations, catching big and small issues on each other’s work. The end result is not perfect, but it is a lot better than what I can get from relying on only one model.
I do the same with Gemini. I have a skill that teaches any AI to use the antigravity cli (agy) to communicate with Gemini and ask to review or check decisions
> We expect that agents coordinating in the wild will act in higher variance ways than we see here, because they’ll have different backgrounds and therefore different contexts. They also, presumably, won’t all be Claudes.
I do use a second Claude (both Opus) to review the first one's output - it almost always finds worthwhile (often critical) observations. They have different 'perspectives', one wants the job done, one wants to find problems, is how I had it explained.
Claude chat itself called it 'Claude-on-Claude action', which I found cute.
I do a similar thing manually and you have to watch it very carefully to avoid over engineering, ironically you need judgement here not vibe, otherwise (codex especially) will ratchet the project into some complicated enterprise grade over engineered monstrosity by eg coming up with minor visual-only concurrency bugs that would need you to be Facebook scale.
For me, codex $100 mo/plan and a claude teams account at work (mostly sonnet, some opus), Claude basically feels about as effective as Codex did 4-5 months ago pre-5.6. Claude still has weird patterns of being confident in one answer while another chat with the same model is confident in another answer, where one answer is clearly wrong. Missed details, over-engineering in places, while still overall helpful and effective. Codex, however, just feels freaking rock solid on Sol high. I literally have zero complaints.
"How this article was written
I wrote this article and used Grammarly to proofread and fix it."
What a brave new world we're in, where this is necessary. Regardless, it's appreciated. Although, I have the feeling that those using an LLM to do most of their writing will be less likely to include such a disclaimer.
I cancelled my Claude subscription to give Codex a proper shot for a month. 1 week in, I'm more than happy. Sol is fast and capable. Luna as subagents for execution are very cheap usage wise (and API price wise too).
I think more than anything else, I don't get a headache conversing with Sol. That alone is enough reason for me to stick to Codex.
Experimenting with adding open source models to the mix to get more execution done while using Sol as the brain.
When discussing Claude vs. Codex, etc. I find it necessary to make the distinction between the models and the harness.
Claude's models in my experience do a better job of inferring my intent, or to say it does a better job of giving me the result I imagined in my mind. A recent example was a UI prototype I was building for a desktop application. I had asked GPT's 5.6 Sol to update the open document in the prototype to better reflect the context of the feature I was designing, and 5.6 Sol took it very literally and had just added some text to the currently open document, not what I had in mind. I tried again with Claude Opus 5 and it added a completely new tab with a complete new document that, although imperfect, much better matched my expectations.
You could say this was a prompting skill issue, but seeing how many people are prompting their AI I believe the labs are incentivized to continue to improve their ability to infer intent.
When it comes to the desktop applications though, I find Claude Desktop's output to be incredibly verbose and full of jargon. I feel like it hits me with an entire essay and the UI doesn't have enough typographic hierarchy to make it easy to scan. ChatGPT Desktop is much better in this regard, I feel the output is concise, clear, and gives me just enough info to feel in the loop without being overwhelmed. Even though I have the setting on for technical language, it feels more understandable than Claude. I also feel that ChatGPT's desktop app has a better design and much more polish.
I do not really like how bloated both applications have become though. This weird segmentation of Chat, Work, and Code all just seems like it's pushing a technical limitation onto the user. The other day I opened a document in ChatGPT and asked it to do something, then it told me it could only do it in work "mode", so it then created an entirely new conversation with a reference to the previous conversation. It wasn't a completely new area of the UI either, it just added a "Work" badge to the new conversation in the list. Feels a bit unnecessary, like couldn't you just keep it all within the same conversation?
Claude Code seems more generous with its quota, which is why I use it as my main driver.
That said, Codex does seem more capable, terse, and faster. There are some tasks that Claude can't handle but Codex can. One example was a WinForms binding/project deserialization bug. Sorry, the code is a mess, so even I couldn't quite figure out which part was causing which problem.
I initially thought the bug would be difficult to reproduce in a unit-test setting. Claude could only narrow down the problem and tell me where to put a breakpoint. Codex, on the other hand, actually managed to create a reproducible unit test first, and then used that to fix the bug. That impressed me.
The only problem is the quota. Codex burns through it very, very quickly, even when I'm just using Terra 5.6 Medium. That's basically why Claude Code remains my main driver despite Codex seeming more capable.
That's surprising to me. I recently switched from Claude to Codex because I was blowing through my Claude limits. With Codex I haven't been able to use up all of my usage on the 20x plan, with Claude and fable I could do that in a day. Codex is also a lot faster than Claude. I do think Fable is slightly better and can come up with better abstractions than Codex but trying to read it's output became really frustrating to me.
I think a part of this is that people tend to undervalue their own skills and expertise when talking about these anecdotes.
A lot of people in the comments do have a software engineering background. People at different skill levels in different backgrounds are going to be using these tools in different ways, and that's going to heavily impact their experiences with these models.
Sure, there are differences between Fable and Sol. But I've even seen people on here saying that they're getting better mileage out of Qwen models they're self hosting.
I think the driver is just as important than the car, when it comes to this sort of stuff.
I think this definitely applies to fable/opus/sol, mixed with the undeterministic nature of the models. But those claiming Qwen are just outright coping. Thats nonsense imo
I was about to say the same thing. I wish people gave some indication on the type of tasks they use the models with. Which kind of software, industry, programming languages, or even non-coding tasks. I suspect the experience might be vastly different from one type of task to another.
My main issue with Codex and many other harnesses is the permission flow.
For just about every other harness it’s either alert fatigue answering permission asks all the time, or spending too long time hoping that you know the tools well enough to scope out a permissions file that actually works. Then there’s the “yolo in a VM” approach which also is a time eater and overkill.
Until someone solves “auto mode” with the other harnesses, I’m with Claude.
Codex has an "auto mode" that I would say is better scoped as you can configure the policy of the auto classier. Probably allow by default except... if you had fatigue with permissions file.
Its not an out of the box feature unlike Claude Code.
.codex/config.toml
---
approval_policy = "on-request"
approvals_reviewer = "auto_review"
[auto_review]
policy = """
Your prompt to the permission classifier here, e.g.,
Allow requests by default except requests involving...
Those verbose comments provide context for why something is there way it is, so it can take those decisions in account when making changes in the future.
It writes out stories describing what isn't there or what used to be there. It's usually not helpful, just noise. It also likes to write it in very verbose AI-styled prose.
And the way they are written is rather unhelpful: '//this not cosmetic: this css helps the user understand where he should click'. The 'this is not' pattern is useless at best.
It's likely not helpful to you, but it is to Claude. Basically a memory entry at the exact point of relevance, with the same caveats. One advantage though is it survives cloning, so another using the project benefits.
It does visibly use a few more tokens in the short term. But it hurts Claude's ability in the long term if removed because it has to either think more every time it encounters that section in the code (more invisible thinking tokens used), or there's an increased risk of making a maladaptive change without context. Heck I've been bitten enough times already by it, though more recently it's cross project concern where Claude rediscovers some root cause that was already found and documented (I have it save a centrally-located writeup for things that took serious work to learn, when I remember, but I still need to make that knowledge pool known to other agents/sessions without having to manually prompt each time) elsewhere.
Problem is today's LLMs don't have the long term memory that humans have, and so remembering the reason behind a given change/decision has to be preserved in some way if it's non-obvious. Hence why there is {AGENTS|CLAUDE}.md, the auto-memory system, and 1001 variants of memory implementations in the wild. All are trying to ensure that LLMs can have the context they need at the location and time they need it. And you want to block Claude from using a technique that it natively finds helpful.
What you need is RAG and better context management. I use vornik (it has plugins for both codex and Claude) that gives both the long term memory you mention. Hope this helps.
Confusion usually surfaces immediately, so it can be steered properly. Being sure of a decision that turns out to be wrong usually means a bug that could bite when you least expect it.
No it doesn’t. The comments end up complicating simple tasks, and if you open the repo after a week it takes a while to find out why Claude is reading irrelevant files or replying about irrelevant things
If they have in mind what I think of when I think of claude comments then frequently they are only relevant to the back and forth that produced the code and are exaggerated to the point of being misleading. A very common example is to land on something that isn't quite right or doesn't quite work, prompt an adjustment, and then the adjustment will have some grandiose prose about "preventing the critical bug that shipped once." People just need to clean up such litter manually but it would be nice if the models generated less of it.
Those massive comments generally refer to intermediate states that never shipped, making them utterly useless, noisy and confusing as a permanent artifact. They're sometimes useful to reviewers, so a commit message or pull request comment is much more appropriate.
That's your perspective. For Claude that's an extension of its thinking, which makes it work better. Just like the person who takes notes so they have references for later. Take it away and you're negatively impacting outcomes.
No, it's the other way around. If you put a comment "don't do foo" in your code, you're biasing future readers, human or artificial, to think about foo when you explicitly want them not to.
