It would be nice if this model would be good enough to update their typscript sdk (+agents library) to use, or at least support, zod v4 - they still use v3.
Had to spend quite a long time to figure out a dependency error...
bayesianbot · 1h ago
I've been extremely impressed (and actually had quite a good time) with GPT-5 and Codex so far. It seems to handle long context well, does a great job researching the code, never leaves things half-done (with long tasks it may leave some steps for later, but it never does 50% of a step and then just randomly mock a function like Gemini used to), and gives me good suggestions if I'm trying to do something I shouldn't. And the Codex CLI also seems to be getting constant, meaningful updates.
mmaunder · 1h ago
Agreed. We're hardcore Claude Code users and my CC usage trended down to zero pretty quickly after I started using Codex. The new model updates today are great. Very well done OpenAI team!! CC was an existential threat. You responded and absolutely killed it. Your move Anthropic.
Jcampuzano2 · 1h ago
To be fair, Anthropic kinda did this to themselves. I consider it as a pretty massive throw on their end in terms of the fairly tight grasp they had on developer sentiment.
Everyone else slowly caught up and/or surpassed them while they simultaneously had quality control issues and service degradation plaguing their system - ALL while having the most expensive models comparatively in terms of intelligence.
mmaunder · 56m ago
Agreed. I really wish Google would get their act together because I think they have the potential of being faster, cheaper with bigger context windows. They're so great at hardcore science and engineering, but they absolutely suck at products.
bjackman · 39m ago
I think this is being downvoted coz it doesn't seem to be really responding to the thread, and maybe it isn't, but for anyone who hasn't tried Gemini CLI:
My experience after a month or so of heavy use is exactly this. The AI is rock solid. I'm pretty consistently impressed with its ability to derive insights from the code, when it works. But the client is flaky, the backend is flaky, and the overall experience for me is always "I wish I could just use Claude".
Say 1 in 10 queries craps out (often the client OOMs even though I have 192Gb of RAM). Sounds like a 10% reliability issue but actually it just pushes me into "fuck this I'll just do it myself" so it knocks out like 50% of the value of the product.
(Still, I wouldn't be surprised if this can be fixed over the next few months, it could easily be very competitive IMO).
mritchie712 · 1h ago
Have you used Claude Code? How does it compare?
mmaunder · 1h ago
It's objectively a big improvement over Claude Code. I'm rooting for anthropic, but they better make a big move or this will kill CC.
EnPissant · 1h ago
My experience with Codex / Gpt-5:
- The smartest model I have used. Solves problems better than Opus-4.1.
- It can be lazy. With Claude Code / Opus, once given a problem, it will generally work until completion. Codex will often perform only the first few steps and then ask if I want to continue to do the rest. It does this even if I tell it to not stop until completion.
- I have seen severe degradation near max context. For example, I have seen it just repeat the next steps every time I tell it to continue and I have to manually compact.
I'm not sure if the problems are Gpt-5 or Codex. I suspect a better Codex could resolve them.
brookst · 1h ago
Claude seems to have gotten worse for me, with both that kind of laziness and a new pattern where it will write the test, write the code, run the test, and then declare that the test is working perfectly but there are problems in the (new) code that need to be fixed.
Very frustrating, and happening more often.
elliot07 · 1h ago
They for sure nerfed it within the last ~3 weeks. There's a measurable difference in quality.
conception · 1h ago
They actually just had a bug fix and it seems like it recently got a lot better in the last week or so
M4v3R · 1h ago
Context degradation is a real problem with all frontier LLMs. As a rule of thumb I try to never exceed 50% of available context window when working with either Claude Sonnet 4 or GPT-5 since the quality drops really fast from there.
darkteflon · 34m ago
Agreed, and judicious use of subagents to prevent pollution of the main thread is another good mitigant.
EnPissant · 1h ago
I've never seen that level of extreme degradation (just making a small random change and repeating the same next steps infinitely) on Claude Code. Maybe Claude Code is more aggressive about auto compaction. I don't think Codex even compacts without /compact.
Jcampuzano2 · 1h ago
I think some of it is not necessarily auto compaction but the tooling built in. For example claude code itself very frequently builds in to remind the model what its working on and should be doing which helps always keeps its tasks in the most recent context, and overall has some pretty serious thought put into its system prompt and tooling.
