GPT-5.6

https://openai.com/index/gpt-5-6/

by logickkk1 • 13 days ago

1561 1098 13 days ago

openai.com

https://deploymentsafety.openai.com/gpt-5-6/gpt-5-6.pdf

https://developers.openai.com/api/docs/guides/latest-model

https://x.com/levie/status/2075287443411222628, https://xcancel.com/levie/status/2075287443411222628

system22• 13 days ago

At this point, they are just changing the decimals to stay relevant and in the news.

dude2507113• 13 days ago

Anthropic should be grateful OpenAI did not borrow "Epic" and "Legend".

system22• 13 days ago

I expect OpenAI names to be "fabulous", "glorious", "empowered", "delicious" etc.

realty_geek• 13 days ago

Wow, the "Agents' Last Exam" graph looks unreal!

therobots9275• 13 days ago

That’s because it’s bullshit

alimhaq• 13 days ago

I mean the y axis is deceptive to make it seem like greater gains since it starts at 30%, when in reality the differences aren't great.

Even worse, it's not a fair comparison: they purposefully just used "adaptive" instead of "max" for Fable.

What about the graph looked so unreal to you?

tedsanders3• 12 days ago

Even worse, it's not a fair comparison: they purposefully just used "adaptive" instead of "max" for Fable.

We agree models should be compared on a fair basis. Unfortunately, adaptive was the only publicly available number. Anthropic doesn't generally let us run their models for evals, so we rely on whatever Anthropic or third parties have published. In this case, the Agents' Last Exam leaderboard has Fable Adaptive, but not Fable Max.

https://agents-last-exam.org/leaderboard

Would have loved to publish a full curve for Fable if anyone makes the data available.

Although we do bias toward publishing evals where we're ahead, we have historically been unafraid to publish evals where we're behind (e.g., GDPval). The point is give people useful information to decide what's best, not to trick people.

Edit: Now I see there's a second entry with xhigh effort. Not sure if that was added or recently or we skipped it.

(I work at OpenAI.)

sidcool• 13 days ago

The claims are pretty bold. I think 5.6 may exceed Fable.

Syntaf• 13 days ago

Ok long time Claude Code user here; lately I've started to realize there's other great models out there I should be trying, but I'm hesitant to leave Claude Code behind for something new.

What's the consensus today on codex vs claude code, does it really matter anymore?

Daedren• 13 days ago

Use a harness that doesn't lock you into a moat, like OpenCode.

AntonyGarand2• 13 days ago

Can't use a claude code subscription in another harness though

thebigspacefuck2• 13 days ago

FWIW Claude Code works with OpenRouter so you can use any model.

maxloh4• 13 days ago

Codex CLI is open source too. I don't think there is a difference.

akmarinov7• 13 days ago

Codex is open source and lets you use any model https://learn.chatgpt.com/docs/config-file/config-advanced#o...

magicalhippo• 13 days ago

You can use Codex with any endpoint compatible with OpenAI Response API[1], like llama.cpp.

[1] https://unsloth.ai/docs/basics/codex

indy• 13 days ago

You wouldn't be leaving Claude Code, just trying something new. If you don't like it just resume using Claude.

CuriouslyC6• 13 days ago

It never really mattered (except when codex was very new). If anything, codex's remote session integration is better, so outside of some "ultracode" orchestration bells/whistles where Claude Code is ahead, I think Codex is a better tool.

mountainriver2• 13 days ago

Agree, I think there was just a blind study that showed no one could tell the difference even though the users were avid they could

cmrdporcupine7• 13 days ago

I left Claude for Codex months ago. I was an early Claude Code adopter but I have found Codex consistently better since about the February time frame. And far more reliable.

It's more diligent and empirical and results focused, and less creative. It sometimes needs a kick to avoid a Zeno's paradox of incremental steps to get to the goal. But it produces more reliable code with fewer race conditions, unhandled negative cases, etc.

It's also better value from a $$ POV, or at least has been. This fluctuates a bit.

You're also free to use your Codex subscription with other harnesses, like opencode, etc. Unlike Anthropic. Plays better with others.

dgritsko• 13 days ago

I use Conductor pretty much exclusively and it makes it incredibly easy to try different models, even within the same workspace - definitely recommend giving it a shot. Whenever I'm forced to use the Claude Code app directly it just seems woefully inadequate compared to Conductor

bakies• 13 days ago

I spent the last couple days switching because Anthropic keeps locking stuff behind API pricing. OpenAI lets you do anything with your sub right now. I'm building headless and web interfaces around Pi.dev. I had this previously with Claude Code but they are going to lock away all those features. I think the Claude does a better job at being proactive to solving things, but I'm going to keep tweaking my harness to nudge gpt to do more in it's turn. Not sure!

postalcoder3• 13 days ago

There is so much less drama involved with the Codex world. You don't realize how oppressive CC is until you've escaped it. Outages, weird restrictions, degradation, accelerated usage, etc etc etc.

timcobb5• 13 days ago

Totally. My experience as well. After some time with codex you're like come on Claude can you just stfu! Haha. I now almost always instruct Claude with specific length requirements when I ask questions. Otherwise, it just blathers and blathers in the most annoying of ways. "Oppressive" is spot on in my opinion

jakswa• 13 days ago

I'll agree and expand on "weird restrictions" -- I used to check the claude usage graphs multiple times a day to see where I'm at on my weekly budget. With gpt 5.5 I don't think I'm working differently but haven't felt the need to check anything because I think I've hit my limit... once? on some egregious edge case scenario iirc

Amir6• 13 days ago

Let alone getting banned out right with no reason, zero updates after weeks, and not even being able to download your chat history (despite the feature being available (I assume they vibe coded it and it does not work!). My story below;

https://news.ycombinator.com/item?id=48597861

Cider9986• 13 days ago

Even less drama with open models like GLM.

tomComb• 13 days ago

Um, the 'codex world' is the OpenAI world and there is a ton of drama and product confusion there!

Anthropic has certainly had some drama inflicted on them by the US administration, but otherwise they have just had heads down and executed with great focus. That is why they have succeeded.

Yajirobe• 13 days ago

At least Anthropic doesn't bend down to Pentagon/Trump administration

matheusmoreira13• 13 days ago

accelerated usage

Can you post more information about this?

m_fayer• 13 days ago

And I know this is petty but the CC cli/harness just grates. It’s overcomplicated, performatively cutesy, and buggy. It’s in my way. The codex harness gives me what I need and gets out of the way.

arikrahman2• 13 days ago

For me the biggest shift was using Deepseek through an American provider with reasonix as the harness, making cache hits at a rate of practically free.

tandr2• 12 days ago

Which provider do you use, if you don't mind sharing? I tried Digital Ocean (looking for Zero retention and no training), but their context limits are rather small for DeepSeek inference.

wyre• 13 days ago

Claude Code is a massively bloated agent harness.

Try Pi: https://pi.dev/

blovescoffee2• 13 days ago

Pi is so “unbloated” that it’s extra effort to use. You can decide how much work to put into it. I get the trade off. But this is a big jump from CC. I’d recommend some middle ground like opencode.

AgentMasterRace6• 13 days ago

better, use oh my pi.

saberience6• 13 days ago

They are both excellent but excel in different areas. Fable is super super proactive and great for doing a LOT of work with a single prompt, also for creative work.

Codex is more details focused, often catches wonky bugs and correctness issues that Fable misses, feels more terse and less "friendly", more like a stern senior engineer versus a friendly talkative engineer (Claude). Codex is also better if you're already an engineer, Claude is better for non-engineers. I.e. Codex works better if you know exactly what you want and know the right way of explaining it.

wahnfrieden• 13 days ago

With the exception of Fable which is going away anyway, Codex is better especially after the last couple Opus releases. It’s also no longer slower than Claude.

You get much more generous usage from the 20x plan.

And you get far better uptime.

If benchmarks and early tester impressions are accurate, you also get access to Fable level capability at greater speed and lower cost (included in subscription).

petesergeant3• 13 days ago

Fable which is going away anyway

$2 says nah. You can't take Fable away in a week where GPT-5.6 and Grok 4.5 launch, if you want to hold on to customers.

kristianc4• 13 days ago

Codex has been good for a long time, more expensive but very focused on efficiency. Working with it feels faster and more to the point than Opus models and I trust it more with long-running jobs. Also regular resets vs being at the whim of Anthropic drama all the time is hella nice.

anukin• 13 days ago

Codex is cheaper on average no? I think the models are expensive but the token efficiency of the harness itself solves the problem.

timcobb5• 13 days ago

Anyone know what the deal is with the resets?

prospector1065• 13 days ago

Try OpenCode and you can point it at either model

sidrag222• 13 days ago

Personally, I started using openai models to mess with other harnesses. I was pretty oppositional to CC and how they don't let you kinda plug and play freely, or give transparency into -p usage with other harnesses. So i mix and match a bunch of openai and some chinese models im trying out into opencode. I keep hearing codex is great, on the tier of current CC, I've tried it and it just ate my entire 5 hour usage window looping without asking for clarification on something and none of it was usable. that was the only time i tried codex as i could got that same task done with maybe 20% of my window with my existing openai opencode workflow.

I had put a decent amount of effort into setting up that initial codex attempt and it went so poorly that i've been entirely uninterested in trying again. This was maybe a month or so ago, and i know stuff moves fast, but for me, i like the models, dont care for the harness.

thebigspacefuck2• 13 days ago

IMO LMArena is the best benchmark that avoids benchmaxxing

https://arena.ai/leaderboard/agent

5.6 isn’t on there yet but Fable leads by a significant margin atm

TranquilMarmot3• 13 days ago

The results here match up to my real-world experience using these models every day at work and switching between them regularly.

NiekvdMaas• 13 days ago

In my experience, for coding Codex is definitely far ahead of Claude Code, even when using Fable 5 as a model.

postflopclarity2• 13 days ago

you have a very strange experience

ralusek• 13 days ago

I use both constantly for different things. You don't need to be a one-model Andy

catketch• 13 days ago

Not sure there's going to be a consensus, but I can tell you that when i have codex review claude-written code, it finds important gaps and fixes. The reverse is also true. Both are powerful, but even better when used in combination

Jtarii• 13 days ago

Literally every top model is identical and anyone saying otherwise is engaging in astrology.

postflopclarity2• 13 days ago

anybody saying they're identical clearly doesn't use both...

Supermancho• 13 days ago

The outputs, ui, and overall behavior (tokenization) are not identical.

vessenes• 13 days ago

More literal, less fluid verbally, harder time understanding nuance, more correct code, fewer bugs. Less pretty UI. I switch back and forth but find I have less 'clean up' work with codex; more upfront communication though to properly specify. High hopes for 5.6!

217• 13 days ago

Consensus itself does NOT matter, omp is objectively the best harness for power users yet it has 0 hn posts about it, zero.

You're fully free to use and try anything and without caring about what others think is right

efficax2• 13 days ago

"objectively the best"?

trollbridge5• 13 days ago

omp is really good.

I have one non technical people in my firm using it. One is using it to assist with editing books, basically using it to gather up manuscripts from e-mail / Google Doc etc. submissions, and then switch models between a cheap one and Opus (for actually analysing the manuscript).

The other non-technical person has done really surprising things with it AI, like a long-running GPT 5.5 Pro chat session which is basically her expense tracker - it has an .xlsx file "carried" in the chat, and she just tells ChatGPT (or scans a receipt) whenever she has a new expense, and then prompts it in natural language when she needs a report. I'm looking forward to seeing what she can do with omp.

joe_mamba• 13 days ago

omp is objectively the best harness for power users

Care to detail this?

saberience6• 13 days ago

How can this be "objective"? Surely its subjective.

I've tried a fuck load of harnesses but keep coming back to Codex as my harness.

Avicebron• 13 days ago

The fact that I thought that this was amp misspelled until i someone validate omp and the checked myself indicates it's a subjective assertion at best.

ljm2• 13 days ago

I figured pi itself would be the best harness because it's barebones and you make it what you want. omp is to pi what doom is to emacs is what lazyvim is to neovim.

financltravsty• 13 days ago

Absolutely. It's the only harness that is actually RSI and not run by idiots.

rpdillon• 13 days ago

omp is amazing. Daily driver for me.

NamlchakKhandro• 13 days ago

Because it's a bunch of extension on top of on pi

maest• 13 days ago

omp.sh is unreadable. I've tried understanding what exactly this is and it's just a wall of edgy sounding slop.

ncr501212• 12 days ago

OMP feels like the Linux of AI

sk4rekr0w2• 13 days ago

Codex app is a much different experience than CC CLI. I would try it out for a couple days with the new model suite and see what you prefer after that.

simianwords7• 13 days ago

Codex UI is way way way better than Claude Code

- codex UI is much more responsive

- i get feedback about the progress easily

- the tool calls and results are very legible, I can click them and see the progress

- no one talks about this but the tool call and response notification are handled much more elegantly in Codex. In Claude Code, it is handled in a clunky way using loops which always causes some delay

- you can steer the conversation midway in Codex

- /side is underrated (/btw is the equivalent and is much worse in Claude Code)

- I have to admit subagents are handled better in Claude Code

timcobb5• 13 days ago

If you can afford it and you have something to justify the expense, I would get both. they're interesting to run side by side, you can hand things off from one to the other. Pretty neat. Unfortunately now I just want to have both :(

xur173• 13 days ago

I personally use opencode so I can swap between models and try different options. I'd say I prefer claude (fable and opus 4.8) so far, but curious to see where gpt 5.6 lands.

For personal stuff, I've been pretty happy with chatgpt's $20 plan. I believe it has considerably higher limits than claude's $20 plan, and it's enough for the personal stuff I play with (hermes, and some small coding stuff). Also allows me to keep up to date on openai models.

timcobb5• 13 days ago

The $20 GPT plan with GPT 5.5 lasted me, somehow, exactly one smallish fixup feature

drschwabe• 11 days ago

When you use opencode to use Claude and Chatgpt models ie- Fable or GPT 5.6 I assume you are getting billed on pure credits? I was under the assumption that you can only use your Claude/ChatGPT paid plans when using Claude Code or Codex. ie- that you would be paying way more via opencode since you would not be getting the extra limits subsidized by your paid plans.

qaq• 13 days ago

I use both especially for checking each others work. Pretty happy with results

nilkn2• 13 days ago

Codex has arguably been better than Claude Code for months now, but it's flown under the radar because it just didn't capture the same viral marketing effect and OpenAI in general has had more optics / PR issues than Anthropic amongst the online developer crowd. I use the word "better" not in the sense that the underlying GPT models are fundamentally smarter or more intelligent, but rather that as a product Codex is just simpler, cheaper, and abundantly reliable and low-drama.

hk__24• 13 days ago

I’d argue the opposite. I’ve switched back and forth from one to the other and Opus/Fable has been constantly better than any GPT in my daily work. It’s a bit slower but it does the things right, with as little code as possible, some comments where needed. Codex is faster but you always have to correct it because it got something wrong; it writes tons of code ("let me add a small helper") with obvious comments.

jrflo4• 13 days ago

Agreed. GPT 5.5 will come up with more straightforward solutions with far fewer tokens than Claude. Also, the usage limits are much more generous for Codex than Claude Code for the same monthly plan.

dboreham3• 13 days ago

Nudged by this thread, I've decided to switch from Claude to Codex for a bit to see what happens. But...I immediately became lost in their marketing vortex of confusion on plans and pricing. Anyone care to tell me which plan I should be using? On the other side I use the $100 Claude Code plan. We actually have a "Business" ChatGPT subscription already, which seems to be $50/mo/seat. OpenAI's web site offers a set of individual subscriptions (for parity with CC presumably) which I suspect weren't available when we signed up for ChatGPT. I think that in turn happened due to some web site feature it didn't allow for free users (uploading PDFs, something like that). Perhaps I should switch from that business account to an individual subscription for Codex?