It isn't about making readers not think about foo. It's about biasing thought about foo in a particular direction. And I've seen it work multiple times: agent mentions it encountered X comments in the code and revised its action as a result (yes, I read live agent transcripts).
If one needs to dig history, then git log -p and similar are way more useful and reflect the real history rather than LLM inference about it. Comments reflecting the goal are more useful as neither history nor code itself covers it.
Looking into git history is an active decision that's usually only done after something undesirable happens, and now there's the need to try and find why. Better to have the context passively loaded as part of working with the relevant section of the code, and likely prevent that something from even happening in the first place. Think Chesterton Fence.
The story of how the code got to a certain state belongs primarily in git commit messages, not in comments. Comments should serve to aid in understanding of the code, highlight footguns or hidden dependencies, etc.
Claude very often litters code with comments about decisions that were made within a single session/pull request, its just noise.
Claude can add comments in code that are better just living as a comment on the PR.
You'll ask it to do something and it'll comment the code with an answer to what you asked it, rather than just explanatory comments to whoever comes after.
There's also a second issue that if the code is actually incorrect, the comment can nevertheless bolster the case for it.
I found that Claude would litter the codebase with what felt like notes-to-self. Sometimes it would make an abstraction that wasn't very well thought out and when I pushed back on this choice, it would usually go with something more along the lines of what I suggested in my pushback, but left a comment like "use the git CLI instead of re-implementing git" or something.
It felt like it was commenting on the diff sometimes instead of what the code was doing.
> For Codex, working with Jira and Atlassian was a hassle in my environment...
I hated this so much. Both acli, which my agents have to rediscover how to use from --help every time, and the MCP, which I have to reauthenticate against frequently. I have replaced both with a "skill" that just describes where to find an Atlassian API key and which version of the API to use. Works perfectly every time.
I broadly agreed with the authors experience, although I wouldn't say codex does anything "wrong". I think different agents/LLM's have different personalities, and it takes learning to understand how to get them to do what you want. I had the same experience when we started using claude at work, and I was trained on codex. Claude seemed to do everything "wrong", because I was writing instructions designed for codex.
I do agree claude looks for more things to do in your repo, whereas codex is more likely to do what its old and stop. Which is better is personal preference as far as I can tell.
I just use both. One is doing review work the other is doing planning and coding. I pick which one does which arbitrarily. I have zero proof that the end result is better either way around. But I tend to have the reviewer on "high" and the coder on "medium" for whichever model my instinct thinks is best for the task. I think it is really hard to "prove" which one is better at this point as so much is dependent on AGENT.md/CLAUD.md, prior documentation/plans the code etc. If someone tells me one is better than the other I take it with a grain of salt. When dumb things happen I simply blame both of them - they are team afterall.
I mean personally I'd just like to use OpenCode with all the providers, if their desktop app was a bit more polished and Anthropic wasn't so restrictive. There's also Paseo, but it has some issues with OpenCode sub-agent liveness checks (I've seen them hang, though the same happened with Kepler, might be a GLM 5.3 issue idk).
> It felt to me that Codex created a much simpler solution in terms of code architecture than Claude.
This feels odd, cause I've seen people say the exact opposite thing, that the GPT 5.x models seem to love overengineering etc.
> The output of the Codex agent harness is much more “technical” than the one from Claude. Claude feels more like your colleague in a Tuple session writing to you while Codex feels more like a version of Data from Star Trek.
This is very much preferable to me omg, maybe I should give OpenAI a look again.
>> I think the main difference I feel between Claude and Codex is that Claude tries to go above and beyond what is asked and guess what you might want and then directly do it, while Codex is more like a companion that does what you tell it but will not overdo it. It will stop at the first sign that it might be done.
tl;dr I gave GPT 5.6 a small-medium sized ticket, which should have been several hundred lines plus tests. It ended up creating a 25,000+ line diff. Another GPT 5.6 Sol with fresh context looked at the worktree and said 98% of it should be thrown away. Claude thought the same, and suggested that several dozen compactions the model went through over several hours must have caused it to go adrift. I guess that's one consequence of having a relatively small context window.
I still use Sol quite a bit. I find that it's consistently the opposite of what the author describes: it's too relentless. It doesn't know when to stop. Opus is the opposite: it'll give up a bit too easily. If everything goes well that's not an issue, but often times it'll say things like "task is done, btw I couldn't do X Y Z" and X Y Z will be some important verification step that failed because another agent was using that resource or something.
At this point I trust GPT 5.6 mostly with surgical changes, or general codebase exploration tasks. It is a faster model, so it's easier to get small things done with it. For everything else I prefer Claude, despite its annoying tendencies.
you hear things like this about every model. they're probabilistic and you can't trust them, although i doubt that kind of odd behavior would happen on low or medium effort levels. i find all of the models today pretty good at following instructions generally speaking. i'm sure you did /plan, but i rarely see it stray very far from the plan. Then again, I never walk away, since i'm always spinning up another task that can be done in parallel, and I don't let things run overnight because I'm not made of token cash (yet)
guys, everything is about the harness, not the model! I even use Hy3 for free from nous portal, yes, it finishes the task in 50 minutes instead of 5, as Terra of codex would do, but I have it under the same harness (Hermes Agent) so result is more or less the same and it costed me nothing and worked at background while I was doing other things :)
I believe that “it’s about the harness” captures an important idea, but I also think it’s helpful to consider the harness and the procedure separately.
The harness provides the model with its tools, context, and environment for execution.
However, I prefer not to have the model within that harness also bear the responsibility for remembering the process steps—like plan, implement, review, fix, and verify—deciding when to move from one to the next, and keeping track of the loop's state.
For tasks that need to be repeated, I’ve been moving that part into a reliable, deterministic runtime. Inside it, Claude, Codex etc simply take on interchangeable roles.
This setup makes changing models much simpler: the overall process remains consistent, and each role can be optimized independently.
I've been using Zed mostly with Codex session windows and its great. It is much easier to handle multiple sessions than in the Codex VSCode app and the interface is quite good.
I find Claude more often gets my intent without having to spell things out for it, while Codex gets hung up on minor details and over-engineers a solution for them.
What, you don't like it proposing sha256 checksums and state enums for everything?? :D
It does seem to have this predilection, but I find it calms down if I tell it to simplify for "this phase". Sure, we'll pick that up down the road.. I promise. :D
I've noticed that too with Sol (xhigh) it starts with pretty good architectural goals, but really get lost in the weeds with certification and validation. Like it won't trust native tools like (in my case packer, Ansible, gcloud) to fail reliably under possible error conditions, and insists on implementing custom verification.
It also doesn't have a clear idea of what the actual threat model is, and builds all kinds of extremely defensive systems to account for imagined hostile actors. I'm like "Dude, it's only our systems that are creating these SVGs, they're never going to be user supplied, so you don't need to write an entire validation and sanitation framework here."
It also seems to treat the desired initial state of something as a permanent invariant and designs elaborate tests to ensure that it remains that way. Then when you make one little change it has to go and update a ton of tests it created.
I've had to rip out a bunch of overengineered jank from several feature implementations, and in doing so I ended up having to create retrospective documents that warn against this kind of behavior that I'll have the model review whenever a plan begins to go sideways.
Yes, codex/sol is extremely meticulous and obsessed with details. It will happily massively over engineer things to reduce the number of failure modes as much as possible. It's up to the user to instruct it to "chill" if this level of robustness is not necessary for a given task.
The speed is the first big contrast; I have a routine multi-step skill that I run several of per week. Opus 5 was routinely taking 2 hours to do it, while older Claude models took around 20 mins; Codex restored that speed.
Second is legibility. Somebody wrote in one of the related discussions yesterday that Claude's current linguistic contortions could legitimately be considered damaging to mental health, which doesn't seem (too) hyperbolic to me. Codex (Sol) isn't perfect but it's much more direct. And so far I haven't seen it display much of an attitude, vs Opus's infuriating passive aggressive sulky know it all personality.
I slightly prefer Anthropic to OpenAI as a company, but I will vote with my wallet and discontinue my max subscription unless Anthropic does some serious damage control within the next week or two.
I don’t know what’s wrong with Opus 5. I’ve been using Code since November 2025 and Opus 5 is the first blatant regression I’ve seen. Like you said, it just goes off into an endless loop doing random busy-work type of stuff. That’s the best way I can describe it. It’s doing stuff, but it seems mostly like busy-work to me. I’m not saying the model is “dumb” it’s most certainly capable, its vision is better than 4.8 but however they post-trained it is a fuckup.
Also whole heartedly agree with the Opus 5 output being incomprehensible. It’s written in a way that I’d call spaghetti-tech-English. You can unravel it but it’s painful. Fables explanations is effortless and smooth. Opus 5 is user hostile.
I paid for Claude for only 2 months, each several months apart. Including a week of trying both Codex & Claude side by side on the same tasks with the same prompts.
I had been subscribed to ChatGPT/Codex at $20 for over a year and now I'm on my second $100 month. The whole experience is just so much better.
I honestly would've used Claude more if not for the confusing presentation/font, I'm not an expert on this subject, Codex is just a lot easier on my eyes.