But they have suffered quite a lot of degradation and quality issues recently.
To be honest unless Anthropic does something very impactful sometime soon I think they're losing their moat they had with developers as more and more jump to codex and other tools. They kind of massively threw their lead imo.
EnPissant · 1h ago
Yeah, I think you are right.
bayesianbot · 1h ago
I definitely agree with all of those points. I just really prefer it completing steps and asking me if we should continue to next step rather than doing half of the step and telling me it's done. And the context degradation seems quite random - sometimes it hits way earlier, sometimes we go through crazy amount of tokens and it all works out.
tanvach · 1h ago
I also noticed the laziness compared to Sonnet models but now I feel it’s a good feature. Sonnet models, now I realize, are way too eager to hammer out code with way more likelihood of bugs.
FergusArgyll · 49m ago
It doesn't seem to have any internal tools it can use. For example, web search; It just runs curl in the terminal. Compared to Gemini CLI that's rough but it does handle pasting much better... Maybe I'm just using both wrong...
Tiberium · 37m ago
It does have web search - it's just not enabled by default. You can enable it with --search or in the config, then it can absolutely search, for example finding manuals/algorithms.
gizmodo59 · 40m ago
Use --search option when you start codex
ollybee · 43m ago
web search too is off by default
jumploops · 14m ago
Interesting, the new model uses a different prompt in Codex CLI that's ~half the size (10KB vs. 23KB) of the previous prompt[0][1].
SWE-bench performance is similar to normal gpt-5, so it seems the main delta with `gpt-5-codex` is on code refactors (via internal refactor benchmark 33.9% -> 51.3%).
As someone who recently used Codex CLI (`gpt-5-high`) to do a relatively large refactor (multiple internal libs to dedicated packages), I kept running into bugs introduced when the model would delete a file and then rewrite it (missing crucial or important details). My approach would have been to just the copy the file over and then make package-specific changes, so maybe better tool calling is at play here.
Additionally, they claim the new model is more steerable (both with AGENTS.md and generally).
In my experience, Codex CLI w/gpt-5 is already a lot more steerable than Claude Code, but any improvements are welcome!
Apparently today is the first release with MCP support? (v0.36)
simonw · 10m ago
This should probably be merged with the other GPT-5-Codex thread at https://news.ycombinator.com/item?id=45252301 since nobody in this thread is talking about the system card addendum.
ionwake · 12m ago
Can someone explain what this all means? Has codex just been updated to use chat-gpt 5 ? Or is this just extra info?
amrrs · 10m ago
It is a new version of GPT-5 that's been primarily optimized for coding. Hence this confusing name - GPT-5-Codex.
This model is available inside all OpenAI codex products. Yet to be available on Api
The model is supposed to be better at code reviews and Comments than the other GPT-5 variant. It can also think/work upto 7 hours.
Does Codex have token-hiding (cf Anthropic’s “subagents”)?
I was tempted to give Codex a try but a colleague was stung by their pricing. Apparently if you go over your Pro plan allocation, they just quietly and automatically start billing you per-token?
steveklabnik · 36m ago
I tried Codex with the $20/month plan recently and it did exactly what Claude Code does, stop and tell you “sorry, you’re out of credit, come back in x days.”
darkteflon · 31m ago
Thank you, glad to hear it. Sounds like my colleague might have had it misconfigured. I’ll give Codex a try then.
withinboredom · 1h ago
Codex always appears to use spaces, even when the project uses tabs (aka, a Go file). It's so annoying.
asadm · 54m ago
this + any coding conventions should ALWAYS be a post process. DO NOT include them in your prompt, you are losing model accuracy over these tiny things.
withinboredom · 39m ago
It helps to actually be able to read the diffs of its proposals/changes in the terminal. The changing from tabs -> spaces on every line it touches generally results in unreadable messes.