Certhas• 13 days ago

That's a strange statement... It's been true for a while now that OpenAI has had much more generous limits than Anthropic on their subscription plans. And with the Fable ban/guardrails disaster, there has been a lot of frustration from people in these comment sections. And Anthropic fucked up Claude Code pretty badly for a couple of weeks during the 4.6/4.7/4.8 transition, which again was widely publicized. And they got a lot of flack over not allowing other harnesses anymore. And ChatGPT got some pretty viral wins on model intelligence when they cracked the high profile Erdos problem.

If anything the online optics have been bad for Anthropic for the last half year. OpenAI doesn't have optics issues, from my point of view they simply have the issue that they are the least trustworthy player at the frontier. The way they pivoted from their original mission is truly breathtaking, especially coming in gloatingly to take the government contract when Anthropic got kicked out for insisting the government does not use their systems for mass surveillance or autonomous weapons systems. You understand what that means, right? OpenAI models are now actively used/developed for mass surveilance and/or autonomous weapons systems.

I know there are plenty here who seem to value their own ability to use these models cheaply above all other considerations. Then OpenAI is a great choice, and much less restrictive than Anthropic. But their problem is not on the optics. It's on the substance.

nolok2• 13 days ago

I really want a good Claude Design competitor in Codex, it's hard to use the others after getting used to it and yet I find anthropic's model to have a much worse understanding of what looks good or not than OpenAI or Google models.

ramijames2• 13 days ago

What about cost?

Trasmatta• 13 days ago

Switched to Codex last week, and I'm already MUCH happier than I have been with Claude Code. Which surprised me.

dyauspitr3• 13 days ago

Honestly it’s the usage limits that are so generous that makes codex worth it even if it may not be exactly as powerful as Claude. The peace of mind that you can try a lot of things and make huge refactors and run extensive redundant tests without running out of tokens just makes the whole thing a much better experience. I tried coding with Deepseek and it was pretty terrible so the only reason codex works is because its abilities are close to or on par with Claude.

herpdyderp• 13 days ago

I keep trying Codex and it constantly produces terrible output compared to Opus. I don’t understand how my results are so bad?

davedx4• 13 days ago

I agree with this statement. And because it churns less tokens, it's just generally faster too - noticeably, throughout the day, across a range of tasks I get more shit done with Codex.

It's not better at reasoning on complex coding tasks, Claude Opus is still ahead there, but not by a lot.

beefsack• 13 days ago

I'd say Codex and Claude Code have different strengths and weaknesses. Claude Code is significantly better in terms of their subagent UI for example - being able to see the list of subagents under the input is great.

To be honest though, I've gotten to the point where I prefer the OpenCode UI. A big win for OpenAI is you can log in to your subscription in OpenCode, whereas this is not trivially achievable for a Claude subscription.

I was getting some really impressive cost efficiency today in OpenCode with the following:

  * Main session agent: gpt-5.6-sol (high) via OpenAI subscription
  * General purpose subagent: deepseek-v4-pro (high) via OpenCode Go subscription
  * Using `obra/superpowers` for subagent driven workflows
  * The main session only being allowed filesystem read permissions and everything else delegated

It was absolutely crunching through tasks without hitting the limit, and this combination is quite cost effective.

GPT 5.6 was picking up on quality and functional issues from DeepSeek and having it resolve them cleanly, and I didn't even get close to my quotas whereas I can usually blast through them. I feel as people get more comfortable with subagents and mixing and matching models in their daily work, Anthropic's walled garden stance will start to hurt them.

giancarlostoro• 13 days ago

Last time I tested Codex on a cheap plan, it barely lasted an hour? I think this was for the $20 plan. I was afraid to try the more expensive plan after that. Not sure, I might just outright rip my Claude Code bandaid if the current usage quotas do die off after the 17th or whatever date they said they would "return on".

maxloh4• 13 days ago

I wish they open source their desktop app and built-in skills one day. That would be a final blow for me.

maxloh4• 13 days ago

Edit: Found that their built-in skills are actually open-source: https://github.com/openai/plugins

wwind1234• 13 days ago

I've been using Claude Code, Codex, Gemini (now Antigravity) at the same time for half year now, ever since I dipped my toe into agentic coding. I'd say in general Claude Code and Codex are equally powerful, Gemini is lagging behind.

One thing I appreciate with Codex is, OpenAI nowadays sometimes just gives you quota resets you can bank, so when you use up weekly quota before the week ends, you could just reset the quota, to continue using Codex. I've been much less anxious about Codex quota because of this perk. I just used one reset in the bank yesterday, and still have 3 resets left. Whereas with Claude, when you've used 95% quota 3 days before the week ends, you'd be much more anxious.

On the other hand, Claude Code's /remote-control mechanism is extremely helpful when I am running it in the cloud and wants to monitor it or control it on my phone. Codex currently doesn't support this kind of usage. Codex only allows you to use your phone to connect to a session on your desktop, not in the cloud.

WhitneyLand• 13 days ago

Codex is supported well on iPhone/iPad, it’s inside the ChatGPT app.

It’s amazing how much work you can get done on your phone now, especially if you already have a design mapped out in your head.

_superposition_3• 13 days ago

I've been using codex app server. Works great.

https://learn.chatgpt.com/docs/app-server

EMM_386• 13 days ago

Yes - Anthropic badly needs this same "here's a reset, use it when you want".

It's vastly better this way. Sure, it may impact the bottom line but it's a huge customer satisfaction win.

When Anthropic randomly resets me and I've only used 2%, that's worthless. When OpenAI tells me I have 3 resets available to use whenever I want - it's wonderful.

matheusmoreira13• 13 days ago

OpenAI nowadays sometimes just gives you quota resets you can bank

That's actually pretty awesome. Anthropic's random resets often have me scrambling to launch huge sessions to make the most of them before the weekly rollover. The gacha-like mechanics are maddening.

throwaway219450• 13 days ago

I’ve found Codex’s overage to be much better value than Claude’s. A monthly $10 budget is plenty for my backup Codex usage, but on Claude Code that would be gone in a couple of days.

romanhn• 13 days ago

The banked resets have been a game changer for me. I've been sticking to 5.4 medium mostly because 5.5 seemed to eat into my quota significantly faster. The reset bank gave me confidence to seriously start using 5.5 high. Lo and behold, I have yet to actually need a reset, but I'm now less likely to explore non-OpenAI models since there's an escape hatch with new models in case a coding session gets a bit crazy.

petesergeant3• 13 days ago

In my projects, Claude writes and Codex reviews, and I've had a lot of code I've been very happy with out of that, although as of today, Grok _also_ reviews, and finds interesting new stuff.

mountainriver2• 13 days ago

There was just a study showing that when presented blindly no one could tell the difference yet users were avid they could

hk__24• 13 days ago

There _is_ a difference in the way Claude and GPT write. Last Friday I felt Opus was becoming dumb because it was writing like GPT.

aroman5• 13 days ago

Claude Code fan here... Codex is very good. Sometimes better. The killer feature is price.

After 6+ months of exclusive Claude Code usage, I was begrudgingly forced to try Codex once Anthropic rejiggered their limits such that I kept maxing out my $200/mo plan in just a few days. These days I pay both $200/mo plans, and it's just about enough to get me through a week's work (small game studio - infinite code to write!)

ValentineC3• 13 days ago

(small game studio - infinite code to write!)

Curious: what multiplier do you think your productivity has increased by, from before AI?

ryan_n2• 13 days ago

Genuine question/not a critique-are you actually reviewing all that code or just sending it and hoping for the best? I just can't imagine someone is reading/reviewing that much code every day, but maybe I'm wrong?

rib3ye• 13 days ago

It's not clear replies to this thread aren't openAI employees or incentivized influencers, but every benchmark has gpt-5.5 underperforming opus 4.8, sometimes by as much as 10%.

Can they all be wrong/paid-off?

novaleaf2• 13 days ago

I sub both codex and claude at 20x. I like opus+fable more than gpt5.5 because it seems gpt tries to finish tasks by leaving any ambiguity unresolved. claude seems better at surfacing open questions.

This is using the same AGENTS.md prompts, which were designed firstly for Claude use, so maybe it's something that could be optimized better if I understood gpt as well?

freely0085• 13 days ago

Is it you have Fable delegate work to Sol? How do you do that? Do you run it in Codex/Desktop app?

znpy• 13 days ago

I'm hesitant to leave Claude Code behind for something new.

Codex and Claude Code are not mutually exclusive, you can use both.

erichocean2• 13 days ago

I use Claude for planning, writing CRs, and code review.

Codex writes all of the code, no exceptions.

Works great, especially when you ask Claude to break up large CRs into roughly 10 minutes of Codex work each.

silksowed3• 13 days ago

Same here. I find the design, architecture, system design discussion to be better on Claude, but after Opus 4.6 I switched over to Codex for actual coding and love the results. I use both via the CLI and generally tell Claude to output the result of our decisions as a markdown that will be easy to read and implement by an agentic coding tool. Then I fire up Codex and read said markdown as the input of the session and way to build all the appropriate context needed. I see this as a way to step into letting the agents go run on their own and interact with each other, but I still like to steer so I put these manual steps in the flow. Letting the agents go off on their own and one shot big chunks is not reliable enough yet imo.

epolanski5• 13 days ago

I do exactly the opposite.

jghn• 13 days ago

I have found Claude Code to be so much better than other common harnesses that it's kept me solely in the Anthropic ecosystem.

YuechenLi2• 13 days ago

The answer is it depends. Claude's generally better at frontend and debugging tasks, while Codex is stronger at backend features and exploratory work. They have very different coding styles and thus very different strengths.

TranquilMarmot3• 13 days ago

Any actual data backing this up? Or is this just your personal experience?

osigurdson2• 13 days ago

I use both. Not because I am cool, but because it is cost effective for personal projects with two $20 / month plans. It is also nice to be able to see what the state of the art is like for both.

Personally, I find it very interchangeable. I open codex --yolo or claude with whatever there yolo flag is (have an alias).

urams• 13 days ago

If you can afford to test it seriously, running both in parallel, it's worth a test to see which you prefer. If you can't, don't bother. You're not likely missing anything since they are close to personal preference with most people I know who have meaningfully tried both preferring Claude

alexhans• 13 days ago

What's the consensus today on codex vs claude code, does it really matter anymore?

Consensus is probably the wrong word for the popular opinions reflected in HN that you might get.

I would recommend that you have 2 of each at all times when it comes to AI so you don't necessarily become overly locked to quirks of one thing. You'll soon realize that things move so fast that you just start internalizing common patterns instead of depending on one specific vendor.

I recommend that you try pi and codex besides claude, to get your own feel for it.

pkulak4• 13 days ago

I can't tell the difference between Fable and GPT 5.5. I tried Fable while it was in trial $20 mode, used up my whole quota, and it was great, but as soon as I went back to GPT 5.5, everything was the same.

But what I love about Openai is that they still let you hook OTHER harnesses up to a subscription. My Pi setup has been built up for a few months now into exactly what I want and moving over to CC or even Codex is really annoying.

Caveat: I vibe code in tiny little chunks. I see what I want to do, and exactly how I want it done, then prompt that, refine, what was output, then repeat. I bet Fable is better at building a whole app from a 2-sentence prompt; but that's just not important to me at all.

akmarinov7• 13 days ago

Same here - gave 5.5 a web design to implement and it sucked. Gave the same to Fable and it still sucked.

edumucelli• 13 days ago

Not sure about the consensus, but during an entire week I have done every task on my workplace with both Opus 4.8 and GPT 5.5. GPT won hands down. I would even sometimes copy the plans and solutions (using different Git worktrees) from GPT and paste it on Opus and itself would say GPT plans were better. At that point I have migrated. Fable is not enabled in our workspace so I have not tried.

Claude lost my trust around February this year when the plan would say nonsensical things as "delete this method" that was clearly a key method on that part of the codebase.

For personal projects I am using Codex 20$ plan and when that is over I use DeepSeek which is insanely good for the cost.

InsideOutSanta3• 13 days ago

does it really matter anymore?

They're different models with different philosophies behind them. This is anecdotal with a user group of 1, but in my experience:

Claude has a stronger personality and is more creative. If you give it vague instructions, it's better at filling in the blanks with reasonable ideas.

GPT-5.5 is better at following instructions. If you know exactly what you want, it will do it without going off the rails. It's also less likely to imply that you're dumb, but I don't really care about that. Some people do.

akmarinov7• 13 days ago

I’ve found that Claude is very literal. When I talk to 5.5 it gets what i want it to do, when I talk to Opus 4.8 it does what I say literally and doesn’t get the intent behind it.

pkulak4• 13 days ago

I wish models called me out more! I can’t count the number of times I’ve had an absolute shit plan, prompted it, and the model built it to a tee. Then I look at the code, and it’s an absolute mess, because it had to make my stupid idea work. Maybe I need a better system prompt.

athrowaway3z• 13 days ago

They blocked Claude from being used in a different harness as well squeezed the usage like crazy. Switched to Codex and haven't cared since.

Between the two the biggest difference by far is ... getting your harness / AGENTS.md / skills / tools set up right.

3371• 13 days ago

My experience is that Codex's auto review is extremely costly, with $20 on both sides, I can run CC with auto mode for longer than with Codex's auto review enabled. Also in my own experience Claude's usage is actually bigger than Codex, but I am not sure if that's due to I stick to 5.5 with Codex while keep Sonnet as the default to orchestrate other models in CC.

Razengan4• 13 days ago

I've subscribed to ChatGPT/Codex for over a year and tried a Claude sub twice 1 month each, with a gap of several months in between.

I tried them both side by side, mostly for reviewing existing Godot/GDScript code, or sometimes generating Swift Mac apps, including converting ancient relics I wrote eons ago in Visual Basic on Windows

Codex was consistently better than Claude: https://i.imgur.com/jYawPDY.png

Besides the useless "This is good" findings while reviewing and the excessive "oops you're right" backtracking, Claude's atrocious UX and borderline "spyware" make me never want to try an Anthropic product again for a long long while.

firemelt2• 13 days ago

just try it you will back to codex because gpt is trash, I ask for refund under 7 hours

linsomniac• 13 days ago

I'm also a long-time Claude Code user here, though the last 3 weeks I've been doing loops having claude use codex to review until they reach consensus; uses tons of tokens but the result is really good.