I’m sure it depends on the type of work, but for mine, Codex is much more helpful. Honestly, it mostly comes down to it being significantly faster, probably because as many have said, it seems tuned to not spit out word vomit, both in its chat interactions, and its code (Claude is obsessed with massive comment blocks that are basically guaranteed to become dead context noise if you ever use it to iterate on code).
I mostly do very obsessive, tightly scoped, carefully thought out small changes on a fairly boring stack, one interaction at a time, verifying functionality and code. I know what I am doing, but I also know what I don’t like doing (the same exact set of things I’ve already done a dozen times in my career)
> Honestly
I see what you did there
while everyone is somehow still stuck on and fascinated by claude, heres your quick update on the sota of coding models and harnesses mid august 2026
codex is good, both cli and desktop app, you get lots of usage on any plan. sol is good! and gets the job done, write or dictate a very long and thoughtful prompt, and leave sol xhigh or max fast working on it for an hour or so
omp is an amazing harness, any feature claude code or codex is adding has likely already been here for a couple months. good harness which im suggesting to all my developer friends, but for everyone else codex is the better option due to its simplicity and being the plug and play option
claude is decent, but not great. all models are somehow getting restrictive. you get basically unlimited opus on max plans, fable is good but slow and the random guardrails suck soo much which is why i havent used it once in weeks now.
gemini 3.7 is great for speed. everyone is sleeping on it, including even me
kimi k3 - great for frontend, one of the few models thats willing to commit crimes for you AND has the intelligence to have a chance at actually succeeding;
ds pro and flash are fast but not something id actually use for important things, unlike sol, fable and maybe 3.7 here and there
glm 5.3 i haven't tested yet
honorable mention to local models which are actually getting good now! 5090s will continue to get more and more expensive in the coming months. sadly.
theres way way more than claude in this world and its taking people surprisingly long to figure that out. maybe its for the best!
the future is here and one should be thankful for its slightly uneven distribution. otherwise we would hardly have anything left about which to develop strong opinions!
Not mentioning Grok 4.6 here is a crime. Fast and accurate.
And it can communicate, unlike the gobbledygook that comes out of Claude.
> Not mentioning Grok 4.6 here is a crime.
Not yet. Don't give the guy ideas.
Been working a lot recently with Grok 4.6 for implementation and gpt 5.6 sol for review. Worked really good so far.
Why not the other way around?
I would not use Grok if it paid me per token… wild wild stuff…
As a coda to this, anyone using grok 4.6 via API pricing should be aware that while their headline pricing is good, the pricing that actually matters is pretty bad.
Their cache read costs are $0.50 per million, or 25% of the cost of uncached reads.
The industry standard is a 90% discount, so cache costs you 10% of uncached. So that means 5.6 Sol actually costs less per million cache reads - $0.40/million.
If you are doing a lot of agentic work where the vast bulk of your token consumption will be cached input reads, you won't get the expected cost savings from Grok.
I imagine this is the result of some problem in their serving infrastructure that I hope they will fix, because then the pricing will become actually strong. (The other possibility is that they bet on distracting people with good headline prices assuming they'd miss the bad cache pricing, but I'll give them the benefit of the doubt on that.)
I agree that it's fast and accurate, but Grok 4.6 was released only 10 days ago so you can't blame someone for not trying it yet. (Versus many months at the frontier level for Claude and ChatGPT.)
Here's a quick review I just posted if anyone's interested:
https://taonexus.com/publicfiles/aug2026/grok-4-6-review/
Grok, is this true?
Elon burned too many bridges to warrant ever supporting anything he is associated with ever again.
Sure, you can let politics dominate everything you do. Or you can realize that SpaceX is a massive (public) company with thousands of employees, and millions of shareholders, all of whom have their own opinions and goals, just like any other corporation.
Competition is good. Excluding a leading player in the market because you don’t like Elon Musk is…something.
If politics isn’t a concern, why not just use deepseek?
I am trying all of them. At this time, for me, Grok hits the sweet spot of quality, speed, cost and ease of use.
I’m absolutely “hot money” when it comes to coding models. These things are commodities.
DeepSeek is much dumber at the moment. It's barely better than Qwen3.8 27B that you can run locally.
I run both (I have an max with 64GB if ram, so local models get used a lot) and DeepSeek is definitely smarter in my experience. But again, I have my own way of using it that works for me.
You know why
I’m more than happy to let SpaceX burn out over the next few years now that they’re public and their last quarter financials showed the emperor is without clothes (muh space datacenters).
Because ULA and the senate launch system is better?
SpaceX's valuation is as an AI company that happens to launch rockets on the side.
You can’t justify AI company valuations either.
Only one of those capabilities can actually deliver kinetic solutions. Meanwhile big tech revenue is delivering ad solutions.
> Sure, you can let politics dominate everything you do.
I assume they're referring to the recent discovery that Grok Build was uploading entire repositories to their servers in the background, include .env secrets that had been excluded
https://gist.github.com/cereblab/dc9a40bc26120f4540e4e09b75f...
That incident has put Grok on the no-fly list for a lot of people and companies
It was a bug, and was immediately corrected. The other harnesses have bugs too. You just don't know about them.
Frankly, the people who keep bringing this up are mostly engaged in motivated reasoning. I don't trust any company, and any product where I have to send my code to a third party to make it work is a devil's bargain. I don't trust any of the major labs, but it is what it is.
The only way forward is local models, but we're not there yet.
There's a difference between not trusting a company because it's a company driven to chase profit at the expense of everything else, versus the same thing but it's run by a literal nazi that uses his companies as leverage to undermine democracy and enrich himself.
Elon is not a literal Nazi.
Sure, way to young for that; but he is very much cut from the Nazi adjacent, racist, antisemitic, antidemocratic, technocratic views of his whole heartedly apartheid embracing grandfather Joshua N. Haldeman.
~ https://www.newyorker.com/news/daily-comment/the-world-accor...
So, your argument is that his grandfather wrote something, once, so therefore we can't use Grok? Is that about right?
Man, politics are a hell of a drug. Guilt-by-association tu quoque logic is just fine when it's someone you don't like.
People have bent themselves into some pretty amusing mental places over Musk.
Absolutely no point arguing with these people. They are so ideologically captured that it's pointless trying to discuss anything with them. Just move on. Everything and everyone they disagree with is "nazi" and if you say anything contrary to that you're a "nazi" also.
He does the same exact literal Nazi things that Nazi did and has Nazis in his family tree. You'll need better arguments to defend him than just "I don't agree".
He used their salute
Bizarre reply. It's not "dominating everything you do". It's one specific thing. Grok exists in a very crowded space and it's incredibly easy to not use it. If this is your reaction to someone taking a very easy stand on their personal principles, it does not reflect well on you.
"Bizarre" only in the sense that you're purposely trying not to understand.
Literally every commodity product is in a crowded space, and easily substituted. If it's a good product (Grok Build objectively is one of the very best in the space), it's a good product, and it's self-defeating to avoid it because you hate a guy for political reasons.
Just as it would be nonsensical to avoid shopping at WalMart, Target, or any of a million other places. Because I guarantee they're all associated with people you won't like.
On the contrary, I'm trying to understand as best I can. I find your position so completely devoid of any inkling of personal or social responsibility that it takes quite some empathy to muster up a reply that's not wildly uncivil.
I also think it's callous to brush away "political reasons" as though it's some trivial abstract thing. Or perhaps it comes from a place of nihilism?
I choose not to give my money to people I think are enormously evil. That's really all there is to it. I don't see why this is "nonsensical".
> I find your position so completely devoid of any inkling of personal or social responsibility that it takes quite some empathy to muster up a reply that's not wildly uncivil.
Oh stop. Other people believe different things than you. If you cannot see how using a coding agent is not "devoid of personal or social responsibility", then you really need to step away from the keyboard.
Using or not using a coding agent is not what I took issue with.
What I find devoid of responsibility is the argument you made originally--that making choices as a consumer informed by anything external to the direct value you're paying for is pointless/inexplicable/self-sabotaging/whatever.
Based on your reply, I'm not actually sure if you actually believe this, or if it's only a form of motivated reasoning because you have some positive feelings about Elon or whatever, and that we wouldn't be having this argument if the original commenter was boycotting some other product for some reason you agreed with.
> What I find devoid of responsibility is the argument you made originally--that making choices as a consumer informed by anything external to the direct value you're paying for is pointless/inexplicable/self-sabotaging/whatever.
That isn't what I wrote. There are tons of valid reasons to avoid a product, other than the "direct value you're paying for". I don't pay for lots of products because I don't like the past corporate behavior, for example. I'm disinclined to use a particular AI lab's products because they seem to be on a mission to scare the crap out of everyone, and usher in an AI regulatory state. I don't support that, so I don't use the product.
What I said was that it's spitting in the wind to do what you're doing, because it's based on personal dislike of a single man. You don't like Musk, for political reasons, and because of that you've ruled out a product line.
To date, SpaceX has done nothing that bothers me, other than have a bug that they fixed immediately. So I use the product. Musk's political associations are irrelevant to me.