I have a pretty complex project, so I need to keep an eye on it to ensure it doesn't go off the rails and delete all the code to get a build to pass (it wouldn't be the first time).
ameliaquining · 33m ago
I think the idea is that your IDE or whatever should automatically run the project's autoformatter after every AI edit, so that any formatting mistakes the AI makes are fixed before you have to look at them.
withinboredom · 28m ago
Do you not look at changes in your terminal as it is making them?
ameliaquining · 23m ago
The thing in the terminal could also run the project autoformatter on the changes before displaying them.
wahnfrieden · 36m ago
You are poisoning your context making it focus on an unusual requirement contrary to most of its training data. It’s a formatter task, not an LLM task
In fact you should convert your code to spaces at least before LLM sees it. It’ll improve your results by looking more like its training data.
withinboredom · 29m ago
Go uses tabs. Full stop. There is no Go code with spaces. Not if they're using the built-in formatter, anyway. In any case, this is about the diff codex is outputting, not the code I commit. With Claude, I generally don't need to run `go fmt`, but with codex, it is absolutely necessary.
> Reason #3a: Work with the model biases, not against
Another note on model biases is that you should lean into them. The tricky part with this is the only way to figure out a model's defaults is to have actual usage and careful monitoring (or have evals that let you spot it).
Instead of forcing the model to behave in ways it ignores, adapt your prompts and post-processing to embrace its defaults. You'll save tokens and get better results.
If the model keeps hallucinating some JSON fields, maybe you should support (or even encourage) those fields instead of trying to prompt the model against them.
ameliaquining · 32m ago
Presumably the Go source files in the training corpus used tabs?
Der_Einzige · 17m ago
Stop telling the normies the secrets please! You've just harmed job security quite a bit for a lot of people!
dgfitz · 22m ago
The future is truly here, we finally solved the tab vs spaces debate. The singularity must be right around the corner.
wahnfrieden · 58m ago
Just use a linter hook to standardize style
lvl155 · 54m ago
I think it would be cool to see *nix “emulation” integrated into coding AIs. I don’t think it’s necessary to run these agents inside of container as most people are right now. That’s a lot of overhead.
simonw · 51m ago
You mean instead of them running the code that they are writing they pretend to run the code and the model shows what it thinks would happen?
I don't like that at all. Actually running the code is the single most effective protection we have against coding mistakes, from both humans and machines.
I think it's absolutely worth the complexity and performance overhead of hooking up a real container environment.
Not to mention you can run a useful code execution container in 100MB of RAM on a single CPU (or slice thereof). Simulating that with an LLM takes at least one GPU and 100GB or more of VRAM.
lvl155 · 20m ago
I understand your point but I basically find myself running all my agents in barebones containers and they’re basically short-run make-or-kill types. And once we ramp up agent counts, possibly into the thousands, that could add up rapidly. Of course, you would run milestone tests on actual container/envs but I think there might be a need for lighter solutions for rapid agent dev runs.
withinboredom · 4m ago
You do realize that there is virtually no overhead in running containers, right? That's the entire point of their existence. They're just processes, with specific permissions (to generalize it). Your computer can run thousands of processes without sweating.
sergiotapia · 40m ago
I signed up to OpenAI, verified my identity, and added my credit card, bought $10 of credits.
But when I installed Codex and tried to make a simple code bugfix, I got rate limited nearly immediately. As in, after 3 "steps" the agent took.
Are you meant to only use Codex with their $200 "unlimited" plans? Thanks!
wahnfrieden · 38m ago
Use Plus first
sergiotapia · 37m ago
Thank you - so to confirm Codex _requires_ basically the Plus or $200 plans otherwise it just does not work?
simonw · 12m ago
The new GPT-5-Codex model isn't yet available in the API, so if you want to try that model using the Codex CLI tool the only way to do that is with a ChatGPT account (I'm more sure if the free account has it, the $20/month definitely does). You need to then authenticate Codex CLI with ChatGPT.
OpenAI say API access to that model is coming soon, at which point till be able to use it in Codex CLI with an API key and pay for tokens as you go.
You can also use the Codex CLI tool without using the new GPT-5-Codex model.
Tiberium · 37m ago
You can use Codex CLI with an API key instead of a subscription, but then you won't have access to this new GPT-5 Codex model, since it's not out on the API yet. But normal GPT-5 in Codex is perfectly fine.
sergiotapia · 29m ago
That's what was in my OP, I used the API approach, but the rate limits were insanely low (seemingly?) the agent died after 3 steps in a single question.
Difwif · 1h ago
Is this available to use now in Codex? Should I see a new /model?
andrewmunsell · 1h ago
Yes, but I had to update the Codex CLI manually via NPM to see it. The VS Code extension auto-updated for me
Had to spend quite a long time to figure out a dependency error...