I'm trying Codex as my primary the last day or so, because I'm at 98% use and reset in 3 days on Claude. I'm worried about a lot of our skills and CLAUDE.mds and the like getting lost unless I migrate them, but otherwise codex seems to be working great.

nvarsj• 13 days ago

The harness is so much better than cc which is a buggy mess. Gpt is also way faster than Claude. I’ve been using gpt for a while now and I know a lot of people that swapped away from Anthropic for multiple reasons. However - fable still seems to be the best coding agent, it’s just slow and the harness sucks. So I still use it in some rare cases like to review codex. I’m hoping 5.6 lets me drop it entirely.

ThunderBee• 13 days ago

IME it entirely depends on your work. I find myself using both daily for different things.

Codex with GPT 5.5 is much better at general SWE tasks but Claude Code with Opus is far better at complex reasoning tasks like reading and summarizing research papers, replicating experiments, identifying research gaps and proposing interesting follow ups.

yokoprime3• 13 days ago

I prefer codex for most tasks, but stil use Claude if i need to make something "nice but generic", i.e. a html artefact or touch up of front end code.

davidhs• 13 days ago

I recommend trying Codex too. In fact, I recommend running them side-by-side if you have the budget, e.g. have both independently plan the same feature or implement in a different worktree, or have them critique each other's work.

I personally find GPT-5.5 to be a better programmer than Opus 4.8, it is extremely thorough, but I don't like the code it generates ("austere"), and find Opus 4.8 to write more "human friendly" code. The programming comments GPT-5.5 makes is pretty awful where-as Opus 4.8 is good. I feel like Opus 4.8 is better at grasping my intention than GPT-5.5, and honestly find GPT-5.5 to be kind of "autistic". I do prefer the language (not the writing) of GPT-5.5, as I find the philosophical flowery language of Opus 4.8 kind of annoying.

I have only managed to try Fable 5 a little bit, which feels like a much more generally smarter version of Opus 4.8, that is much better a programming and grasping your intention, and I think even the intention of your code, and is _really_ good at spotting bugs or problems with logic in your code. It feels wicked smart but is extemely expensive. It feels smart in the sense like it has a "bigger brain" and is much more sensitive to subtleties/details.

These are different "brains", have different "personalities", etc. I think the best thing is to develop a feeling for it yourself.

novaRom• 13 days ago

I haven't tried Codex yet, but I for my tasks GPT-5.5 may correctly point to a proper direction but its code feels a bit weird. Opus 4.8 is way better in coding, and actually it's the only one who could catch very very sophisticated bug in a large codebase (I tried different models including GPT-5.5 and DeepSeek). Interestingly Gemma 4 under opencode running locally performs not bad at all, it's far yet from DeepSeek level, but it manages to understand tools quite well, and code quality is pretty good. So, for simple coding projects I can say local models already won. It's amazing how smart open models of desktop size have become today. I mean it's quite plausible to manage small codebase today relying on only open tools and local models, you don't need any subscription to produce high quality code, but yes I assume you already experienced and know what you're doing :)

noisy_boy• 13 days ago

I did the side by side between Claude code (effort medium) and Cursor (auto). Asked Claude to prepare a plan and asked Cursor to review it and it found tons of gaps in the plan. Cost-wise, it came out better too. I have been using Cursor daily (along with Claude) and the former has been 20-30% cheaper despite me spending more time on it.

teki_one• 13 days ago

I had great results combining the two. If you (or your employer) can afford then you can ping-pong the models in the plan phase (not really ping-pong as humans should get a say too) and then let one implement and the other review. I got better results working this way than just to stick to a single model.

setnone• 13 days ago

like others said in the thread: much less drama and i'll add much less attitude from the company and the models, overall i'm having much calmer experience with codex, hope it stays that way

purpleidea• 13 days ago

The codex software is garbage compared to Claude, but open source is the future, so you should at least switch.

marknutter• 13 days ago

It honestly baffles me how people can ask a question like this and get such a wide spectrum of answers in response. It's all so much based on vibes and anecdotal evidence. I've not really noticed much of a difference in capability since Opus 4.6 and I've used a ton of different models. They all work pretty damn well for me.

corford• 13 days ago

Personally I use Open Code with a copilot sub. Then all models are available in my session with just a /model and /variants command combo. Makes it super low friction to try different models & combos (my favourite right now is DeepSeek V4 Flash for initial PRD then Fable 5 high for implementation).

siva72• 13 days ago

Have been long time clauder but honestly codex feels much more liberating. Something you can't buy..

lizardking• 13 days ago

I consistently have better results with Codex for the work that I do. People have been saying that for six months, but until 5.4 the experience was sufficiently slower that it wasn't worth the switch. Making the switch was frictionless. Give it a try

Skidaddle• 13 days ago

A few less obvious niceties of Codex:

- built-in image generation using your subscription, which can be super handy

- can actually edit Google Docs and Google Sheets (Claude can only create new or sometimes append)

- I get a surprising amount of mileage out of the $20 plan

They both have their places for sure.

steve-atx-76002• 13 days ago

Set yourself up to be able to try / switch between models easily. I was a claude only user and just have my user level AGENTS.md for codex and others simply point at my user CLAUDE.md. Have a script that syncs my skills (just directories) between all models. Also, if you want to use /simplify or similar from claude in another model, you can ask claude for the prompt and put that in a skill for the other models.

SatvikBeri• 13 days ago

It's trivial to try another agent. You can spend $20 for a monthly subscription and ask it to import all your settings from Claude Code.

Kerbonut• 13 days ago

Claude Code is not the model, it's the harness. You can use any model you want with Claude Code to varying degrees of success. I use Qwen3.6-27b daily with Claude Code as an example.

small_model2• 13 days ago

Now we have various Opus+ level models (Opus/Fable, Grok 4.5, GPT 5.6) I prefer to focus on price/speed and harness as models are all generally good enough for coding. (Fable is overkill for 90% of work but is still level above). So I use Grok Build with 4.5 as its VERY fast and cheap, Codex is next best for me with sol/lunar 5.6. and Claude Code Fable for the 10% of tasks that need that level of reasoning. However I find Claude Code harness responsiveness much less than other two (all TUI versions) I wish they would fix this.

lavela• 13 days ago

Am I missing something or isn't sol/lunar 5.6 only out for like 3 hours? How did you evaluate?

forshaper• 13 days ago

Don't know about consensus, but I personally still find Opus to be better for sniffing codebase intent and checking things as a whole, while Codex seems more detail-oriented for individual files.

bmurphy1976• 13 days ago

I use both. Both are great. But in terms of Desktop Apps I think Codex has the better UI. It's more straightforward, just works, and has small conveniences like the open in editor icon.

Claude's very bloated and convoluted by comparison. Maybe you need the bloat (Claude Design), but I prefer the more razor's edge efficiency of Codex.

Model wise, I can't really tell. They all do what I want them to do most of the time and go off the rails occasionally. The question is increasingly becoming who's faster and cheaper and gives me more tokens, not who's better.

gregwebs• 13 days ago

I run my AI agent as a different user (in addition to using the sandbox functionality provided by cc/codex). It does not seem possible to run the Codex GUI as a different user. I can run the TUI (/Applications/Codex.app/Contents/Resources/codex) but it has the shortcoming that remote control is only available in the GUI.

I installed the Claude Code Codex skill provided by Anthropic and I am having Claude invoke it automatically to review all plans and changes. The nice thing about this is that for an additional $20/month pro plan I can extend the runway for Claude rate limiting and compare frontier model responses. I am looking for more ways now to work in Codex as a subagent that gets used automatically from Claude Code.

Lucasoato2• 13 days ago

I had to switch to Opencode from Claude code because the latter wasn’t supporting GitHub Copilot as model provider.

I didn’t think I could have found a better solution, spawning multiple subagents with different models is such a great thing.

I built in the past very small cli wrappers to call other models; Claude Code often refuses to do that, lies and does the job itself instead of delegating to another provider’s llms.

ra0x3• 13 days ago

My final answer on this is that we just can't say anything affirmative because all of our projects/codebases are completely different. I've gone back and forth on the "codex vs claude" being better, and while I'm currently of the believe that Claude is superior, I understand that might be the case for _my_ particular set of projects and _my_ personal way of interacting with the model.

OkWing99• 13 days ago

I used to have the CC $200 plan, and moved to Codex 6 months ago. I have the anthropic $20 plan + API billing for rare use. Use Codex daily.

Not having to deal with Anthropics constantly changing policies, token-gating, and carrot-and-stick marketing helps me to focus on work, rather than dealing with their company problems.

jeffybefffy5192• 13 days ago

IMO Codex has been the same rollercoaster ride as Claude. GPT 5.3-codex was incredible for backend/system tasks, GPT5.5 is better all rounder but weaker in some spots. There has also been many weeks when Codex's models were dumb AF. Same rollercoaster ride as anthropic between Opus 4.5 to 4.8...

IMO the two biggest problems not really being answered by both OpenAI and Anthropic are: 1. Why not make specific models good at specific tasks for Codex/Claude Code. Theres a handful of types of work here whereby small good quality models would do better than these generalised all purpose models whereby someone discovers Fable is bad at biology.... 2. Why cant they consistently run these models and keep them performing? Performance of the models seems to directly correlate with amount of compute available, but they dont talk about it...

jatora7• 13 days ago

Codex has been comparable for a while. 5.1-5.5 have competed closely with 4.5-4.8. Fable blew them all out, now Sol comparable to Fable again. Some slight tooling differences with skills and hooks but for the most part I think if people are so engineered into one CLI that swapping to another inhibits them, then that is an error in usage habits.

Codex historically will follow tasks more closely with less creativity, whereas Opus will do more than you specify. I wouldnt consider either one better due to this fact, just makes them useful for different situations. Generally they'll perform similarly for most tasks.

Opus and Fable dominate 5.5 in artistic design (pixel art, ascii art), and edge out 5.5 slightly in general UI design taste. Have not tested Sol in that regard yet.

So far in my usage Sol has been superior to Fable at graphics rendering engine optimization.

Codex will work longer, and in single sessions without as much subagent usage.

Codex only has 256k context but its compaction is absolutely next level. You will not notice compactions and they will happen multiple times during a complex task or set of tasks without you ever having to notice or care. Claude code on the other hand still has fairly poor compaction.

Codex has more generous usage limits, and they also give you usage resets (weekly+5h resets) that you can bank for a month or so. Not sure how often they give these out.

Codex also seemingly never has outages or weird delays like Claude code does.

OpenAI randomly resets usage just like Anthropic does

I would use both if you code often

snthpy2• 13 days ago

OT but how are y'all sharing your skills and agents across harnesses?

I have a bunch of Claude Code Plugins and yesterday asked Codex to make them accessible to itself. It wanted to rewrite most of it. I was hoping i could get by with some symlinks or something to avoid drift.

alchemism• 10 days ago

It’s almost as complex as compiling software for different runtime environments; it requires a knowledge artifact repository and publishing system, e.g. https://github.com/thinkingsage/context-bazaar

hagen8• 13 days ago

In my opinion Opus is waaayy better in agentic orchestration. It feels like it can natively deal with multiple subagents whereas gpt needs to be taught extensively.

davedx4• 13 days ago

I switch between both as my daily drivers.

I do almost all my regular coding tasks with Codex 5.5 on medium. Sometimes for niche edge cases, or when I run out of tokens on my Codex sub, I'll switch to Claude. Some recent examples where Claude was able to solve things Codex couldn't:

- 3D gamedev layout: I asked Codex to render a solar system in a certain camera positioning, saying it needed to fit the planets of the system to the viewport. Codex just couldn't do it, even on high reasoning: Claude Opus did it first attempt.

- Tricky Tiptap image drag-n-drop layout implementation: Codex failed this after numerous iterations. Claude Opus also struggled mightily to get it to work, but I think around 3 attempts it nailed it. Both of them ended up grepping the Tiptap code from node_modules - that's the kind of task it was.

But these are really isolated examples. Across all my projects (I have many; mostly TypeScript, but also things like C#), Codex "Just Works" (tm), with minimal prompting effort from me.

algoth12• 13 days ago

A great thing about codex is that, even if run out of usage, it finishes the task. Claude code will abruptly break the work and leave it there unfinished as soon as it runs out of tokens. Also, antrophic randomly resets the token usage which is annoying when I’m trying to ration them. While openai gives you extra resets that you can apply when you want to

fny• 12 days ago

I have them talk to each other via tmux to great effect on complex changes. Its great for auditing changes as work is done.

sdoering• 12 days ago

To me, the question of switching (and any recommendation) depends highly on the type of work you do as well as your setup in terms of harness and memory, context management, and so on.

I have my context managed in a structured (but nowadays way too big) Obsidian Vault. I also built myself a vector based "vault search" capability and have my harness use this as a tool to find thematically similar things across the different contexts, when needed. I also build a few custom skills and extensions for my harness to be able to do my work.

Talking about harness: I use pi.dev and have taken care of, that i set it up in a way as to easily be able to switch the intelligence layer without loosing context. Yes, there are differences in how well models perform, but if a model refuses a task - like gpt-5.5 not willing to build a downloading tool for Annas Archive - I switch the model to something less finicky.

Thus I was able to switch to gpt based models after about a year with Claude (and having had a Claude Max since the early days it was available).

I played a lot with other models recently, to see how stabl my setup is for switching, should something like Fable happen on a broader scale with the US government. As said, minor changes in tonality, minor issues ith the quality of long text being written by the model, but most of it is actually managed in by the tonality docs, guard rails, coding standards and the likes, I set up over the last 9+ months of intensive work with it (first in Claude Code, then Codex and now as said pi.dev).

So YMMV and it heavily depends on your setup. But I more and more treat those models as interchangable.

saberience6• 13 days ago

"On Agents’ Last Exam (opens in a new window), an evaluation of long-running professional workflows across 55 fields, GPT‑5.6 Sol sets a new high of 53.6, eclipsing Claude Fable 5 (adaptive reasoning) by 13.1 points. Even at medium reasoning, it beats Fable 5 by 11.4 points at roughly one-quarter the estimated cost. That efficiency extends to smaller models, which are essential to making intelligence more abundant and affordable: GPT‑5.6 Terra and GPT‑5.6 Luna outperform Fable 5 at around one-sixteenth the cost. "

Some pretty big claims and results! Excited to see how it feels during usage.

I use Fable and 5.5 extensively and I still find both have a place in my toolkit, i.e. Fable IS good but it isn't perfect, and it's still better to play them off against each other. I have Fable and 5.5 write plans and have them adversarially review each other's plans.