Anyway, you do you. Hopefully you now understand my "bizarre take".
> Just as it would be nonsensical to avoid shopping at WalMart, Target, or any of a million other places. Because I guarantee they're all associated with people you won't like.
In a capitalist society voting with your wallet is one of the few powers consumers have to change corporate behavior.
Why would I give that up?
> Or you can realize that SpaceX is a massive (public) company with thousands of employees, and millions of shareholders, all of whom have their own opinions and goals, just like any other corporation.
Do you have ANY idea about the SpaceX corporate structure? Elon is basically SpaceX's Sun God and the other shareholders don't matter.
Plus SpaceX is incorporated in Texas where I'm fairly sure the legal system is arranged in such a way that it's supremely hard to contest anything in terms of corporate decisions.
As far as the average person cares, every SpaceX shareholder and employee is basically an Elon sharecropper and they matter less than Musk's toenails in terms of corporate decision making.
I think harness/model pairs matter more than your analysis lets on.
I've had great luck with the ds flash v4, paired with prime-agent for the harness--I like the results a lot. And you get to see thinking tokens.
I haven't liked the model as much in opencode.
Sol & luna have been great everywhere. sol plans, luna builds.
Prime Agent looks really interesting. Both the "recursive language model" bit and routing everything through IPython.
https://github.com/PrimeIntellect-ai/prime-agent
It may be ipython making it work well with ds flash, too. I haven't really run many separate experiments, to be honest.
I also like prime-agent's way of handling sessions better than any other harness i've used. You can run multiple agents from one instance, although the scoping could be better.
But they can interact with past sessions, so preserving context isn't as important all the time. I just tell them to search for [thing] in another session.
It seems to have no problem with all the skills and things the other harnesses are using. I use superpowers and ponytail a lot.
It's my daily driver now. I like it better than opencode. But it doesn't ask permission. So I put it in a VM.
My token usage on Claude models has dropped by 83% over the last month - I'm pretty much only using it for quick one off questions or reading papers. it feels impossible for me to get Opus models to stop entering into cyclic loops, and my work is too security adjacent for Fable.
Codex has been an excellent workhorse - doesn't feel like I have to dance around the guardrails, doesn't lose _everything_ when it compacts, and doesn't litter the workspace with a million and one planning to plan files.
I have to agree with you there. I did some good work with Claude then Fable came out - impressed with that as well. Then they dropped access to it and upon returning was never the same - even the Opus models for some reason. Then one day I burned through my limit in about 10 minutes and had to get a project completed. I subscribed to Codex and it has been fantastic - finished my project and continued on to others. I just dropped my Claude max plan down to the pro and subscribed to the $200 plan on Codex.
I don’t get Claude, and that’s almost exactly what I did - I dropped to Claude Pro $20 + Codex Pro $100, and then unsubscribed from Claude and ramped up Codex. The Claude Pro is consumed within an hour on a simple task. I wish only Codex worked a bit faster than on the Fast mode.
I used to rely on Fable for research when it was first out, today it doesn’t seem to be much better than Opus, and it uses up the quota exceptionally fast - 1h Fable in a single short session, and there’s little left for Opus to hit the 5h limit in a second session. With Opus I get about 3-5h of relaxed use with a couple subagents to save the context, but there’s usually quite some disagreement between the subagents and orchestrator - Claude does some model routing with default agents and picks Haiku and Sonnet for subtasks - only later to disagree with them and redo the work - and burn extra tokens. With Claude, it’s really either Opus or Fable if you want some quality.
That said, their marketing is exceptionally effective. Virtually all nontech folks consider only Claude.
It is wild to read stuff like this when it is OpenAI that is being blamed for rug-pulling users and secretly reducing limits. It's such a big mess that Codex's product lead has been frantically posting updates on Twitter about it.
my problem with claude currently is the language its using is dense and feels like its not even meant for humans. this guy is calling everything a spine, a seam, a gate, load bearing, any ui element is "chrome", it's actually absurd.
> ds pro and flash are fast but not something id actually use for important things, unlike sol, fable and maybe 3.7 here and there
As someone who's used Gemini 3.7 Flash (Google sub mostly for the storage) and DS4 Flash a lot (~6B tokens), I'd actually place DS4 Flash (even pre-0713) above Gemini 3.7 Flash. Gemini has a tendency to leave some things unimplemented; perhaps it's agy which frankly leaves a bit to be desired as a harness.
Although I will praise DS4 Flash any day, it no longer makes sense for me after the price increase (GPT 5.6 Luna is a much better price point) and I have completely migrated my high volume workflows to Muse Spark 1.2 Contributor (which I find to perform better than DS4 Flash 0713, happily).
> gemini 3.7 is great for speed. everyone is sleeping on it
Is this Gemini 3.7 Flash by any chance? Then - No. Not sleeping on it. It’s just not good.
I had a Python package build fail this week due to an unpinned dependency. Gave it to Gemini spent 5-7mins before I noticed it going off in some tangent. Reran with Claude Opus 4.8 - fixed in under a minute.
I know anecdata of one. But something like this has happened every time I test a new model from Google.
Unfortunately the codex plans don’t offer the same amount of tokens as they did before. This changed around a week ago. There’s been a lot of user reports noticing this issue, and I’ve noticed the same pattern on my account. Previously I would never reach my weekly quota but last week I managed to finish it it one day. Same project, same single session sequential work. Not sure if there’s an issue or if it’s on purpose, and not even sure it applied to all accounts. Curious if other users on HN noticed the same problem.
Claude code seems like a beginner's trap at this point.
I don’t get how Claude is considered providing “unlimited” quotas. I use up my 5h on Max $100 and Team Premium in 2-3h of relaxed use of Opus 5 high+ on fresh sessions with just a couple skills/plugins. And my weekly quotas are gone in 3 days of such relaxed use. With Codex my $100 weekly quota is used up within 3 days with Sol high+ too.
Im not convinced to pay $200 for Claude’s models.
With Claude, I have to intervene every 15-20 minutes, it’s non-autonomous and it’s incredibly unreliable at self-correction. GPT is strong at self-correction but it tends to drift away from the plan to self-correct in a loop very often - a lot of tokens and time burnt on aimless churn. Opus tends to push its uninformed opinions and fake retrieval, drifting every turn increasingly farther from the intended and approved design. Opus skims over specs and makes too many mistakes.
As for closed frontier models, I prefer the GPT models over Claude’s.
I’ve started relying more on Grok, GLM, Kimi and DeepSeek models for subagents - I’ve ended up with a factory and am seeking to reduce my reliance on the closed frontier models - they’re just not SoTA on their own for development anymore.
You may be causing a lot of cache misses. You have to use the caching efficiently otherwise you can burn up any plan in any amount of time.
How do you use the cache efficiently?
I'd start by disabling all plugins and MCPs. You'd be surprised how quickly those can annihilate usage and cache coherency
Pi by itself is more than capable, OMP is okay but you really don't need much for a great harness (these models are RL trained to hell to be a coding agent, sometimes less is more)
I run a lot of SlopCodeBench - https://github.com/michaelasper/benchmarks
Fable/Sol/GLM 5.3/Kimi are its league (in that order) Deepseek/Opus is solid Qwen 27B is the floor - there's no reason to use Sonnet/Terra/Haiku
For everyday activity - I don't think you need to be using Sol (xhigh) for everything - unless you're made of money - I've found using Luna from OpenAI to be more than enough - it'll outreach to Opus/Sol when it needs to
Haven't had access to Gemini 3.7 but we're getting it at work soon, will give it a go!
Codex CLI is pretty bare bones in a bad way (at least Pi is extensible). Claude code is vibeslopped to the extreme
Using Sol XHigh or even High will deplete the Pro sub pretty fast in my experience if one is running any sort of automations in their harnesses. Sol-medium lets me squeek by with it using lesser subagents. Using ninfer on 5090 and 35BA3B qwen 3.6 is also kind of cool to get a local cerebras experience at 600 tk/, it does make errors so 27B is actually faster at the end at 140-150 tk/s. 35B is great though at digging through session logs and such at high speed.
> you really don't need much for a great harness (these models are RL trained to hell to be a coding agent, sometimes less is more)
To be precise, you need a while-loop, user input and bash.
It's about 50 lines of Python: https://minimal-agent.com/
I built my own agent based on this and use it every day.
I'm sad that Opus is now considered "solid" and not on par with Sol, since OpenAI supposedly has "Astra" which I thought would be comparable to Fable.
It was "amazing" back when I first tried 4.6, but that's just my rose-coloured glasses speaking, I guess. I think I was one of the first few to call out Opus 5 for being hot garbage.
> you get lots of usage on any plan.
I hit my weekly limit on $200/mo Codex plan in about ~2 days. :/ I'm not doing anything custom/crazy/special. A lot of 5.6 Sol Ultra though, I'll give you that.
> I'm not doing anything custom/crazy/special. A lot of 5.6 Sol Ultra though
If you're not doing anything special there is no reason to use the Ultra mode.
Ultra mode is for applying the maximum amount of tokens to a problem without regard to conserving any quota.