Everyone else slowly caught up and/or surpassed them while they simultaneously had quality control issues and service degradation plaguing their system - ALL while having the most expensive models comparatively in terms of intelligence.
My experience after a month or so of heavy use is exactly this. The AI is rock solid. I'm pretty consistently impressed with its ability to derive insights from the code, when it works. But the client is flaky, the backend is flaky, and the overall experience for me is always "I wish I could just use Claude".
Say 1 in 10 queries craps out (often the client OOMs even though I have 192Gb of RAM). Sounds like a 10% reliability issue but actually it just pushes me into "fuck this I'll just do it myself" so it knocks out like 50% of the value of the product.
(Still, I wouldn't be surprised if this can be fixed over the next few months, it could easily be very competitive IMO).
- The smartest model I have used. Solves problems better than Opus-4.1.
- It can be lazy. With Claude Code / Opus, once given a problem, it will generally work until completion. Codex will often perform only the first few steps and then ask if I want to continue to do the rest. It does this even if I tell it to not stop until completion.
- I have seen severe degradation near max context. For example, I have seen it just repeat the next steps every time I tell it to continue and I have to manually compact.
I'm not sure if the problems are Gpt-5 or Codex. I suspect a better Codex could resolve them.
Very frustrating, and happening more often.
But they have suffered quite a lot of degradation and quality issues recently.
To be honest unless Anthropic does something very impactful sometime soon I think they're losing their moat they had with developers as more and more jump to codex and other tools. They kind of massively threw their lead imo.
SWE-bench performance is similar to normal gpt-5, so it seems the main delta with `gpt-5-codex` is on code refactors (via internal refactor benchmark 33.9% -> 51.3%).
As someone who recently used Codex CLI (`gpt-5-high`) to do a relatively large refactor (multiple internal libs to dedicated packages), I kept running into bugs introduced when the model would delete a file and then rewrite it (missing crucial or important details). My approach would have been to just the copy the file over and then make package-specific changes, so maybe better tool calling is at play here.
Additionally, they claim the new model is more steerable (both with AGENTS.md and generally).
In my experience, Codex CLI w/gpt-5 is already a lot more steerable than Claude Code, but any improvements are welcome!
[0]https://github.com/openai/codex/blob/main/codex-rs/core/gpt_...
[1]https://github.com/openai/codex/blob/main/codex-rs/core/prom...
(comment reposted from other thread)
This model is available inside all OpenAI codex products. Yet to be available on Api
The model is supposed to be better at code reviews and Comments than the other GPT-5 variant. It can also think/work upto 7 hours.
https://cdn.openai.com/pdf/97cc5669-7a25-4e63-b15f-5fd5bdc4d...
I was tempted to give Codex a try but a colleague was stung by their pricing. Apparently if you go over your Pro plan allocation, they just quietly and automatically start billing you per-token?
I have a pretty complex project, so I need to keep an eye on it to ensure it doesn't go off the rails and delete all the code to get a build to pass (it wouldn't be the first time).
In fact you should convert your code to spaces at least before LLM sees it. It’ll improve your results by looking more like its training data.
> Reason #3a: Work with the model biases, not against
Another note on model biases is that you should lean into them. The tricky part with this is the only way to figure out a model's defaults is to have actual usage and careful monitoring (or have evals that let you spot it).
Instead of forcing the model to behave in ways it ignores, adapt your prompts and post-processing to embrace its defaults. You'll save tokens and get better results.
If the model keeps hallucinating some JSON fields, maybe you should support (or even encourage) those fields instead of trying to prompt the model against them.
I don't like that at all. Actually running the code is the single most effective protection we have against coding mistakes, from both humans and machines.
I think it's absolutely worth the complexity and performance overhead of hooking up a real container environment.
Not to mention you can run a useful code execution container in 100MB of RAM on a single CPU (or slice thereof). Simulating that with an LLM takes at least one GPU and 100GB or more of VRAM.
But when I installed Codex and tried to make a simple code bugfix, I got rate limited nearly immediately. As in, after 3 "steps" the agent took.
Are you meant to only use Codex with their $200 "unlimited" plans? Thanks!
OpenAI say API access to that model is coming soon, at which point till be able to use it in Codex CLI with an API key and pay for tokens as you go.
You can also use the Codex CLI tool without using the new GPT-5-Codex model.