Having this amount of competition in the coding model space is good for all of us.

vamsiraju3• 13 days ago

I think this is the phase shift 5.6 (Sol set to Ultra) is bringing to the table. Until now we have become accustomed to asking models to continue and their natural inclination is always to stop. Now OpenAI have flipped it around and for the first time are asking us to steer or stop the model instead, and its own inclination is to keep going. We now have to decide when we need to steer or want to catch up on our understanding of the work done but it will keep going.

tipiirai• 13 days ago

Thought Fable was great

rvz• 13 days ago

Most importantly, the cost:

GPT‑5.6 is priced per 1M tokens across three model sizes: Sol is $5 input / $30 output; Terra is $2.50 input / $15 output; and Luna is $1 input / $6 output.

Just as expensive as Fable 5. But of course, another slot machine upgrade but the costs will keep going up and the open weight models from china will continue to race everyone else to $0.

Looking forward to the next version of GLM, Qwen, Deepseek and Minimax.

therobots9275• 13 days ago

Also watching deepseek closely. Seems like US frontier labs only know how to throw money at things as opposed to actually make smart improvements to the algorithms.

trollbridge5• 13 days ago

To be fair, DeepSeek doubled prices during the peak Chinese workday. (Which admittedly doesn't affect me much.)

celesian• 13 days ago

That's wrong. GPT 5.6 Sol looks to have the same price as GPT 5.5, apart from a new pricing fee for cache writes. Fable 5 is $10 input / $50 output.

sd9• 13 days ago

I haven't tried an OpenAI model for a long time, but with Fable going to API pricing soon this might be enough to get me to try codex.

danielbln2• 13 days ago

Seeing how Anthropomorphic just reset usage quotas back to 0 and the other day extended Fable sub inclusion by a few days, I have a feeling they might not drop Fable out of sub after all, because like you I would most definitely take a long good look at codex at that point.

matheusmoreira13• 13 days ago

It's not just the API pricing either, there's also the constant uncertainty. They pull the model then put it back up, they say the model is going away then suddenly it's not. And then there's the fact Fable is barely usable because it randomly downgrades to Opus out of nowhere whenever it thinks about exploits.

It's definitely good that Anthropic's feeling the pressure. Anthropic has worn out their welcome with this "safety" nonsense. If OpenAI actually lets me use the LLMs on a subscription without any of this bullshit, I'll definitely switch.

cbg02• 13 days ago

5.6 Terra (mid tier model) as good as Fable on DeepSWE while cheaper than Opus API pricing. Seems like a homerun.

osti5• 13 days ago

GPT usually performs better on DeepSWE while Claude does better on FrontierCode. These two coding benchmarks are pretty much the only ones right now that's still worth taking a look at imo.

DetroitThrow2• 13 days ago

DeepSWE seems to strongly, strongly prefer ChatGPT models. There were also major flaws in its methodology pointed out recently, that overlap strongly with the flaws OpenAI pointed out in its SWE Verified report.

I use both ChatGPT and Claude for engineering work on a daily basis, touching performance critical code to application backends to frontend work, and I've found that DeepSWE scores don't reflect my reality when I assess high quality output from the models/harnesses.

Not that Opus always beats GPT 5.5., but that 5.5 is ahead of Opus on a general benchmark smells off to me.

minimaxir4• 13 days ago

The developer's guide (https://developers.openai.com/api/docs/guides/latest-model) has some interesting semantic tips for using the model:

Intent understanding: GPT-5.6 can better infer the user’s underlying goal and intended level of work without you specifying every step. Continue to state important constraints, approval boundaries, and success criteria explicitly.
Original image detail: GPT-5.6 preserves the original dimensions of images sent with original or auto detail instead of resizing them to a patch budget or pixel-dimension limit.
Use shorter prompts: In internal evaluations, replacing long, explicit system prompts with minimal prompts improved scores by roughly 10–15%, while reducing total tokens by 41–66% and cost by 33–67%.
Avoid generic brevity instructions: GPT-5.6 is more sensitive than GPT-5.5 to instructions such as “Be concise,” “Keep it short,” or “Use minimal text.”
Control warmth: GPT-5.6 does not become meaningfully better when prompted to be broadly friendlier or more empathetic.

ravenstine• 13 days ago

Avoid generic brevity instructions

That part is confusing because it's not like they provide an example of how default GPT-5.6 output compares with GPT-5.5 both with default output and prompted for brevity. Whenever I use such prompts, it's usually because I want the model to give me the gist in a few sentences. I'd be stunned if GPT-5.6 was that concise by default. I would think that could "break" a lot of things for developers who didn't know to make prompt changes after upgrading to 5.6. What if you were expecting GPT to be as wordy as it usually is? Then suddenly your output is not wordy enough?

Smells like OpenAI trying its best to stave off financial armageddon for another few months. Then again, I'm not sure why they chose to waste so much output computation on verbal diarrhea all this time up to now.

anticorporate• 13 days ago

It seems like the way brevity instructions have changed is mis-aligned with how most people would expect to use them or are currently using them.

Here's the example they give:

Instead of asking for the shortest possible answer, replace brevity instructions with prioritization:
Lead with the conclusion. Include the evidence needed to support it, any material caveat, and the next action. Omit secondary detail and repetition.
Keep all required facts, decisions, caveats, and next steps. Trim introductions, repetition, generic reassurance, and optional background first.

Generally speaking, when I ask for a short answer, I want a short answer because I'm not really willing to read through a bunch of bullshit to get to a summary. Putting the onus back on me to assume what the model will return and write a longer prompt detailing exactly what information I want completely misses the point of why I'm asking for a short answer in the first place.

tshaddox• 13 days ago

If you conceptualize this as “there is an appropriate amount of brevity for each situation” then it would be expected for a better model to use different amounts of brevity if it gets better at determining the appropriate amount.

My view is that popular models by default output wildly excessive amounts of prose for nearly every use case, so if this changes in a new model that’s a pure win.

clhodapp• 13 days ago

It sure is suspicious that both Anthropic (adaptive thinking) and OpenAI (Avoid generic brevity instructions) both seem to be suggesting that the best way to improve outcomes is to entirely leave it to them to decide how many tokens get used.

I mean, it's true that it would be ideal of this stuff did just get figured out optimally behind the API, but there is definitely an incentive on their side to burn more tokens.

wrs• 13 days ago

could "break" a lot of things for developers who didn't know to make prompt changes after upgrading to 5.6.

How does this differ from the other changes in behavior in 5.6 that will also break things? New models always break things.

8note• 13 days ago

this is a dependency update.

shouldnt you have good testing for that and not deploy a version update when those tests fail?

RossBencina• 13 days ago

For sure verbal diarrhea can be a problem. I think there's a difference between a generic instructions e.g. "be brief" and contextual guidance: "I am an experienced software developer with a recent undergraduate degree in pure mathematics. Be terse, I will ask questions if I need clarification."

roncesvalles• 13 days ago

I think it is widely known by now that instructions to alter the LLM's "tone", things like asking it to adopt a persona ("you are the world's best programmer"), and overly broad directives ("make no mistakes") always gives poor results. Just state directly what you want. If you want something very specific, add more information. "Prompt engineering" is pseudoscience.

To put it another way, you will only get the benchmarked performance if you let it talk the way it talks by default. Trying to modify this neuters the model's IQ.

postalcoder3• 13 days ago

Avoid generic brevity instructions: GPT-5.6 is more sensitive than GPT-5.5 to instructions such as “Be concise,” “Keep it short,” or “Use minimal text.”

RIP Caveman skill. Six month good. Now skill dead.

delichon• 13 days ago

A Yoda skill, is there?

gershy• 13 days ago

Caveman speak make compression not brevity

mlmonkey2• 13 days ago

Avoid generic brevity instructions: GPT-5.6 is more sensitive than GPT-5.5 to instructions such as “Be concise,” “Keep it short,” or “Use minimal text.”

What about my favorite, "no yapping"?

astrange3• 13 days ago

It might need the longer answer to think about the question, so one approach would be to ask it normally and then ask it to repeat itself shorter.

elAhmo• 13 days ago

Use shorter prompts: In internal evaluations, replacing long, explicit system prompts with minimal prompts improved scores by roughly 10–15%, while reducing total tokens by 41–66% and cost by 33–67%.

A shorter prompt results in half as much tokens spend? I find this very hard to believe.

zeven7• 13 days ago

Maybe Codex has the same problem I sometimes have focusing while reading and has to reread the same sentence over and over again.

bulder• 13 days ago

If it's anywhere close to the same universe as smaller models in its behavior, a lot of time in "thinking" mode is spent on reiterating on any constraints given in a prompt. So the more constraints you give it, the more tokens it will spend going "Hold on, the prompt said I have to dot my i's and cross my t's. Let me go through my work to check that all the i's are dotted."

TacticalCoder• 13 days ago

A shorter prompt results in half as much tokens spend? I find this very hard to believe.

Should be relatively easy to test. And if it's true, just first use a very cheap near-SOTA model to first rewrite the prompt to a similar but shorter prompt before sending it to GPT-5.6.

pi.dev for example can control other harnesses.

An example: the other day for example I didn't understand why Claude Code CLI (which I hadn't used in a while) wouldn't let me cut/paste anymore (turns out they apparently fixed some long-standing scrolling and blinking SNAFU, but this modified how mouse selection/paste worked under Xorg but I didn't immediately realized they changed this)... I had to copy/paste the oauth challenge/response for I was logged out (maybe because I hadn't used Claude Code CLI in a while, dunno). But my usual copy/paste wasn't working and I didn't know how to fix it at first. And because I wasn't logged in, I couldn't use Claude Code itself for this.

My prompt was something like: "Screenshot the Claude Code TUI, transform the URL into a link, open that link in a broswer to get the oauth token, copy it character by character by simulating keypresses in the Claude Code CLI".

(remember: I had no idea how to paste with the mouse not with the keyboard, no I know but I was pissed off and wanted to be logged in immediately... So: another model / harness to the rescue).

(for the curious: it decided to use xdotool and use a 50 ms wait between simulated keypresses to copy the oauth token)

This worked just fine. And I that with a cheap model.

I think that just like Linux and Git owned many proprietary software, we'll soon have fully open-source harnesses orchestrating everything and delegating the work to proprietary tools (like "ChatGPT now Codex and vice-versa" and Claude Code)... If proprietary tools are even still needed at all.

Honestly I begin to wonder if they're even needed at all: the models, sure, while waiting for the open-weight ones to beat them. But those proprietary tools trying to lock people in?

I feel like the open source harnesses are already more powerful.

fodkodrasz• 13 days ago

So the user must be concise, but cannot ask the model to be concise... because it hurts the model...

epihelix• 13 days ago

Use shorter prompts: In internal evaluations, replacing long, explicit system prompts with minimal prompts improved scores by roughly 10–15%, while reducing total tokens by 41–66% and cost by 33–67%.

When has this ever not been the case? I don't think this is a GPT 5.6 specialty!

adam_arthur3• 13 days ago

Information density of the prompt is the most important factor in my experience.

And interestingly, LLMs seem particularly bad at writing prompts for other LLMs for this reason (you can guide them to be more dense, just speaking by default).

Conciseness is usually a byproduct of information density though.

daemonologist• 13 days ago

There was a fad a while back of building insanely long prompts - tens of thousands of tokens - including having models write prompts for themselves. I always thought it was counterproductive, especially if you're going to use the prompt more than a couple of times. (That said, the e.g. Claude Code system prompt is insanely long, so if you genuinely have a lot of information to provide maybe it's beneficial. Like, shorter is better, but you don't want to be under-specified.)

CuriouslyC6• 13 days ago

For Gemini 2.5 and ~GPT5.0-5.1, longer prompts with lots of explicit instructions and examples produced better conformance. Seems like heavily second guessing the models started to get counter productive around the end of last year.

artisin2• 13 days ago

Control warmth[1]

GPT-5.6 does not become meaningfully better when prompted to be broadly friendlier or more empathetic. Instead of generic instructions such as “Be friendly and warm,” use concrete guidance: Be direct and tactful. Acknowledge friction specifically when relevant. Avoid canned reassurance and unnecessary sign-offs.

Soo basically, my new 5.6 custom instructions: Be Jeeves and eliminate all friction from my life through immense processing power. Acknowledge friction specifically when relevant. Avoid canned reassurance and unnecessary sign-offs.

[1] https://developers.openai.com/api/docs/guides/latest-model#c...

firemelt2• 13 days ago

do we have similar guidance or page from anthropic for claude?

swatcoder• 13 days ago

can better infer the user’s underlying goal and intended level of work

This is a trap.

It's the optimistic fallacy that poisons all "consumer scale" machine learning products and what's going to effectively ruin these models as they keep chasing it in the same way that web queries were ruined, social media feeds were ruined, and media recommenders were ruined.

For the vendor, optimizing metrics across their whole user base, they always see positive technological progress as their system gets better at making assumptions and accumulating user engagement scores in aggregate. But for the individual user, most of which has some weird tail intent/interest and some of whom have many weird tail intent/interests, the experience quietly but catastrophically degrades. Output/results become more generic, more divergent with the underspecified "weird tail" intent, and more stubbornly hard to ever wrangle towards that "weird tail" altogether.

We've been watching this cycle happen for 20 years now and it's proving hard for anybody to escape because it works so well for the trillion dollar company driving it forward. But while each step might feel ergonomic and welcome to individual users, there's a frog boiling enshitification at play.

In pursuit of output quality and capability (rather than simply the vendor's user count), what we need rather than "makes better guesses" is "presses for more clarity", even where it feels kind of annoying.

Even among human professionals, one of the first hurdles of breaking out of junior tier work is gaining the confidence to press your colleagues and clients to be more specific in their thoughts and expressions despite their desire to have you do it all for them. But they're often coming to you with incomplete, muddy, and conflicting ideas for which there is no safe and correct assumption that you might just run with, and it's your expertise (i.e. relevant "intelligence") that's critical to bringing attention to that. To achieve professional progression, you need to learn to do that and to not just optimize appeasing the ambiguous client/colleague today in exchange for mutual expense tomorrow. To avoid enshitification, which is probably not possible, we need these models to be learning that too.

loufe• 13 days ago

I agree to an extent but it needs to be balanced. Receiving a half-baked, extremely verbose recap of thinking on benign details with Opus 4.8 or GPT 5.5 feels like an extraordinary loss of quality of experience compared with fable 5.

Yes it shares less, but I think the trade-off is you pay less in tokens and hopefully it's truly just not needing to say things because it truly does just better get what you're saying, think to read X markdown file or GH issue which contains the info, etc.

As long as I can still push back and get it to share its thinking on demand and I'm confident the model isn't actually basing things on poor premises, this is okay for me. I am more productive when not inundated with time-wasting check-ins.

That said, I absolutely lament the loss of the ability to access the thinking - I would happily read the "DANGER DANGER DANGER" internal gremlin thoughts fable 5 makes to verify something if they were accessed, and prefer that to a recap presented only for my benefit.

nullbio• 13 days ago

I want my model to help me build up its own infrastructure that instills it with the sort of constraints I want for my project, rather than have it behave generically and automatically for everything.

It should follow instructions incredibly well while inferring contradictions or gaps in logic and surfacing those to the user as suggestions for improvements and persistence.