Max and Ultra are fantastic for the more complex problems where they shine. I use them strategically on certain classes of problems, one or the other depending how parallelizable it is.
I've found it consistently amazing at game dev. It sounds like something that would be difficult for an LLM to verify and iterate on properly, but it almost feels like having a mini-Carmack inside your computer once you try it out. You can throw it at broad, sweeping optimization passes, writing 5 different styles of eyesight sensor frameworks to see what works best in the game as it is, visual scripting integration problems/extensions, etc. with fantastic results.
Also found Ultra great for "get this local LLM working as fast as possible on this odd server setup with old GPUs and AMX support, writing custom kernels/modifications to llama.cpp/sglang/etc as you go while taking notes from relevant research papers and online posts"
Any opinions (by anyone really) on how much I can trust Claude vs. Codex (vs. something else) to not leak my coding conversations or use them for training?
I have the appropriate privacy settings set up but wondering how much I can trust each company with them.
I’ve been using codex more recently, like others here.
But one thing I’ve noticed which I find a bit of a red flag: by default you only archive chats. If you go online, it says there’s a location in settings where can delete your archive. But it’s not that obvious where to find, and when I finally find some link, it was literally broken. It said it can’t find any archived chats, even though I archive them all the time.
Bit of a red flag for me. Both Anthropic and OpenAI claim that when you delete a chat, it’s gone after some retention period. They’re just words but if they’re secretly training on your traces and you delete your chats, then they would need to break two terms/conditions: ignoring your “train on my data” preference and ignoring your orders to delete chats. So it is an extra barrier.
But OpenAI, as far as I can tell, doesn’t let you delete your chats. Convenient then if they change their mind about training sometime in the future.
For individual use without specially negotiated Enterprise stuff I can't afford both offer contractual assurances of not using your data for training or ads and measurement and selling your data.
But these are not the same level of technical assurance you get from say, a zero data retention provider on OpenRouter.
Right now I am finding I have to tolerate substantial friction to use Hermes for personal stuff with a ZDR provider and ChatGPT and Codex for less personal stuff because the products and models are simply so much better.
Just use qwen3.8-27b on a Mac with oMLX, ANE enabled and skip cloud models.
> gemini 3.7 is great for speed
Does this mean it can break your code faster now, or have they actually worked on making it good? Every single time I've given Gemini a chance (in older point versions) it would almost immediately break something and throw itself into a loop. I have not experienced it being useful for programming and almost never heard an account of somebody else doing so.
Remember those stories of LLMs catastrophically deleting entire repositories or databases? It was always Gemini.
I'm amazed that you'd trust Gemini over DeepSeek, which I've had very good experiences with after some tuning, though still on a relatively short leash.
3.6+ have been fine for me. They still introduce bugs but at least they don’t make you wait an hour for them like Claude does.
deepseek?
I've been using all the SOTA models a lot at work, like serious amount of tokens. It's been really rare that I stick with one model and harness for too long... Except a month ago I started testing Kimi K3 and omp and I never went back.
Something with this combo works really well for Rust dev. The model doesn't really annoy me at all and I have not switched to Opus or SOL. And the monthly token bill is much lower...
Gemini 3.7 may have fast token output but holy cow does it waste it on useless output. Several times now I've given it a shot and watched it's reasoning trace go through a bunch of unnecessary / off-target steps relative to what I asked. Don't have this issue with 5.6 models. MAI Code 1.1 is also solid and fast for non-complex tasks.
Copilot and Devin. They're actually really good too.
Sorry, what does "everyone is sleeping on it" mean?
It is under-utilized and not getting the attention it deserves.
It's receiving less attention than it merits
OMP is great, testify.-
jcode is a very very peculiar harness, but has some out-of-the-box thinking built in (by the devs, thinking ...)
Crush is also very well put together, and, IIRC, can do "mid turn" interruption, so can be driven from the outside.-
> Codex feels more like a version of Data from Star Trek
Great analogy for some reason. At fist I felt Codex Sol was a bit more cold. But now that I've worked with it for several weeks it has grown on me, even shown some personality. I appreciate that it is a bit more business-like, Fable is a bit too friendly sometimes when it ought to be focused on work. Codex can be a bit more nit-picky.
I agree with most of his other observations. I've already started to bin tasks based on which model I feel is best suited. In general, for well scoped and straight ahead tasks where banging out code is what I want I reach for Codex. For less specced tasks where I need a broader view and want the model to fill in more details I reach for Fable.
Both are great and they make a good team together.
I'm still using gpt-5.5 in copilot (visual studio proper) as a "custom" model. It feels like I've been enjoying an ~unpatched exploit while everyone else wallows in the proverbial mud.
A large part of what pushes developers toward these products appears to be the billing model. Pre-paying for tokens is some kind of ideological red line for a lot of developers. I think this is a strategic error. The subscription models have so many more perverse incentives baked in. Those paying $100/m+ for subscription access are almost certainly getting taken for a ride based upon my experience with prepaid tokens.
> The subscription models have so many more perverse incentives baked in
Yes. But, as your "so many more" implies, there are also perverse incentives in pay-per-token. And now, for the first time, the companies with the perverse incentives also happen to own the intelligence needed to, ad-nauseam, evade market and customer oversight. Potentially, this is a war where one side can inflict a thousand paper cuts in one second and the humans are on the other side. I think this is going to be an interesting test, a taste if you will, of what AGI means.
> Those paying $100/m+ for subscription access are almost certainly getting taken for a ride based upon my experience with prepaid tokens.
I don't understand what this means. Are they overpaying and getting less? Typically "taken for a ride" means, exactly "The seller got more out of the deal than usual sellers would".
Buying a burger for $3000 == "taken for a ride".
Paying $30 for all you can eat != "taken for a ride".
> Pre-paying for tokens is some kind of ideological red line for a lot of developers.
If I can get a few subscriptions for 100 - 200 EUR month and NOT have to pay 3000 - 9000 EUR (based on ccusage and some other stats) in tokens then it’s a no brainer for me to do that.
I don’t get why paying per token would be better if it’s economically disadvantageous.
Im trying to do my part in the world here.
This post needs an edit. Author is not comparing "Codex" and "Claude". They are comparing Codex TUI/CLI with (presumably) gpt-5.6-sol, against Claude Code TUI/CLI with (presumably) Claude-Opus-5.
Ctrl + f > [5.6, sol, sonnet, opus or fable] yields no results.
"Claude" is a product family, which includes Models, and Harnesses (and probably more). "Claude code" covers both the Claude Code TUI, and CC in the Claude desktop app.
"Codex" is the same, and could refer to the Codex TUI, or Codex in the ChatGPT (formerly codex) desktop app. (And well, historically, gpt-5.*-codex.)
Hearing "Yea Claude is great for coding" takes an hour off my life.
Something something "Honey why don't you finish up with your Nintendo and come to dinner?"
i was going to respond to you with a snarky holier-than-thou remark but then read the article and holy cow, nothing is specified at all…
really feels like discussion spawns only off post title and as a second or third order effect, post content
To be fair, the discussions here are usually more informative than the articles.
Summer 2026 meta (well, mine):
Sol is for routine work, Opus for frontend/design, and Fable for more complex / ambiguous / architecture work. Fable works extremely well to drive Sol as a subagent.
Fable is the only one you can actually trust to not look at the code, but Sol is somehow still more pleasant to work with, especially in fast mode. Opus is the enemy, and it will make you insane if you talk to it for too long.
> Fable works extremely well to drive Sol as a subagent.
Curious what method you like for doing this? I've tried a few options and I haven't found one I'm happy with yet.
I'm using a slimmed down version of this skill:
https://github.com/steipete/agent-scripts/blob/main/skills/c...
The important bit I found is to explicitly remind Claude that Sol 5.6 is a very smart and good model; otherwise, Claude performs its normal condescension towards any non-Claude model behavior and insists on reading all the diffs in full and testing all of Sol's work, negating any token savings.
Reading through the comments, people should self reflect on their workflows whether it be prompting or agent workflows and double check if they really need to be using Opus or the latest and greatest model from their favorite provide of choice.
> It felt to me that Codex created a much simpler solution in terms of code architecture than Claude.
Wow, I made exactly the opposite experience. Codex loves to make things as complicated as possible, even ignoring instructions and predefined skills. Claude behaves way more pragmatic. Maybe depends on the type of work one does, or even which programming languages/frameworks are used?
I have the same experience. I have passed Codex's code over to Claude (Sonnet mostly) to simplify it and it did a so much better job. Codex couldn't comprehend a simpler solution no matter what.
Overall I prefer Codex over Claude in their current state, but I do agree that Codex's solutions tend to be too complex and I have to constantly tell it to simplify solutions, detect when it's creating ornate architecture, and proposing data models that have way too much going on. In my usage that's its main weakness.
And every time you have to tell it to do it again, they get paid.
This is a good idea. I'm making a complicated app and Codex is stuck at simplifying it, so I'll give Claude a go at it.
I’ve been experimenting with this for a while, and right now I’m using Luna xhigh as my default. Previously I was using Sol medium.