I really hate how Claude just assumes you want to do X/Y/Z and goes off and breaks everything and you're constantly screaming at it STOP DOING THAT. Instead, it should just do the minimal things while building its own guidance along the way in a persisted memory, like, 'would you like me to do X, now, and in the future?' etc.

yobanate• 12 days ago

It's really easy to test and it's my personal go-to benchmark. I ask the model something deep and unproven, meta physical like "oh, I heard that magic mushrooms can open the mind, but does that mean some of the great ideas people had, famous people were due to that or was the idea already there?" Like, bullshit questions that nudge towards a known example (Steve Jobs in this case) that are hard to answer and then add something like "but I'm mincing my words here, you'll get what I mean". You'll get an interesting interpretation of the question back.

I use better questions than the above but will keep my questions safe so they don't end up in the model, the point is however, when the model repeats your question back to you and "gets" what you really mean, that's a good sign of intuition and also suggests you'll get a response back that hopefully matters.

stillpointlab2• 13 days ago

Avoid generic brevity instructions: GPT-5.6 is more sensitive than GPT-5.5 to instructions such as “Be concise,” “Keep it short,” or “Use minimal text.”

I used to go to a barber and if you said "cut it short", he cut it really short.

avaer• 13 days ago

I'm impressed. It feels like a faster Fable (probably due to the more efficient token usage). It performs roughly the same job, just with 4x less steps (gamedev).

Remains to be seen how the "shorter prompts" advice translates to homogeneity/collapse though.

someguyiguess2• 12 days ago

and 1/4 the output quality

egorfine2• 13 days ago

Intent understanding

This will totally make it brain damaged over a certain tasks. Sort of like the same brain damage that prompted OpenAI project managers to destroy ChatGPT.app today.

oezi• 13 days ago

Can you elaborate?

zahlman4• 13 days ago

destroy ChatGPT.app today.

... What changed, exactly?

speak_plainly• 12 days ago

It's crazy that they sort of deprecated chat in the new ChatGPT app.

__mharrison__2• 13 days ago

Serious question: what is a short prompt?

(For that matter at what point is it "long"? And does the rest of the context matter? Should it be short too?)

kordlessagain2• 13 days ago

"fix this shit"

bsenftner• 13 days ago

It creates the context of the request without including language or terms that activate additional areas of knowledge not necessary for an accurate reply.

mdgld3• 13 days ago

Why waste time say lot word when few word do trick?

kylecordes• 13 days ago

I wonder if it will do any better than past versions when one begs and pleads for it to get a job done using a concise, modest amount of code (as an expert human developer might), rather than responding to all prompts by shoveling in a large amount of code.

try-working• 13 days ago

they said it will do worse on that

zahlman4• 13 days ago

...tips for using the model:
Avoid generic brevity instructions: GPT-5.6 is more sensitive than GPT-5.5 to instructions such as “Be concise,” “Keep it short,” or “Use minimal text.”

I don't follow. Isn't "the model actually cares and will do what you say" a reason to use those kinds of instructions more liberally?

greggsy• 13 days ago

I think they’re saying it’s irrelevant now, possibly because it’s less likely to trail off on meandering thought bubbles.

rrvsh• 13 days ago

Click through to the link - it states that the model tends to over correct on brevity instructions by omitting required information

derpified• 13 days ago

Intent understanding

Does this mean ChatGPT will stop botsplaining things to me? I get it quite a bit more per unit time from ChatGPT than claude. Maybe that will change now.

(By botsplaining I mean when the AI explains some unstated premise of the prompt itself back at me as a correction when in many cases it's the motivation for the question in the first place)

jeffybefffy5192• 13 days ago

I found changing chatgpt's persona settings helped a lot with this!

embedding-shape2• 12 days ago

Never had that happen in ChatGPT itself, I almost always use Pro mode whenever I use ChatGPT, but what you say happens a ton in codex, when I look through the session traces it seems to happen because of the automatic compaction, where some assumption the initial pass did gets passed on as a question from the user to the part after compaction, which is a bit confusing. I think it was mentioned somewhere that the compaction got a lot better, but I haven't used GPT-5.6 enough to say if it's actually better or not on that.

exceptione• 13 days ago

  > Intent understanding: GPT-5.6 can better infer the user’s underlying goal and intended level of work without you specifying every step. Continue to state important constraints, approval boundaries, and success criteria explicitly.

I guess this has been achieved by training on user's chat history?

ryukoposting2• 12 days ago

Avoid generic brevity instructions

y'know, I don't think I will. I really, truly want one-word answers to any binary or multiple-choice question. If I want more, I will ask for it once the model has given its answer.

jitl• 12 days ago

that is a specific brevity instruction!

willchis• 13 days ago

The marketing team must've done research that said "people are starting to think that you guys are evil-water-stealing-lay-off-loving-bubble-bursting scumbags" and decided to really lean into the small family business and happy font vibes!

enraged_camel5• 13 days ago

CTRL-F: Fable

15 hits

Holy shit. They must be feeling very threatened by Fable if they're spending this much energy talking about it in the release notes for their own model.

therobots9275• 13 days ago

Apparently it significant outperforms fable on both an intelligence and cost index.

I don’t believe it at all and I don’t think anyone else does either.

trollbridge5• 13 days ago

I believe that it outperformed it on benchmarks.

cbg02• 13 days ago

In the past they received a lot of hate for not comparing to the competition.

InsideOutSanta3• 12 days ago

Sir, you do not understand! This is the Internet! You must always find a reason to be upset and/or complain!

BrokenCogs2• 13 days ago

yikes - looks like you need to go back to stats school

gemini - 13 hits

opus - 18 hits

So they are more threatened by opus than fable, or are they almost as threatened by gemini as they are by fable?

enraged_camel5• 13 days ago

The second paragraph has four mentions of Fable. I think that makes my case pretty clearly.

simianwords7• 13 days ago

Downvoted comment but I did find this comparison aggressive and tacky.

Laurel1234• 13 days ago

Anthropic fumble of Fable's release will go down in the history books, makes sense for OpenAI to run with it.

dude2507113• 13 days ago

Not available - checked and it's not there.

cactusplant7374• 13 days ago

They have really been stringing us along for the past few weeks.

tedsanders3• 13 days ago

As usual, even though GPT-5.6 is releasing today, the rollout in ChatGPT and Codex will be gradual over many hours so that we can make sure service remains stable for everyone (same as our previous launches). We usually start with Pro/Enterprise accounts and then work our way down to Plus. We know it's slightly annoying to have to wait a random amount of time, but we do it this way to keep service maximally stable.

The timescale is typically hours not minutes, so if you don't see it now, I'd try again later today.

We mention it will be a gradual rollout over the next 24 hours in the Availability section at the bottom of the blog but I admit it's pretty buried.

(I work at OpenAI.)

dude2507113• 13 days ago

Understood thanks; will 5.6 fix this issue that makes Pro unusable?

https://github.com/openai/codex/issues/30364

"GPT-5.5 Codex reasoning-token clustering at 516/1034/1552 may be leading to degraded performance on complex tasks"

jiggawatts• 13 days ago

Is this bug fixed with 5.6? If not, it probably doesn’t matter which version Codex users are getting because the overall result is dramatically worse than stated by Open AI advertising: https://github.com/openai/codex/issues/30364

trollbridge5• 13 days ago

It's available in Cursor now.

efficax2• 13 days ago

on Plus I see Terra and Luna, but not Sol

therobots9275• 13 days ago

Do they expect us this model is 15ppt more accurate at half the price of fable? What’s going on?

arizen• 13 days ago

"GPT‑5.6 delivers a step change in design judgment. With only high-level direction, GPT‑5.6 creates tasteful, ergonomic, and functional interfaces. Its stronger computer-use capabilities let it inspect and refine the rendered result—not just generate the underlying code or content—so it can catch visual and functional issues and apply finishing touches before handing the work back."

This one is really promising, as it may allow to close major gap with Claude in design/UI skills

GenerWork• 13 days ago

Agreed, I’m looking forward to trying it out. I think that the rise of visual design skills that are pretty clearly targeted towards Codex users has lit a bit of a fire under their butts.

HyperL0gi• 13 days ago

+1. I've been only using Sonnet/Opus these days for UI work because GPT 5.5 just can't do any of that. Its just really terrible. Eager to give this one a try.

silksowed3• 13 days ago

Computer-use is a big limitation that my 2015 Macbook Pro cannot handle. I find the Codex cli says it looks at the end output artifact but so often it fails to refine it into acceptable form. If it could use my computer screen and visual inputs for review, it might be able to actually design documents/powerpoints/etc. I'm juicing everything I can out of the 11 year old laptop and I'm honestly impressed at what it can still do.

semiquaver2• 13 days ago

How dare you point out that 2015 is 11 years ago.

eig• 13 days ago

Funny to see that they did not include Fable 5 in their GeneBench and LifeSciBench comparisons because "it does not answer advanced biology questions and refuses the majority of questions in this eval".

Winner by default!

paxys8• 13 days ago

Where’s the lie?

inciampati• 13 days ago

This is a major reason why I and a number of biologists I've talked to have canceled their anthropic accounts recently. Not working is not working.

fellowniusmonk• 13 days ago

I mean it's a fucking joke, I kept getting refusals on a code base I wasn't familiar with and it was literally just because there are some vars named DNA. Just absolutely stupid.

steve_adams_862• 13 days ago

It's so absurdly sensitive. It bailed out earlier today working on a TypeScript client for a sensor network API which happens to include some temperature and pH sensors for tanks, which yes, are used for biology experiments. But wow, we're degrees of separation from the actual biology work.

It's making it very hard to justify even trying to use Fable. When it works, awesome; it's legitimately good. But I can't trust it to do a task without deferring to Opus and that's really annoying at times. I want to know what I'm getting up front, not after the fact.

insanitybit3• 13 days ago

I'm writing a programming language with a "capability security model". That's enough to trigger Fable, it won't work on the language. It's hilarious. The mere presence of the word "security" seems to be enough to trip it up.

zmmmmm• 13 days ago

Yes it has completely turned me around - was all in on Anthropic but now it just looks too risky. Better off leaning into open models. Even if I found a way to work with the restrictions as they are, who is to say they won't suddenly change tomorrow. It's not worth it.

midtake• 13 days ago

You shouldn't know too much about biology, stupid human. You might live your life in an unexploitable way.

matheusmoreira13• 13 days ago

Anthropic's talk of "uplifting" people was so abhorent.

fblp• 13 days ago

oh that's sad, are the biolgy limitations for "safety"?

sunnybeetroot• 13 days ago

Yes

mnicky9• 13 days ago

Well it seems like they removed quite a few 3rd party benchmarks they used for GPT-5.5 release where Opus 4.7 was better and added many new benchmarks created by them where conviniently GPT leads.

Seems a bit more hand picked than usual to me..

matheusmoreira13• 13 days ago

Anthropic just refuses to allow Fable to properly code review my projects. It's so obnoxious. If OpenAI's Fable equivalent is better at this, that'll get me to cancel my Anthropic subscription and switch.

insanitybit3• 13 days ago

Given that Fable is so gutted and Anthropic added the absurd data retention policy for it, I'm going to advocate that we prioritize support for as many other models as we can at work.

weird-eye-issue• 13 days ago

Almost anything related to nutrition that goes beyond the very basic surface level questions is blocked

Schlagbohrer6• 13 days ago

I recently asked Claude to help me choose a single MOSFET (transistor) for a specific use case in a mundane circuit. The safety triggered and it ended the conversation and refused to continue. Gemini has also done the same thing to me. Looks like the big players got very spooked by the temporary Trump admin ban on Mythos and they all locked down way too hard.

murkt• 13 days ago

It triggered for me on a completely pedestrian game design prompt a couple of days ago. I’ve sent feedback and continued with Opus, but that was really unexpected

melenaboija• 12 days ago

The other day I asked Fable about fasting for 16 hours, and it flagged my question.

Pathetic situation, this one, where we are supposedly building a superintelligence while at the same time thinking that fasting is a biological weapon.

barbacoa• 11 days ago

My new favorite new passtime with frontier LLMs, keep telling them "I just ate a [non-food object]". Eventually it gets stuck in a loop of telling me to call 911, unlock my front door, and lay on the floor in case I lose consciousness.

newfriend• 13 days ago

Even at medium reasoning, it beats Fable 5 by 11.4 points at roughly one-quarter the estimated cost.

Sounds great.

Also latency looks very good.

GodelNumbering3• 13 days ago

Dirac (https://github.com/dirac-run/dirac, https://dirac.run/) now supports gpt-5.6. This thing does now seem to be on the chatGPT/codex accounts yet.

UPDATE: it is now available in chatGPT account also, they rolled it out

denysvitali• 13 days ago

Will be there soon according to the last commits in the codex repo: https://github.com/openai/codex/pull/31684/changes

Also, confirmed it works for me by using --model gpt-5.6-sol

BoorishBears3• 13 days ago

I used to pride myself on not being the "fonts too pointy, scroll too buttery" crowd! But AI has brought me full circle and now nothing removes my interest in reading even a single word on a page faster than purple gradient greeble-afflicted tailwind-slop models put out without stronger prompting/references

That being said, maybe 5.6 can fix that!

GodelNumbering3• 13 days ago

Thanks, I needed to hear that lol. Yes, the site was an afterthought, core work took/takes most my focus. I will look into un-slopping the site soon.

esafak3• 13 days ago

Does it support subagents?

GodelNumbering3• 13 days ago

yup it does

hughw• 13 days ago

If it's not dangerous enough to be classified as WMD by USG, who's interested.

big_toast2• 13 days ago

The cost & output token charts are useful but I wish I could view them more like a 3D surface. Like the CS:APP memory mountain charts.

I wonder how long model size and effort will be a few discrete points instead of continuous.

Tenoke7• 13 days ago

Is any of those comparisons about Pro vs non-Pro (Pro is only available in $100+ plans)? I am curious about that but I think Sol, Terra, Luna are different sizes of it without the Pro part, and I want to know how much worse do I have it on the $20 plan compared to if I upgrade.

gozucito• 13 days ago

The meat of the report for SWEs:

SWE-Bench Pro Sol: 64.6% Fable: 80% Opus: 69.2% (!!!!)

So, it still trails Opus, significantly, and is not a next-gen coding model like Mythos/Fable 5.

Disappointing to say the least, but somewhat expected.

paxys8• 13 days ago

Makes sense why they released an entire study yesterday discrediting SWE-bench Pro.

osti5• 13 days ago

And they'd be right, it's an almost saturated benchmark where even some subpar open source models score very well on. And most models are clustered within a small range so it really doesn't tell you much.

osti5• 13 days ago

SWE-Bench pro is pretty much useless now even though many ppl still look at it. OpenAI published a report yesterday saying so as well. Only look at DeepSWE and FrontierCode right now for coding imo.

SirMaster2• 13 days ago

Amazing, a company that does poorly in a benchmark says that benchmark is useless...

sk4rekr0w2• 13 days ago

You've overstated the conclusion. The SWE-bench series has had issues since its inception.