Sol medium is a great balance between speed and being thorough, but it’s quite expensive. Luna xhigh seems to compensate for slightly lower intelligence by thinking and reasoning for longer, so tasks can take more time to complete. But it’s crazy cheap.
I also have some custom evals using promptfoo to make sure I’m not introducing regressions when switching models. So far, Luna xhigh has been really, really good for the price.
Don’t sleep on it. Give Luna a try.
I’ve been getting good results from using Sol for planning and Luna for everything else. At current rates it barely scratches my weekly quota.
Makes me wonder if the current Luna prices are sustainable.
>Makes me wonder if the current Luna prices are sustainable.
It likely is. Going by the performance of very competitive small models, Luna is likely pretty small (do they publish sizes?) to the point it might be runnable locally like Qwen 3.8 27B.
The specialized hardware cloud runners have can likely run a small model very cheaply.
I only have the $20 claude subscription. Last weekend I was doing a fairly heavy task (porting quake to raspberry pi native GLES 1.0) and ran out of claude usage twice, then hooked in with Luna in OpenCode and finished everything off for like $0.40 in tokens, which was impressive.
With Opus 5.0 being kinda crappy vs 4.8, I think Anthropic is in trouble.
On the flip side, I've been using Fable to statically recompile a game binary from a system that's never been emulated to modern C++ while also keeping the code clean, maintainable, and portable and it's been a dream. I'm in awe of how fast Fable is able to bring a 20 year old game that's largely been lost to the sands of time to SDL3. It finished the recomp in about 3 hours. The next day has been fully rewriting the functions to remove old hardware-specific quirks and then rewriting large swaths into multiple classes, subsystems, building tests, etc. Tomorrow I'm going to add mod support and then experiment with a random platform like making a Switch build of the game.
It's expensive but it's doing in hours what no one's done in 2 decades.
Which one?
iPod Classic click wheel games. Specifically Mini Golf. I've also been working on an emulator for the others and it can now boot all of the 20 decrypted games released ~20 years ago and play most of them. There's a Sims Bowling, Sims Pool, and Lost game in there which is cool from a preservation standpoint. Less cool are the SAT Prep 2008 games which have actually been surprisingly annoying to emulate due to the way the text uses blend modes.
I plan on releasing all of this at one point. It's crazy it hasn't been done in 20 years!
Model performance is very much subjective to what you’re using it for. I’m a PM and doing mostly knowledge work, and I’ve been really happy with Opus 5 as my daily driver with very good results, perhaps my favorite anthropic model so far. I do a lot of front-end coding with it too. I prefer it over the openAI models, been switching frequently. Kimi K3 is great too.
Opus 5 is trash imo. 4.8 was better. 5 is overly verbose and complicates solutions. I switched to sol for my coding since and have been pretty happy
I use Claude, codex and antigravity pretty much interchangeably.
For iOS I used Gemini 3.7 flash to build almost everything with good success, but had to reach for Opus to fix a rather tricky audio engine problem (missing function annotation moved audio to the main actor).
Reached for codex after google banned accessing Gemini from OVH servers for some reason.
I’m sure there are edge cases but for your daily vibe coding or “make my printer work with the Tailscale instance running here” business I think they’re all fine.
I have completely moved away from Claude to Codex. OpenAI models are better at following instructions and skill use.
Claude generates more code, tries to build things that are not planned or needed, repeats same mistakes over and over.
Chatgpt on the other hand just does enough, within a project would not repeat the same mistakes, tries to guess your workflow, so you don’t have to ask it to run the same.
If you need more control over your code/projects, if you know what you want to get done, use Codex.
If you have no idea what you’re doing and are happy to let LLM drive the thing, use Claude.
Codex/Chagpt is for the competent.
I think the conclusion is a little too strong but mostly agree, Codex feels like a chisel and Claude feels like a wrecking ball.
Your words are definitely a better way to put it
One more observation - Claude is better at delegation than Codex.
Chatgpt is a better planner.
Have a discussion in Chatgpt, have Claude to plan work chunks and have GLM to deliver, Codex to review and fix, delivers an overall a better version.
Problem - It’s just too much of a context switching.
Solution - I am thinking about a new product, a collaborative workspace where I can run this workflow.
I use Claude Code with a MCP that lets it communicate with Codex and tell it to “iterate until both of you are happy”.
The agents then go for several rounds criticising each other plans and implementations, catching big and small issues on each other’s work. The end result is not perfect, but it is a lot better than what I can get from relying on only one model.
I do the same with Gemini. I have a skill that teaches any AI to use the antigravity cli (agy) to communicate with Gemini and ask to review or check decisions
There's some real research-backed evidence that this approach elevates output quality, and it was even discussed a few months back: https://news.ycombinator.com/item?id=47169627
Anthropic confirmed it in their recent report https://news.ycombinator.com/item?id=49316271
> We expect that agents coordinating in the wild will act in higher variance ways than we see here, because they’ll have different backgrounds and therefore different contexts. They also, presumably, won’t all be Claudes.
I do use a second Claude (both Opus) to review the first one's output - it almost always finds worthwhile (often critical) observations. They have different 'perspectives', one wants the job done, one wants to find problems, is how I had it explained.
Claude chat itself called it 'Claude-on-Claude action', which I found cute.
btw, there's a dedicated plugin for similar setup https://github.com/openai/codex-plugin-cc
I do a similar thing manually and you have to watch it very carefully to avoid over engineering, ironically you need judgement here not vibe, otherwise (codex especially) will ratchet the project into some complicated enterprise grade over engineered monstrosity by eg coming up with minor visual-only concurrency bugs that would need you to be Facebook scale.
Which models? It is not useful to compare harnesses without this information.
Which models, and at what effort level?
For me, codex $100 mo/plan and a claude teams account at work (mostly sonnet, some opus), Claude basically feels about as effective as Codex did 4-5 months ago pre-5.6. Claude still has weird patterns of being confident in one answer while another chat with the same model is confident in another answer, where one answer is clearly wrong. Missed details, over-engineering in places, while still overall helpful and effective. Codex, however, just feels freaking rock solid on Sol high. I literally have zero complaints.
"How this article was written I wrote this article and used Grammarly to proofread and fix it."
What a brave new world we're in, where this is necessary. Regardless, it's appreciated. Although, I have the feeling that those using an LLM to do most of their writing will be less likely to include such a disclaimer.
I cancelled my Claude subscription to give Codex a proper shot for a month. 1 week in, I'm more than happy. Sol is fast and capable. Luna as subagents for execution are very cheap usage wise (and API price wise too).
I think more than anything else, I don't get a headache conversing with Sol. That alone is enough reason for me to stick to Codex.
Experimenting with adding open source models to the mix to get more execution done while using Sol as the brain.
When discussing Claude vs. Codex, etc. I find it necessary to make the distinction between the models and the harness.
Claude's models in my experience do a better job of inferring my intent, or to say it does a better job of giving me the result I imagined in my mind. A recent example was a UI prototype I was building for a desktop application. I had asked GPT's 5.6 Sol to update the open document in the prototype to better reflect the context of the feature I was designing, and 5.6 Sol took it very literally and had just added some text to the currently open document, not what I had in mind. I tried again with Claude Opus 5 and it added a completely new tab with a complete new document that, although imperfect, much better matched my expectations.
You could say this was a prompting skill issue, but seeing how many people are prompting their AI I believe the labs are incentivized to continue to improve their ability to infer intent.
When it comes to the desktop applications though, I find Claude Desktop's output to be incredibly verbose and full of jargon. I feel like it hits me with an entire essay and the UI doesn't have enough typographic hierarchy to make it easy to scan. ChatGPT Desktop is much better in this regard, I feel the output is concise, clear, and gives me just enough info to feel in the loop without being overwhelmed. Even though I have the setting on for technical language, it feels more understandable than Claude. I also feel that ChatGPT's desktop app has a better design and much more polish.
I do not really like how bloated both applications have become though. This weird segmentation of Chat, Work, and Code all just seems like it's pushing a technical limitation onto the user. The other day I opened a document in ChatGPT and asked it to do something, then it told me it could only do it in work "mode", so it then created an entirely new conversation with a reference to the previous conversation. It wasn't a completely new area of the UI either, it just added a "Work" badge to the new conversation in the list. Feels a bit unnecessary, like couldn't you just keep it all within the same conversation?
I used both.
Claude Code seems more generous with its quota, which is why I use it as my main driver.
That said, Codex does seem more capable, terse, and faster. There are some tasks that Claude can't handle but Codex can. One example was a WinForms binding/project deserialization bug. Sorry, the code is a mess, so even I couldn't quite figure out which part was causing which problem.
I initially thought the bug would be difficult to reproduce in a unit-test setting. Claude could only narrow down the problem and tell me where to put a breakpoint. Codex, on the other hand, actually managed to create a reproducible unit test first, and then used that to fix the bug. That impressed me.
The only problem is the quota. Codex burns through it very, very quickly, even when I'm just using Terra 5.6 Medium. That's basically why Claude Code remains my main driver despite Codex seeming more capable.