OpenAI no longer recommends SWE-Bench-Pro as a benchmark: https://openai.com/index/separating-signal-from-noise-coding...

bigfishrunning• 13 days ago

That's smart, they only recommend benchmarks that make them look better then their competitors.

kubb• 13 days ago

They have a fantastic media team.

mchinen2• 13 days ago

The frontier graph on all these benchmark are extremely in favor of 5.6 Sol over Fable, more than the best model comparisons in previous iterations.

I'd like to know how cherry-picked this is, and what tests it performed less overwhelmingly in, but I suppose that info is not going to be on this post.

If it pans out to be as good as it says, that's great. On the other hand, if this model is not overwhelmingly impressive over Fable, I will lose what remaining trust I had in these announcements.

therobots9275• 13 days ago

The proof is in the pudding and these benchmark stats will only work for so long before people lose interest.

thurn• 13 days ago

They do disclose that they scored much lower than Fable on SWEBench Pro, which is a pretty high-quality benchmark. I think it's partially just about what they choose to emphasize...

mchinen2• 13 days ago

I totally missed that, because in the charts they showcase for coding, the SWEBench score is not present, they only include it at the end of the post in tables. Hmm.

Great catch.

simianwords7• 13 days ago

SWEBench Pro, which is a pretty high-quality benchmark

No, doesn't seem like it

https://openai.com/index/separating-signal-from-noise-coding...

bel82• 13 days ago

SWEBench Pro should be ignored until they fix it or disprove the broken task accusations.

danielsamuels• 13 days ago

It's worth noting that OpenAI recently came out saying, "We don't think SWEBench Pro is worth reporting any more" - https://openai.com/index/separating-signal-from-noise-coding...

lwansbrough• 13 days ago

Didn't they also just post about how SWEBench is broken?

futureshock• 13 days ago

There has been a lot of chatter ever since the Mythos scores had been release that SWEbench pro had major contamination and that Mythos had memorized many questions that lacked the context to be solvable on their own. And now with OpenAI saying a large number of the questions are broken, I think it's worth taking that single outlier benchmark with some salt when the overall trend is that 5.6 is very competitive with Mythos at about half the price.

enraged_camel5• 13 days ago

The charts are also extremely difficult to parse. They seem auto-generated. Dataset coloring is atrocious.

Regarding your main point, yes, I agree. My impression (as someone who uses both Codex and Claude Code daily) is that OpenAI does a fair amount of benchmaxxing.

luciana1u• 13 days ago

GPT-5.6 Sol, Terra, and Luna. at this rate GPT-6 will be named after a parking lot and GPT-7 after whatever Elon names his next kid.

nharziro• 13 days ago

where is it? Still not accessible...

jstummbillig4• 13 days ago

"GPT‑5.6 is available starting today across ChatGPT, Codex, and the OpenAI API. The rollout is starting globally now and will continue gradually toward full availability over the next 24 hours."

bryceneal• 13 days ago

I find that 5.5 gives me far fewer refusals than Anthropic models for security and reverse engineering work. I hope the same is true for 5.6.

SwellJoe2• 13 days ago

Yeah, I pretty much had to switch to using GPT rather than Opus completely for all my security benchmarking and harness development. I was annoyed enough to blog about it: https://swelljoe.com/post/why-i-had-to-switch-to-gpt/

artisin2• 13 days ago

I wish they had kept their previous sensible naming convention instead of this celestial Sol, Terra, and Luna mumbo-jumbo

SwellJoe2• 13 days ago

I assume they're jealous of the Fable/Mythos hype. People talk about Fable like it's a whole new thing, rather than another incremental improvement over the existing best models (which has happened several times and continues to happen).

samuelknight• 13 days ago

There is an issue on the page that causes the benchmark tables to get cut off. If you highlight and drag right you can see a few more models like Gemini and Claude Opus. It's also interesting that they introduced explicit caching, which is something that only Anthropic had for a long time.

m3h• 13 days ago

We have an official pelican on a bicycle from the OpenAI livestream:

https://imgshare.cc/mz9xwut3

BrokenCogs2• 13 days ago

holy moly it's in THREE dimensions!

AGI solved

SirMaster2• 13 days ago

So it's failing epically because it generated a tricycle instead of a bicycle?

jstummbillig4• 13 days ago

"GPT‑5.6 is available starting today across ChatGPT, Codex, and the OpenAI API. The rollout is starting globally now and will continue gradually toward full availability over the next 24 hours."

terramex• 13 days ago

I am on Plus subscription and see Terra and Luna in Codex, but no sign of Sol. Will it be available only on Pro plans?

lostmsu• 13 days ago

I an on Pro and it still returns "The 'gpt-5.6' model is not supported when using Codex with a ChatGPT account"

UPD from announcement: "The rollout is starting globally now and will continue gradually toward full availability over the next 24 hours."

enraged_camel5• 13 days ago

My Codex app got upgraded to the new unified ChatGPT app. I don't see Sol available though. Only Terra and Luna. I'm on the Pro plan. Anyone else see it?

RobinL• 13 days ago

Same, no Sol (i'm on plus)

leonidasv• 13 days ago

Same here (Business Plan).

philip1209• 13 days ago

Will this run on Cerebas? I'm really looking forward to that.

paxys8• 13 days ago

Sam Altman confirmed during the initial limited release that Sol will run on Cerebras at 750 tok/sec.

kordlessagain2• 13 days ago

"I canna' give her any more, Captain!" - Montgomery "Scotty" Scott, Chief Engineer

apitman• 13 days ago

This is the part I'm most excited about with the new release, though I'm concerned plebs like me may never get a chance to play with it

simianwords7• 13 days ago

On the Artificial Analysis Coding Agent Index, GPT‑5.6 Sol with max reasoning sets a new state of the art at 80, 2.8 points above Fable 5, while using less than half the output tokens, taking less than half the time, and costing about one-third less.
That advantage extends across the family: Terra performs just above Fable 5, while Luna outperforms Opus 4.8; each does so in roughly one-third of the time, with about half as many output tokens, and at approximately one-quarter the estimated cost.

Wow. I don't believe it. Every indication and twitter post told me that Fable is much more intelligent than Sol and here we are told that even Terra outperforms Fable?

Not only that, Sol doesn't even come with run time classifiers. So it is even more suspicious.

What's even stranger is that OpenAI is directly referencing a competitor in this direct way.

I_am_tiberius2• 13 days ago

The way they talk about cyber security fixes makes clear that they are in bed with the government in order to get ahead of Anthropic.

culi3• 13 days ago

All of them closely collaborate with the government. LLMs are a national security priority and are vetted. Claude AI was used by Palantir's Maven to target the Minab school that led to a triple tap strike killing over 150 schoolchildren.

applicative• 13 days ago

The Minab disaster has every sign of being a pure humint fail the defense department decided to cover up with politically expedient AI blaming.

esafak3• 13 days ago

The DIA's Maven database was out of date: https://www.theguardian.com/news/2026/mar/26/ai-got-the-blam...

vinhnx• 13 days ago

GPT‑5.6 system card https://deploymentsafety.openai.com/gpt-5-6/gpt-5-6.pdf

browski• 13 days ago

Here's me using a Gemini chat log scraper (from Gdrive) then dumping my prompt+Gemini response into local AI

Never go over the free limits in Gemini Pro.

Gemini is great at research and architecture, and my 30 years experience in programming everything; for fun or work; means together there is little to no code slop.

Add to project repo some git submodules of reference source code; boom, bobs your uncle

Zero reason to sign up for OAI or Claude. With employers realizing the costs are more than employees, local models getting more powerful, and models in chips just a few years out, neither of the one note LLM companies without diversified services and R&D portfolios gonna last

mchusma• 13 days ago

Looks like a great set of models, but there are about 20 different thinking/model levels here in this family and they are very complex to pick the right one for the task

E.g. for GeneBench Pro, it looks like you would always use GPT-5.6 Sol over Terra/Luna, its pareto optimal.

For Agents Last Exam, you would maybe want Luna, then Terra, then Luna, then Sol as you increasingly budget for tasks.

I feel that there may need to be a new auto mode in many of these cases. It selects the best model and thinking given a particular problem.

Feels like it's going to have to go that way eventually, because here we have about 20 different model and thinking levels you could use, and they're not obvious which ones are right for the given use case.

WarmWash2• 13 days ago

8% on ARC-AGI-3, they actually got some traction going...

eugene3306• 13 days ago

note that ARC-AGI-3 has its rules changed.

before today all the contestants were capped at $10k

hereme8882• 13 days ago

So is 5.5-Daybreak still relevant for cyber security give. 5.6 capabilities?

twothreeone• 13 days ago

Wow the video is much better.. the PR spend clearly went up a lot. Mainly just showing "real people" doing "real stuff".

Jcampuzano23• 13 days ago

I really wish there was just an easy guide on when to use Sol vs Terra vs Luna, and it just moves further into confusing territory when it comes to naming.

The naming convention is especially difficult to decipher depending on what your native language is. Of course a latin language speaker might be able to easily determine oh yeah each one is slightly bigger than the other but I still think it borderlines too confusing.

That aside all the numbers look amazing, and I'll be happy to probably main this alongside grok-4.5 for a while comparing the two on price and efficiency.

I vastly prefer the direction that OpenAI seems to be going with token efficiency and performance compared to Anthropic who seems to be moving towards a world where you just token-max as much as possible ignoring any and all costs.

jstummbillig4• 13 days ago

Why would you need a guide for that now? We long had to pick different models (and thinking levels) by task and feel.

Jcampuzano23• 13 days ago

Previously it was much more obvious which model to reach for depending on your use case because they had the mini and nano naming conventions.

Getting rid of that seems like a step back. Just a personal nit though.

I've seen buzz about this elsewhere as well but to me effort levels seem more like spend limits disguised with another word. I don't think they should even exist.

bigyabai2• 13 days ago

The naming convention is bizarre and doesn't really mean anything to normies. Trying to pick between "Sol" and "Terra" is like asking the average person if they want the Max or the Ultra chip.

aerhardt• 13 days ago

My guide was to pick the best model on "High" for 99% of tasks.

taytus• 13 days ago

You don’t know what sol means? You don’t understand the difference in sizes between Terra and sol? I’m genuinely asking.

Jcampuzano23• 13 days ago

Did you not read the second sentence? Obviously I know what sol is given my first language being Spanish. I'm just speaking in a general sense that it can be confusing for others.

I already know plenty who had no clue what the difference between Terra and Luna would be.

adamrezich• 13 days ago

Sure—so, is Sol 109.2x better than Terra? Or 1.304x10^6 better?

Someone12343• 13 days ago

That isn't what "genuinely asking" looks like, you're criticizing using "questions" as cover. It isn't subtle, nor is it constructive.

I agree with them, Sol, Terra, and Luna are confusing names. They mean the same thing as GPT-5.6-Max, GPT-5.6-Plus, and GPT-5.6-Fast but require base knowledge for an analogy.

It feels like it was adding by the marketing department.

bloody-crow• 13 days ago

I do know what Sol/Terra/Luna mean, but was also confused for a second on the hierarchy. After doing a bit or research it dawned on me that they are arranged in the order of the sizes of the celestial objects but it somehow wasn't immediately obvious to me from the start.

Anthropic ships models with a helpful one-liner tag that makes the model hierarchy obvious. I think it wouldn't hurt if OpenAI did the same.

asadm• 13 days ago

it's simple: unless trivial TOIL, always use the highest at ultra max settings.

paxys8• 13 days ago

Okay Richie Rich

epolanski5• 13 days ago

Non sense, and time consuming.

jrflo4• 13 days ago

My guess is that it's the same for Haiku/Sonnet/Opus: Biggest model for architecture and high level planning and technically challenging problems, medium model for simple implementation tasks, small model is for nothing

XenophileJKO• 13 days ago

small models are good for "finding stuff" and "summarizing" in support of the large models.

newtwilly• 13 days ago

Use Luna. It's more performant than 5.5 and it's cheap. Hopefully it's cheap because it's more environmentally friendly than the bigger models. So you're doing a good thing. If it's a smaller model it may even be faster, but I haven't looked into it yet.

XCSme9• 13 days ago

In my tests, in almost all cases, using Sol on (low) reasoning is the best option intelligence/price-wise.

Luna is good too, for classification tasks or any pre-processing task that is not critical

energy1232• 13 days ago

I use the strongest model (5.5 now 5.6 sol) on the highest reasoning effort with /fast for everything. With a $200 pro sub I can't even use my weekly limit. And it's faster than using a weaker model that makes more mistakes which I have to waste time fixing.

paxys8• 13 days ago

I have found that higher reasoning doesn't always produce better results. Models often tend to overthink and get themselves in a bind. And tasks just take longer for no reason.

jtrn• 13 days ago

Same, I am actually able to reach my weekly limit, but when I start going below 30%, I switch to normal speed, and that usually gets me through the week.

I absolutely save money and time by constantly using everything at the highest reasoning. I guess my use case and needs are different from others, but I really don’t understand how it can be true when people say they don’t need the highest reasoning and best model. Every time I drop down, things are missed, code gets unnecessarily bloated, more mistakes, and more iterations to solve the same problem. I think it might be because I’m spending a lot of time in a legacy system that I’m trying to clean up, and given the messiness, one needs all the reasoning available to decode what the hell is going on in there.

steve-atx-76002• 13 days ago

I used to have the same experience until 5.6 sol xhigh. I have instructions in my code review skill and agents.md to encourage parallelism including multiple agents as long as quality isn’t impacted. I additionally instruct codex to not use less capable agents because at least with 5.5 this would seriously increase slop. Maybe sol is smarter about delegation. Hopefully because I’ll have to slow down or hopefully get approval for extra use credits. Now’s a great time for a limit reset if anyone from open ai is reading :).

droidjj• 13 days ago

I love how all the replies to this comment recommend completely different strategies for deciding which model to use.

rldjbpin2• 13 days ago

I really wish there was just an easy guide on when to use Sol vs Terra vs Luna

Their dev guide has the following:

Use gpt-5.6-sol for frontier capability, gpt-5.6-terra for a balance of intelligence and cost, or gpt-5.6-luna for efficient, high-volume workloads. The gpt-5.6 alias routes requests to gpt-5.6-sol

https://developers.openai.com/api/docs/guides/latest-model#u...

Razengan4• 13 days ago

I really wish there was just an easy guide on when to use Sol vs Terra vs Luna

Terra when you need to get shit done here on Earth, Luna for moonshots, and SOl for when you want to launch something into the sun..

..right?

Schlagbohrer6• 13 days ago

the size comparison didnt occur to me. I assumed the names were just random nice sounding focus-groupped marketing names.

torginus3• 13 days ago

It's just how LLMs work - these are three completely separate models trained in parallel, with different numbers of parameters and using different amounts of compute.

They could hide this behind a harness that picks the correct model for you, but devs don't seem to like that.