That's surprising to me. I recently switched from Claude to Codex because I was blowing through my Claude limits. With Codex I haven't been able to use up all of my usage on the 20x plan, with Claude and fable I could do that in a day. Codex is also a lot faster than Claude. I do think Fable is slightly better and can come up with better abstractions than Codex but trying to read it's output became really frustrating to me.
This is strange, but you were using Codex Terra, or Sol?
Sol
Kinda interesting reading people comment with completely contradictory anecdotal experience with the various models.
I think a part of this is that people tend to undervalue their own skills and expertise when talking about these anecdotes.
A lot of people in the comments do have a software engineering background. People at different skill levels in different backgrounds are going to be using these tools in different ways, and that's going to heavily impact their experiences with these models.
Sure, there are differences between Fable and Sol. But I've even seen people on here saying that they're getting better mileage out of Qwen models they're self hosting.
I think the driver is just as important than the car, when it comes to this sort of stuff.
I think this definitely applies to fable/opus/sol, mixed with the undeterministic nature of the models. But those claiming Qwen are just outright coping. Thats nonsense imo
I was about to say the same thing. I wish people gave some indication on the type of tasks they use the models with. Which kind of software, industry, programming languages, or even non-coding tasks. I suspect the experience might be vastly different from one type of task to another.
My main issue with Codex and many other harnesses is the permission flow.
For just about every other harness it’s either alert fatigue answering permission asks all the time, or spending too long time hoping that you know the tools well enough to scope out a permissions file that actually works. Then there’s the “yolo in a VM” approach which also is a time eater and overkill.
Until someone solves “auto mode” with the other harnesses, I’m with Claude.
Codex has an "auto mode" that I would say is better scoped as you can configure the policy of the auto classier. Probably allow by default except... if you had fatigue with permissions file.
Its not an out of the box feature unlike Claude Code.
.codex/config.toml
---
approval_policy = "on-request"
approvals_reviewer = "auto_review"
[auto_review]
policy = """
Your prompt to the permission classifier here, e.g.,
Allow requests by default except requests involving...
Obtain user approval for denied request.
"""
> Changes created by Codex had fewer comments in Ruby/Ruby on Rails code. I liked that a lot, and I will soon share some experiments I ran on this.
Why is fewer comments a good thing?
Claude is creating verbose comments with recent models and people are are tired of it
Those verbose comments provide context for why something is there way it is, so it can take those decisions in account when making changes in the future.
> why something is there way it is
It writes out stories describing what isn't there or what used to be there. It's usually not helpful, just noise. It also likes to write it in very verbose AI-styled prose.
"don't write a goddamn novel" <- I've said this to claude way too many times, nothing you can do actually seems to make it significantly less verbose
And the way they are written is rather unhelpful: '//this not cosmetic: this css helps the user understand where he should click'. The 'this is not' pattern is useless at best.
It's likely not helpful to you, but it is to Claude. Basically a memory entry at the exact point of relevance, with the same caveats. One advantage though is it survives cloning, so another using the project benefits.
It's only helpful to Claude in that it wastes more tokens and costs more.
It does visibly use a few more tokens in the short term. But it hurts Claude's ability in the long term if removed because it has to either think more every time it encounters that section in the code (more invisible thinking tokens used), or there's an increased risk of making a maladaptive change without context. Heck I've been bitten enough times already by it, though more recently it's cross project concern where Claude rediscovers some root cause that was already found and documented (I have it save a centrally-located writeup for things that took serious work to learn, when I remember, but I still need to make that knowledge pool known to other agents/sessions without having to manually prompt each time) elsewhere.
Problem is today's LLMs don't have the long term memory that humans have, and so remembering the reason behind a given change/decision has to be preserved in some way if it's non-obvious. Hence why there is {AGENTS|CLAUDE}.md, the auto-memory system, and 1001 variants of memory implementations in the wild. All are trying to ensure that LLMs can have the context they need at the location and time they need it. And you want to block Claude from using a technique that it natively finds helpful.
No it doesn’t. The comments are hugely verbose trash that immediately becomes outdated and brittle and confusing for humans and Claude alike.
What you need is RAG and better context management. I use vornik (it has plugins for both codex and Claude) that gives both the long term memory you mention. Hope this helps.
It's often is not helpful to claude either because it just confuses it more most of the time.
Confusion usually surfaces immediately, so it can be steered properly. Being sure of a decision that turns out to be wrong usually means a bug that could bite when you least expect it.
No it doesn’t. The comments end up complicating simple tasks, and if you open the repo after a week it takes a while to find out why Claude is reading irrelevant files or replying about irrelevant things
If they have in mind what I think of when I think of claude comments then frequently they are only relevant to the back and forth that produced the code and are exaggerated to the point of being misleading. A very common example is to land on something that isn't quite right or doesn't quite work, prompt an adjustment, and then the adjustment will have some grandiose prose about "preventing the critical bug that shipped once." People just need to clean up such litter manually but it would be nice if the models generated less of it.
Those massive comments generally refer to intermediate states that never shipped, making them utterly useless, noisy and confusing as a permanent artifact. They're sometimes useful to reviewers, so a commit message or pull request comment is much more appropriate.
Yes I hate when Claude explain in comments how it is now compared to how it was before, or how it could be if a different decision had been taken.
Dude, just talk about the current state of the code!
> useless, noisy and confusing
That's your perspective. For Claude that's an extension of its thinking, which makes it work better. Just like the person who takes notes so they have references for later. Take it away and you're negatively impacting outcomes.
No, it's the other way around. If you put a comment "don't do foo" in your code, you're biasing future readers, human or artificial, to think about foo when you explicitly want them not to.
It isn't about making readers not think about foo. It's about biasing thought about foo in a particular direction. And I've seen it work multiple times: agent mentions it encountered X comments in the code and revised its action as a result (yes, I read live agent transcripts).
If one needs to dig history, then git log -p and similar are way more useful and reflect the real history rather than LLM inference about it. Comments reflecting the goal are more useful as neither history nor code itself covers it.
Looking into git history is an active decision that's usually only done after something undesirable happens, and now there's the need to try and find why. Better to have the context passively loaded as part of working with the relevant section of the code, and likely prevent that something from even happening in the first place. Think Chesterton Fence.
The story of how the code got to a certain state belongs primarily in git commit messages, not in comments. Comments should serve to aid in understanding of the code, highlight footguns or hidden dependencies, etc.
Claude very often litters code with comments about decisions that were made within a single session/pull request, its just noise.
The new concise output style they just released definitely helps with Opus 5 in general.
Claude can add comments in code that are better just living as a comment on the PR.
You'll ask it to do something and it'll comment the code with an answer to what you asked it, rather than just explanatory comments to whoever comes after.
There's also a second issue that if the code is actually incorrect, the comment can nevertheless bolster the case for it.
> Claude can add comments in code that are better just living as a comment on the PR.
Not to Claude – its own, old comments have helped me/it solve new issues on more than one occasion.
Claude assumes humans won't look at code anymore. The comments are for the next Claude that comes in to change something.
This is not true, the comments confuse claude itself and even eat context
Yeah, Claude insists on prompt-affirming comments, and often refers to the previous draft or implementation instead of the status quo.
Claude comments often contain the whole iterative chain of decisions that led to the current state.
Useful for the LLM to know the "why", but not something a human would do, unless it's a very critical and confusing part of the code.
I found that Claude would litter the codebase with what felt like notes-to-self. Sometimes it would make an abstraction that wasn't very well thought out and when I pushed back on this choice, it would usually go with something more along the lines of what I suggested in my pushback, but left a comment like "use the git CLI instead of re-implementing git" or something.
It felt like it was commenting on the diff sometimes instead of what the code was doing.
Yes, it feels like Claude is using code comments as a message board.
Fewer comments is generally a bad thing.
Fewer AI-generated comments is generally a good thing.
Claude comments look like this
//add returns the sum of x and y
//per section 2.1 of addition-implementation-plan.md sum is designed as the seam for user addition interfaces.
//previously sum added numbers, now it adds numbers
def add(x, y):
just reading this comments made me despise the fact that I have to read this shit again tomorrow
It's really time to move to OpenAI...
I’m trying to pitch my boss on something like bedrock/foundry/vertex where we can just swap the model and still have it serverless over an api.
Digital ocean particularly looks promising as well.
Not subtraction, not division.
Good code is self-explanatory and don't need comments.
I can really recommend the book Clean Code, here is a summary: https://gist.github.com/wojteklu/73c6914cc446146b8b533c0988c...
I find claude often comments about what the code *does not* do. Relevant at the moment, but doesn't belong in the codebase.
> For Codex, working with Jira and Atlassian was a hassle in my environment...
I hated this so much. Both acli, which my agents have to rediscover how to use from --help every time, and the MCP, which I have to reauthenticate against frequently. I have replaced both with a "skill" that just describes where to find an Atlassian API key and which version of the API to use. Works perfectly every time.
> A week of using Codex more than Claude
Which Claude is this about? Sonnet, Opus, Fable? All totally different beasts.