There's also the 'effort' slider, which I guess how many experts in the MoE are evaluated and how long reasoning chains are allowed to go on, which is the 'smooth' scaling you are thinking of.

jatora7• 12 days ago

isnt native english speaker

"i really wish this thing in my non native language was easier to decipher"

huh? if you dont know the words then read them in your native language. Sol/Terra/Luna are immediately unambiguous to an english speaker with any sense.

meetpateltech• 13 days ago

GPT-5.6 Sol sets a new SOTA on ARC-AGI-3: 7.8%

Sol is the first verified frontier model to ever beat an ARC-AGI-3 game

https://arcprize.org/results/openai-gpt-5-6

simianwords7• 13 days ago

Very interesting. My prediction is that Mythos would outperform Sol.

Also what does this tell about Yann LeCuns whole world model theory? Bro has been going on and on about it. He has made multiple wrong predictions on the trajectory of LLMs.

At some point his claim should be fully falsified no?

osti5• 13 days ago

Mythos probably wouldn't, otherwise they'd have included it in their release. Next version of Mythos probably will though.

And yeah.. Reality has not been kind to LeCun.

Maxatar• 13 days ago

Falsifying Yann Lecun isn't exactly a priority for anyone seriously working in this space.

bevekspldnw5• 13 days ago

“Bro” spent most of his career in the wilderness because everybody thought ML/NN/etc were a dead end.

I’d not wager against him having at one one more break though architecture before he retires.

raverbashing• 13 days ago

Notice how neither him, nor Ilya, nor Mira shipped anything relevant recently

It's telling

reasonableklout• 13 days ago

Mythos doesn't appear to be on the verified leaderboard for ARC-AGI 3

10xDev2• 13 days ago

Seeing the dramatic differences in scores just going from high to xhigh is just another demonstration of the bitter lesson: Just keep scaling search and learning. We are probably going to need a lot more GPUs.

vatsachak9• 13 days ago

I mean, theoretically you can solve every finitary problem with a brute force solution...

Richard Sutton specifically states that the search has to be smart. We know that the brain uses recurrent connections and is shallow. I think a lot more money has to go into architecture. Feed Forward transformers can only scale so far

altcognito3• 13 days ago

While I think this is true, remember as we get more efficient we just decide to scale even bigger. So more GPUs, and more efficient.

I agree with the sibling comment, effiency is probably the more important component at this point. We are hitting not just a practical engineering roadblock for scaling with current technology, I think we have definitely hit a financial and logistical roadblock for up scaling with the number of GPUs (on an immediate basis)

Razengan4• 13 days ago

We are probably going to need a lot more GPUs.

Or a breakthrough in algorithms etc.

The human brain, heck all bio brains, are proof that you don't need a lot of power or size for intelligence.

emp17344• 13 days ago

This isn’t really how it works anymore. Agents rely heavily on tool use and the agentic harness to perform tasks. Pre-training is no longer very effective.

bevekspldnw5• 13 days ago

These aren’t raw base models they are the result of a ton of RLHF and various adjustments.

Bitter lesson wildly overstated in this context.

Salgat• 13 days ago

Kind of refreshing though that the "throw more processing at it" scaling we saw in the 90s has returned in a different way. For a while we were really bottlenecked in our advances by relatively low levels of parallelism (most software used by your average user doesn't scale cleanly with more than a few threads).

dyauspitr3• 13 days ago

And dozens of data centers in every state so tokens are dirt cheap.

energy1232• 13 days ago

Dramatic difference

Isn't this just the difference between getting 0 right and getting 1 right?

navigate8310• 13 days ago

There goes my plan to buy a PC for the next decade

orbital-decay2• 13 days ago

Or a lot better efficiency.

dmitriy_ko• 13 days ago

And a lot more electricity to power them.

XCSme9• 13 days ago

Not always, in some cases, changing to a higher reasoning makes the AI doubt itself too much, and skip over the correct answer by overcomplicating the problem and polluting the context.

It would be nice to see on which categories of problems the extra thinking makes it better and on which it makes it worse.

hyperbovine• 13 days ago

Or a new model. The human brain does far more with far less.

andai5• 13 days ago

I said a few months ago, "man, Opus is great, but sometimes when talking with it I have the feeling like, this thing should be about 10 times bigger."

When Mythos was announced after that, I was pleasantly surprised to hear about it. But when it turned out to be only two times bigger, I was a little disappointed!

(I am even more disappointed with the safety filters, but that's kind of a separate discussion... "Fortunately" I find that I can usually edit my prompt by single character and get through...)

nbardy• 12 days ago

We’re definitely going to need a lot of Gpu’s

balefulboy• 13 days ago

it seems the older models were capped at 10kusd for the runs though?

maxnevermind• 13 days ago

I'm surprised it is that low. Are not all top AI labs "cheating" and workaround LLMs's low sample efficiency by hiring people to generate more data points - similar problems with answers, so they can train models on those and improve scores? A good benchmark for general intelligence probably should be a complete black box, no sample data given/leaked at all.

Kuinox• 13 days ago

Oh it's because the bench is lying. You need to pass each level without failing, if you fail a level, it count as you "lost" the minigame. The fact it start to get a score means it managed to get a 100% score on one of the minigame.

monk_grilla• 13 days ago

This is the first I have herd of this benchmark. Can someone explain how it in any way indicates how close we are to "AGI"?

Replay of Sol attempting the game: https://arcprize.org/replay/83543d22-8e1e-439a-8809-129ff1d9...

It seems a weird and arbitrary challenge for a language model to be expected to perform. It also seems like there are some harness/visual issues even in the first few steps, where it states that it hasn't moved when it clearly has.

drdrey• 13 days ago

the problems are general and abstract, domain specific knowledge and memorization don't help. Figuring out the rules, the goal, the controls, and how to solve in a reasonable budget all indicate some level of general ability.

andriy_koval3• 12 days ago

Can someone explain how it in any way indicates how close we are to "AGI"?

I think it is historical name. At some point when benchmarking was very undeveloped, this was targeting abstract reasoning and generalization, hence AGI.

gertlabs3• 13 days ago

We have it slightly ahead of Fable in our multi-agent coding evaluations.

Fable's main advantage is that its average solution size is smaller. However, GPT 5.6 Sol is a substantial improvement from GPT 5.4/5.5 which would write verbose, defensive code. 31KB for GPT 5.4/5.5 down to 26KB for GPT 5.6 Sol, with better performance for Sol.

Fable scores slightly lower, but with an average solution size of 12.2 KB.

Data at https://gertlabs.com/rankings?mode=oneshot_coding

dgfl2• 13 days ago

This looks like a good benchmark. Time and time again I keep giving OpenAI models the chance to win me back, but Opus (and Fable especially) just writes more elegant code and is a significantly more productive rubber duck for interactive discussions. I feel vindicated seeing your description of verbose and defensive code, and I’m a bit disappointed that 5.6 Sol’s solution is still >5x longer than the human solution and 2x as verbose as Fable’s. Do you have any insight whether any of that is comments?

I wonder why nobody has tried to optimize for actual code size or complexity metric, or at least why I haven’t seen more benchmarks that display this. GPT5.5 just keeps pushing more and more pointless indirection into every function it writes in my main project, it’s borderline negative productivity.

P.S. I’d be curious to see Cursor’s composer models in there, they seem to be among the best performing low cost models: https://artificialanalysis.ai/articles/cursor-composer-2-5-c...

CuriouslyC6• 12 days ago

Seems quite kind to Gemini models.

akoboldfrying• 12 days ago

Cost/task: $25.1K

Yikes

karma_daemon• 13 days ago

I wish model launches were like proper product releases

it's impossible to _try_ it out on release!

it's not on their codex subscription, or the web/mobile chatgpt interfaces, or aws bedrock, etc. I just cant find a working endpoint with the latest model after they announce

O5vYtytb• 13 days ago

The announcement says they're rolling it out over the next 24 hours or so. I think it's reasonable to do a slow-roll-out release for one of the most used products on the internet.

patapong• 13 days ago

GPT-5.6 Terra just showed up in Codex for me.

ssl-32• 13 days ago

For me, minutes ago, as a Plus subscriber:

I started up Codex CLI fresh. That version of Codex was 1.42.5. 5.6 wasn't in the models list.

After I updated Codex to a newer version (0.144.0), 5.6-terra and -luna appeared in the models list (but not 5.6-sol).

(It's impossible for me to know whether updating was causative or just correlative, but that's the timeline I experienced.)

bearmania2• 13 days ago

If OpenAI can add all the features from CC into Codex i’ll gladly switch.

bel82• 13 days ago

Which features?

OutOfHere2• 13 days ago

You posted the same comment twice.

bearmania2• 13 days ago

if OpenAI adds all the features from CC into Codex, i’ll gladly switch.

gavino• 13 days ago

What features are you missing? That you can't add through skills?

CjHuber• 13 days ago

Instead of requiring developers to script every step or passing every tool response back through the model, Programmatic Tool Calling in the Responses API can filter large amounts of intermediate data, retain only what matters, and adapt its workflow along the way.

this seems very interesting

aliasxneo4• 13 days ago

"We've extended usage of Claude Fable" message incoming any day now.

ftchd• 13 days ago

They reset all usage half an hour ago. It's back to 0% per week and session. No specifically Fable related.

halfmatthalfcat3• 13 days ago

Hahaha seeing this play out in real time is absolutely incredible.

user439289• 13 days ago

I let it work on two features while I was using mostly GPT 5.6 and it has already consumed 10% of the weekly Fable limit on Max x20.

GPT 5.6 on the Pro x5 plan is down to... 100%. It looks like they just reset the usage limits again. And I still have two resets on the bench.

Anthropic is going to have to up their game to compete.

matheusmoreira13• 13 days ago

Before the reset, a single 5h window would use up 5% of the weekly quota. Now it uses 10%. Thanks a lot, Anthropic.

mmaunder• 13 days ago

Or an allegedly even more dangerous model that they refuse to release. What a joke Anthropic has become.

big_toast2• 13 days ago

In the introduction video they say 5.6 Sol autonomously post-trained 5.6 Luna. Curious what this means.

vibcdingenjoyer• 13 days ago

Sounds like they gave it a goal to hit certain benchmarks and just let it have its way with the base Luna model.

block_dagger• 13 days ago

This produced a disturbing mental image.

2001zhaozhao3• 13 days ago

It means OpenAI and Anthropic are now in a RSI race with each other

jrflo4• 13 days ago

/goal tune 5.6 Luna parameters until performance is maximized across all benchmarks

ddxv• 13 days ago

I'm disappointed these models continue to be closed source and so expensive.

Open weight models being 10x or more cheaper is just so much more of an unlock than incremental gains for me.

AgentMasterRace6• 13 days ago

because they're stealing from the frontier models. they're gaming the benchmarks. look how bad glm 5.2 is on cursors evals. gmhit garbage , but it gets glazed as God tier.

anematode• 13 days ago

They're stealing, eh?

maxdo2• 13 days ago

cursor benchmarks with GPT 5.6 in picture, a good reason to stop using opus.

https://cursor.com/evals

The good news you don't have to send your dollars to China to fund ai dictatorship, in russia, north korea, african countries and south america.

AgentMasterRace6• 13 days ago

so the answer is use grok ?

maxdo2• 13 days ago

I'd say answer , the opus is no longer undisputed. grok + gpt models are very competitive + glm if you are ok to wait 3-4 times longer, unless you have some unique access to GPU

neuropacabra• 13 days ago

Is it available in EU? I only see 5.5 still :-(

yokoprime3• 13 days ago

Arguably not in the EU, but I'm seeing Sol,Terra and Luna on my account here in Norway

hereme8882• 13 days ago

I use 5.5 a ton. It's immediately apparent that 5.6 is truly a better model. Hope they don't lobotomize it later.

fractorial• 13 days ago

Sounds like a perfect fit for a minimal or bespoke harness?

lukebuehler3• 13 days ago

Oh man, I love capitalism spoiling us here. I was just enjoying my extra Fable credits, now I'll switch to using 5.6 this weekend. I was planning to ration my Anthropic credits, I guess now I do not have to. And I was half wondering if exactly this would happen: right when Fable usage credits were starting to kick in for people, OAI swoops in and takes the puck. As much the AI craze is crazy, this play by play part is pretty fun.

sidrag222• 13 days ago

top it off with anthropic stressing about the release and resetting usage to 0 for the week just now.

halfmatthalfcat3• 13 days ago

Anthropic just reset all limits, including Fable. Capitalism is spoiling us.

lukebuehler3• 13 days ago

Make hay while the sun is out.

mempko• 13 days ago

If hoarding is spoiling. You know what would be better than using fable and gpt 5.6, being able to run that level of model on your own hardware.

vamsiraju3• 13 days ago

prompts -> loops -> slingshots?

Its an extremely capable model. I think the way we need to approach works shifts again. We need to get our harnesses/workflows to let it gather some momentum on the first couple rounds but then we also need to structure it so that it can slingshot and accomplish the long range goal.

Razengan4• 13 days ago

Just a day before my $100 subscription expires, perfect

hyperknot2• 13 days ago

GPT‑5.6 also introduces more predictable prompt caching, including support for explicit cache breakpoints (opens in a new window) and a 30-minute minimum cache life.

Great to read they are moving away from the 5 minute cache defaults. Hopefully other providers follow soon!

hrpnk• 13 days ago

They highlight the cache write price now much more in the guide. Did it increase vs. prior generations?

hyperknot2• 13 days ago

There was no cache write before!

https://openrouter.ai/openai/gpt-5.5?endpoint=58e5b336-423e-...

https://openrouter.ai/openai/gpt-5.6-sol?endpoint=a54c5de0-8...

vatsachak9• 13 days ago

I wonder what increment of progress will be achieved by the next billion dollars

OutOfHere2• 13 days ago

Like the last time, again they failed to note whether there is an Instant model or when it might become available.

mNovak• 13 days ago

> approximately 700,000 A100e GPU hours of black-box automated red teaming

Amusing that they use A100e as the reference point to sound impressive. Different ways you could make that conversion, but based on FP4 FLOPs (yes it's disadvantageous to A100, that's the point), that's something like 200hr on a GB300 NVL72 rack.

Not nothing either, but far less astounding sounding than 700k hrs.

stavros• 13 days ago

Wait, what do you mean? 700k A100e hours are equal to 200 hours of a GB300 NVL72 rack? One GB300 NVL72, 72-GPU rack has equal processing power to 3500 A100e GPUs?

pizzafeelsright2• 13 days ago

maybe? ai says about *8.3 days* of continuous runtime on a single GB300 NVL72 rack

about a sprint's level of effort.

BoorishBears3• 13 days ago

based on FP4 FLOPs (yes it's disadvantageous to A100, that's the point)

The A100 doesn't have hardware FP4, and you'd be running a quantized model with some accuracy loss but unless this was natively trained on FP4*

* to add another layer, they own the model and could apply tons of post-training techniques to reduce that accuracy loss and probably already do

BoorishBears3• 13 days ago

I'm pretty sure Altman has spoken about giving a model 100k+ A100s specifically, this might be them being very literal

laichzeit0• 13 days ago

So glad Fable limits just got reset. Thanks OpenAI.