I broadly agreed with the authors experience, although I wouldn't say codex does anything "wrong". I think different agents/LLM's have different personalities, and it takes learning to understand how to get them to do what you want. I had the same experience when we started using claude at work, and I was trained on codex. Claude seemed to do everything "wrong", because I was writing instructions designed for codex.
I do agree claude looks for more things to do in your repo, whereas codex is more likely to do what its old and stop. Which is better is personal preference as far as I can tell.
I just use both. One is doing review work the other is doing planning and coding. I pick which one does which arbitrarily. I have zero proof that the end result is better either way around. But I tend to have the reviewer on "high" and the coder on "medium" for whichever model my instinct thinks is best for the task. I think it is really hard to "prove" which one is better at this point as so much is dependent on AGENT.md/CLAUD.md, prior documentation/plans the code etc. If someone tells me one is better than the other I take it with a grain of salt. When dumb things happen I simply blame both of them - they are team afterall.
Ohh this comes in a really good time!
I mean personally I'd just like to use OpenCode with all the providers, if their desktop app was a bit more polished and Anthropic wasn't so restrictive. There's also Paseo, but it has some issues with OpenCode sub-agent liveness checks (I've seen them hang, though the same happened with Kepler, might be a GLM 5.3 issue idk).
> It felt to me that Codex created a much simpler solution in terms of code architecture than Claude.
This feels odd, cause I've seen people say the exact opposite thing, that the GPT 5.x models seem to love overengineering etc.
> The output of the Codex agent harness is much more “technical” than the one from Claude. Claude feels more like your colleague in a Tuple session writing to you while Codex feels more like a version of Data from Star Trek.
This is very much preferable to me omg, maybe I should give OpenAI a look again.
>> I think the main difference I feel between Claude and Codex is that Claude tries to go above and beyond what is asked and guess what you might want and then directly do it, while Codex is more like a companion that does what you tell it but will not overdo it. It will stop at the first sign that it might be done.
Damn, my experience is the complete opposite of this. I have posted about it a few times, e.g. https://news.ycombinator.com/item?id=49348265
tl;dr I gave GPT 5.6 a small-medium sized ticket, which should have been several hundred lines plus tests. It ended up creating a 25,000+ line diff. Another GPT 5.6 Sol with fresh context looked at the worktree and said 98% of it should be thrown away. Claude thought the same, and suggested that several dozen compactions the model went through over several hours must have caused it to go adrift. I guess that's one consequence of having a relatively small context window.
I still use Sol quite a bit. I find that it's consistently the opposite of what the author describes: it's too relentless. It doesn't know when to stop. Opus is the opposite: it'll give up a bit too easily. If everything goes well that's not an issue, but often times it'll say things like "task is done, btw I couldn't do X Y Z" and X Y Z will be some important verification step that failed because another agent was using that resource or something.
At this point I trust GPT 5.6 mostly with surgical changes, or general codebase exploration tasks. It is a faster model, so it's easier to get small things done with it. For everything else I prefer Claude, despite its annoying tendencies.
I run sol on medium about 90% of the time. Maybe that's worth a try. Especially for a small change.
you hear things like this about every model. they're probabilistic and you can't trust them, although i doubt that kind of odd behavior would happen on low or medium effort levels. i find all of the models today pretty good at following instructions generally speaking. i'm sure you did /plan, but i rarely see it stray very far from the plan. Then again, I never walk away, since i'm always spinning up another task that can be done in parallel, and I don't let things run overnight because I'm not made of token cash (yet)
guys, everything is about the harness, not the model! I even use Hy3 for free from nous portal, yes, it finishes the task in 50 minutes instead of 5, as Terra of codex would do, but I have it under the same harness (Hermes Agent) so result is more or less the same and it costed me nothing and worked at background while I was doing other things :)
I believe that “it’s about the harness” captures an important idea, but I also think it’s helpful to consider the harness and the procedure separately.
The harness provides the model with its tools, context, and environment for execution.
However, I prefer not to have the model within that harness also bear the responsibility for remembering the process steps—like plan, implement, review, fix, and verify—deciding when to move from one to the next, and keeping track of the loop's state.
For tasks that need to be repeated, I’ve been moving that part into a reliable, deterministic runtime. Inside it, Claude, Codex etc simply take on interchangeable roles.
This setup makes changing models much simpler: the overall process remains consistent, and each role can be optimized independently.
I’ve been developing this approach as ctx.traits, if you're interested, here are the docs: https://ctx.company/traits/docs/quickstart/example/
I've been using Zed mostly with Codex session windows and its great. It is much easier to handle multiple sessions than in the Codex VSCode app and the interface is quite good.
I find Claude more often gets my intent without having to spell things out for it, while Codex gets hung up on minor details and over-engineers a solution for them.
Agree with most of these.
One thing I don’t love about codex/sol is I find it tends to overengineer and be overly cautious.
I was using it to do create some scraping + data processing.
It went kind of crazy on the provenance, need at least 3 sources of consensus before promoting facts type bullshit.
defined a bunch of enums and gates.
I just wanted scrape some site data and put it into a SQLite dB. Like chill codex.
I feel like Claude is better at that.
As a follow up.
I feel like codex/sol is better at well scoped hard technical problem.
Where it can sort of run this brute force analytical loop.
Like doing performance optimization or other search type problems. I think the math proofs are good examples of this.
Agreed, only LLM I can give a folder of packet traces from a multiplayer game and wake up the next day with a server that feels identical.
What, you don't like it proposing sha256 checksums and state enums for everything?? :D It does seem to have this predilection, but I find it calms down if I tell it to simplify for "this phase". Sure, we'll pick that up down the road.. I promise. :D
I've noticed that too with Sol (xhigh) it starts with pretty good architectural goals, but really get lost in the weeds with certification and validation. Like it won't trust native tools like (in my case packer, Ansible, gcloud) to fail reliably under possible error conditions, and insists on implementing custom verification.
It also doesn't have a clear idea of what the actual threat model is, and builds all kinds of extremely defensive systems to account for imagined hostile actors. I'm like "Dude, it's only our systems that are creating these SVGs, they're never going to be user supplied, so you don't need to write an entire validation and sanitation framework here."
It also seems to treat the desired initial state of something as a permanent invariant and designs elaborate tests to ensure that it remains that way. Then when you make one little change it has to go and update a ton of tests it created.
I've had to rip out a bunch of overengineered jank from several feature implementations, and in doing so I ended up having to create retrospective documents that warn against this kind of behavior that I'll have the model review whenever a plan begins to go sideways.
“Extreme defensiveness” is a good characterization.
I wonder if it’s an artifact of OpenAI’s values or rl training approach.
Also, it prob does make it perform better just not more efficient.
Great for the OpenAI employee working on security scanning who doesn’t have to pay for their tokens.
Not so much for the dev building their web app who is trying maximize their subscription.
Like hiring an aerospace engineer to build you a shed.
Yes, codex/sol is extremely meticulous and obsessed with details. It will happily massively over engineer things to reduce the number of failure modes as much as possible. It's up to the user to instruct it to "chill" if this level of robustness is not necessary for a given task.
I did the same this week.
The speed is the first big contrast; I have a routine multi-step skill that I run several of per week. Opus 5 was routinely taking 2 hours to do it, while older Claude models took around 20 mins; Codex restored that speed.
Second is legibility. Somebody wrote in one of the related discussions yesterday that Claude's current linguistic contortions could legitimately be considered damaging to mental health, which doesn't seem (too) hyperbolic to me. Codex (Sol) isn't perfect but it's much more direct. And so far I haven't seen it display much of an attitude, vs Opus's infuriating passive aggressive sulky know it all personality.
I slightly prefer Anthropic to OpenAI as a company, but I will vote with my wallet and discontinue my max subscription unless Anthropic does some serious damage control within the next week or two.
I don’t know what’s wrong with Opus 5. I’ve been using Code since November 2025 and Opus 5 is the first blatant regression I’ve seen. Like you said, it just goes off into an endless loop doing random busy-work type of stuff. That’s the best way I can describe it. It’s doing stuff, but it seems mostly like busy-work to me. I’m not saying the model is “dumb” it’s most certainly capable, its vision is better than 4.8 but however they post-trained it is a fuckup.
Also whole heartedly agree with the Opus 5 output being incomprehensible. It’s written in a way that I’d call spaghetti-tech-English. You can unravel it but it’s painful. Fables explanations is effortless and smooth. Opus 5 is user hostile.
My last experience with Claude: https://i.imgur.com/jYawPDY.png
I paid for Claude for only 2 months, each several months apart. Including a week of trying both Codex & Claude side by side on the same tasks with the same prompts.
I had been subscribed to ChatGPT/Codex at $20 for over a year and now I'm on my second $100 month. The whole experience is just so much better.
Claude is pretentious abrasive snob, codex is the blue collar guy that gets shit done in my experience.
I honestly would've used Claude more if not for the confusing presentation/font, I'm not an expert on this subject, Codex is just a lot easier on my eyes.
Yes I have tried different settings already.
Aren't these CLI tools? How do they get to pick the font?