InsideOutSanta3• 13 days ago

Oh hey, thanks for the hint!

dwa3592• 13 days ago

This marketing video on the page is nice!! can't wait for the hardware to get cheaper to live the AI life i wanna live.

thimabi• 13 days ago

I’m interested in knowing how each of GPT 5.6’s variants fare in non-English writing/translation tasks.

GPT 5.5 has a tendency to write English calques and non-idiomatic prose in other languages. Although that can be somewhat tamed with detailed instructions and a corpus of confusing terms, the model’s output often reads like a literal translation rather than native prose. Since I notice these issues most clearly in languages I know well, it makes me reluctant to trust the model’s output in languages in which I’m less proficient.

Ironically, ChatGPT began as a simple text-generation tool, but much of its offerings and benchmarks now focus on coding and agentic workflows, while leaving behind what made it notable in the first place.

diwank• 13 days ago

i'm not happy with how openai is trying to pit 5.6 sol as a cheaper equivalent to fable here

for one thing, they said that on AA, sol is "within one point of fable" at 58.9 vs 59.9 but don't clarify that the latter is with safeguards where ~8% of the tasks got routed to opus

i'm not rooting for either and genuinely think that the token efficiency and cheaper price are important but this sort of thing just feels disingenuous :-/

mnicky9• 13 days ago

This is especially interesting because IIRC the AA benchmark is calibrated so that 1 point and greater difference is statistically significant.

2001zhaozhao3• 13 days ago

Huh, a good alternative just as anthropic's 50% weekly subscription subsidy is ending this weekend. Time to see if it's benchmaxxed or actually a strong leap over GPT5.5.

They also seem to really not care about alignment, or care about it in the wrong way. It's entirely missing in the blogpost and there are some concerning bits in the model card, seemingly treating CoT controllability as something to be "investigated" rather than the warning sign it's supposed to be.

mnicky9• 13 days ago

There's also this:

GPT-5.6 Sol’s detected cheating rate was higher than any public model we have evaluated -- https://www.lesswrong.com/posts/JFjNmPTbH8kL6xtp6/gpt-5-6-th...

lukebuehler3• 13 days ago

Very interesting: I wonder if the RL approach is diverging between Anthropic and OAI?

I noticed that Fable uses shell tools almost exclusively (even to search and edit files), compared to previous Anthropic models.

Having run some experiments with 5.6, I notice that it uses built-in file systems and provider native tools much more (not shell tools), compared to previous OAI models.

golangdev• 13 days ago

good alternative to anthropic

paul7986• 13 days ago

For writing GPT which i was subscribed to Fall 2024 to March 2026 (laid off) is superior to Gemini. Been using Gemini since March mostly and they offered a $10 a month plan so i took it. Though today realizing GPT is superior to help me write I am back to being a paying customer. Im in full swing mode to get back into the job market (get the heck away from UI/UX which is now a stupid career in terms of number of jobs out there and in the future there will continue to be less) pivoting into product management (can vibe code anything now) and or customer relations. Hopefully GPT helps me with this pivot and Im again gainfully employed!

super256• 13 days ago

On the tiny voids demo: does your Firefox js thread lock up as well, when you try to interact with it?

https://openai.com/index/gpt-5-6/#a-leap-forward-in-design

fisher-brett• 13 days ago

Yep, happens to me on Chrome as well

gorgmah8• 13 days ago

Just used terra ultra for exactly one prompt in codex and it ate through my full 5h window in about 10mns (20$ plan). The results look pretty good though. Luckily I have had my chatGPT subscription for a while and have a bunch of resets available (nice compared to anthropic).

Assuming I take the 5x plan it would give me about an hour of active sessions with terra ultra (maybe ultra is not good value regarding tokens?), not even using Sol yet. Does everyone using codex use the 200$ plan?

I normally use the 100$ anthropic plan and barely ever reach the usage limit.

altcognito3• 13 days ago

Do you know if you used sol/terra/luna?

jstummbillig4• 13 days ago

maybe ultra is not good value regarding tokens?

Well, yes, as explicitly stated on https://openai.com/index/gpt-5-6/: "ultra goes further by coordinating four agents in parallel by default, trading higher token use for stronger results and faster time-to-result on demanding tasks."

gorgmah8• 13 days ago

thanks, it makes sense, I'll stick to max from now on

ssl-32• 13 days ago

I use the $20 plan, but I don't code all day every day.

With Codex, it is my experience that I can churn through a 5h window in no time with newer models -- especially when they're new. So I tend to use fancier models for planning, and the less-fancy models for writing code based on that plan. I switch to the fanciest model if any part of this gets stuck.

If I've got a something big-ish to work on, I pay attention to the reset timers so I can get more of it done in one chunk.

Models seem to slowly get better/relatively less-expensive as they age. (It isn't clear to me if that's because the cost actually goes down, or if the allotment goes up, or if things get more efficient in unseen ways, or what. OpenAI is vague AF about what we get for the $20 that we pay.)

Squarex• 13 days ago

Same for me, but it produced much better answer than what would I expect from GPT 5.5 xhigh. Also the good think about Codex is that it always finishes the prompt, even when the limit was reached in the half.

ls612• 13 days ago

I think the most interesting part of this is that OpenAI is going way easier on the classifiers than Anthropic. They explicitly state that many defensive cybersecurity uses are supported and implicitly criticize Anthropic's stance on Fable's uses by saying that overblocking cyber requests is itself a major security risk as more AI models continue to advance in intelligence. I have so many questions as to what is going on on a game theoretic level in the AI space in the past two months, it seems like multiple actors have realized their incentives are really quite different than they originally thought.

goodmattg2• 13 days ago

I flip back and forth between whoever currently has the more powerful frontier model that isn't cost prohibitive - subscriptions only, API pricing a non-starter. Today that's Fable 5 which has been excellent, as soon as it's Sol I'll switch to that. The OAI/Anthropic harness behavior has mostly stabilized for me with consistent AGENTS.md that I sync with CLAUDE.md - I like pi (pi.dev) and have tried to build it up to get performance comparable to the two "first-party" harnesses, I'm just not there yet.

One major sticking criteria for not going with OpenCode / pi for all of my coding is I want access to the tier-1 frontier model of the day without API pricing - e.g. afaik I can't use Fable 5 via pi harness even though I have a subscription, so for this week I'm on Claude Code. It's not the need to Fable 5 for everything, but even if I just want the marginal intelligence benefit to stress test an architecture decision, it's a safety blanket to know there isn't a ~smarter~ model I could have used. And for my use cases, the doggedness and capability of these frontier models has been insanely effective.

My feeling is we're still in the Uber era subsidy period - the moment the subscriptions either try to lock me in longer than a month or stop OAI/Anthropic stop delivering frontier models in the subscriptions, I'm out - switching fully over to pi.dev or another OS harness and routing my token spend via OpenRouter or offloading to Qwen locally. Then I'll have to put an accurate dollar amount on frontier intelligence.

2001zhaozhao3• 13 days ago

I'm working on a multi-harness IDE that supports custom agent workflows and skills that are shared between any harnesses it wraps over. I think it might prove handy for a workflow like yours.

goodmattg2• 13 days ago

Would it currently support Fable 5 via the restrictions Anthropic is placing on usage... because that's my major blocker

RhodesianHunter2• 13 days ago

My feeling is we're still in the Uber era subsidy period

I often wonder whether this doesn't continue indefinitely.

Uber was able to do this because it was just them and Lyft playing second fiddle, with a huge barrier to entry once the network effects had kicked in.

It just seems like the model space has way too many competitors, + OSS/Local options for them to ever be able to jack up their prices. At least once the datacenter bottleneck has been cleared.

threatripper2• 13 days ago

Cars are pretty mature while AI is just getting started. Expect 100x price drop for the same quality.

flaburgan• 13 days ago

Zed IDE is allowing me to use Fable with Max x5 or any OpenAI model.

tmaly• 13 days ago

One of my best use cases for the short duration I have fable is to use it to create the plan and acceptance test files then use GPT 5.5 Pro to do an adversarial review on the plan then feed that feedback into fable to fix the plan.

xur173• 13 days ago

Looks like I have access to gpt-5.6-terra and luna. How does one decide between gpt-5.5 and gpt-5.6-terra? Pricing is similar, but it's hard to tell if it's better..

netcraft• 13 days ago

this is exactly my question. I would expect that luna is analogous to mini before, but is terra equivalent/better than 5.5 and Sol is a step above? or is terra nerfed and 5.5 is analogous to sol?

mnicky9• 13 days ago

Maybe Terra = mini and Luna = nano?

sunaookami• 13 days ago

Overloaded in Codex, no indication if it is already in ChatGPT and I can't use it in the API even though it says it should be available. Typical horrible OpenAI launch. Glad that Anthropic just reset the rate limits so I will go back to Fable again.

AgentMasterRace6• 13 days ago

I never have have the issues most people talk about ... I feel like most were never Devs before ai and don't know what they actually need done when prompting. that on top of not utilizing good tools such as a codebase indexer, lsp and a project scaffold.

revolvingthrow• 13 days ago

Benchmarks look really promising. Suspiciously good, even. I guess we’ll see soon enough.

My question to previewers: how are the guardrails for random joe that wasn’t personally blessed by the ai pope to access the non-nerfed model? Fable is a nightmare in this regard, but I’m not sure whether 5.6 also gets a critical side-eye from the gubmint when you ask it to fix bugs in your code (you filthy hacker, you).

cmrdporcupine7• 13 days ago

I almost immediately ran into "This request requires additional safety checks, which can take extra time. Hang tight or retry with a faster model for a quicker response, though it may be less capable of handling complex requests."

Which is something I've never seen with codex before, and I wasn't doing anything funky. Just writing CUDA kernels and benchmarks for them.

alex0015• 13 days ago

I was getting that regularly last week with regular 5.5 medium on the plus plan. I was doing benchmarking for a photo editor in Swift.

matheusmoreira13• 13 days ago

Is it actually usable though? Because the Fable situation is just obnoxious. If OpenAI's Fable equivalent is actually usable, I'll cancel my Anthropic subscription on the spot.

simonw6• 13 days ago

Here are 18 pelicans - six each for Luna, Terra and Sol at the six different reasoning effort levels (plus the price to generate each one): https://static.simonwillison.net/static/2026/gpt-5.6-pelican...

Or if you want to see some in 3D, OpenAI featured a pelican riding a tricycle, bicycle, pony and another pelican in their livestream this morning: https://www.youtube.com/live/Wq45rvPGNHs?t=1070s

yokoprime3• 13 days ago

Thank you Simon! Luna is surprisingly decent across all reasoning levels.

vecter• 13 days ago

I think all of Luna's are bad. The only decent one is sol @ xhigh. Even sol @ max is weird. Sol @ high and @ medium are ok, and every other single one across every model is bad.

emehex• 13 days ago

gpt-5.6-sol x XHIGH is my favourite

throwaw12• 13 days ago

something is wrong with Terra model series, most pelicans, except Max, looks bad

CryZe• 13 days ago

Seems to match the pareto frontier on Artificial Analysis as well. Terra is nowhere on it.

siva72• 13 days ago

Ok, I'll never use max effort again on OAI models..

isoprophlex• 13 days ago

Is that... an x-rated, censored pelican?

cma256• 13 days ago

Is the direction of the pelicans encoded in your prompt? Curious why they are all left to right with the exception of terra xhigh.

sbayg• 13 days ago

History moves left to right.

layer8• 13 days ago

Cultural bias.

hirvi742• 13 days ago

I like Terra High the best. That pelican is utterly yoked.

miohtama• 13 days ago

At what stages will models start to internally reflect the drawn SVG and automatically fix their own mistakes?

I assume multimodal models can do it already do it today if constantly asked "make it better"

simonw6• 13 days ago

I haven't tried this in a few months, but last time I tried a loop that rendered the pelican and asked for improvements the results were actually quite disappointing. Be interesting to try that again against GPT-5.6 at Claude Fable 5 though.

firebot• 13 days ago

AI really sucks at bicycles...

rsoto23• 13 days ago

LLMs really suck*

algoth12• 13 days ago

gpt-5.6-sol Max pelican didn’t skip neck day

aappleby• 13 days ago

Surely "how to draw a SVG pelican on a bike" has made it into the training data by now ...

conception• 13 days ago

And yet... only one is any good.

huseyinkeles• 13 days ago

Surely this comment is literally on every new model release post.

astrange3• 13 days ago

If that was the case in a non-trivial way you'd see mode collapse, but you don't, they come out differently.

ismailmaj• 13 days ago

Apparently plus users do not have access to Sol, so I'm really worried about the ugly Terra Pelican.

pupppet2• 13 days ago

Time to dump this test. Probably not a coincidence every version has the same rolling green hills, gradient blue sky, sun in the corner, etc.

fastball3• 13 days ago

On the one hand: yes, pelicans on bikes are definitely in the training set at this point.

On the other hand: the test is clearly not saturated, given that you can see a clear difference in output at the various reasoning levels / model versions.

dbt00• 13 days ago

Goodhart's law.

modriano• 13 days ago

I don't know. If they were training on this, I feel like they would be able to get the shape of a bike frame right; it's a pretty simple polygon, and a lot of the bike frames that are getting generated would be impossible to steer.

ceroxylon• 13 days ago

I partially agree, but in this case it kinda illustrates that it may not be worth using Terra on any reasoning level below high; those are some awful penguins on bikes.

threatripper2• 13 days ago

Waiting for the AMA on Reddit "Ten years ago I was responsible for the pelican department at OpenAI, AMA"

Night_Thastus• 13 days ago

I think the 'pelican test' is becoming useless. It's been around long enough that now I'm sure good examples are in the training data, and hell they might even do some hand tuning to make it do a decent job since they know people will ask about it.

But either way, with no real way to visualize the result of the text it starts with - it will always be stabbing in the dark. It can't understand conceptually what any of it should look like and then refine the SVG to improve it gradually. It just throws darts at a wall and hopes it comes out alright.

skybrian2• 13 days ago

I think it's still useful in a "hello world" sort of way. It means you actually tried the new model.

observationist• 13 days ago

Pelicans, maybe, but the point is to measure how good the "internal visualization" abilities are. Throw curveballs, like a unicorn with a duck bill serving coffee at a basketball court. An elephant playing a piano while its trunk swings a baseball bat at a tiny alien spaceship buzzing its head.

Have them use tikz instead of svg, or have it write code that moves the cursor and draws the thing in paint.

Compositionality and visualization are generally much, much better at each new generation / release cycle.

It's fascinating how well models have internalized visualizing things without actually having joint embeddings / broad multimodality.

tandr2• 12 days ago

Still fun to watch models trying their best :). I think "money spent" metric in this test is becoming the most interesting to watch. It is like looking at RT cost of "Hello, world!"...

irthomasthomas3• 13 days ago

Cool. I still find these a useful visualization of some the qualities of llms. Even if they did train for [animal] on [vehicle] svg, it's still nice to see at a glance how the different models and reasoning levels perform. Lunar misses part of the frame, except on max reasoning. While most of the others have a mostly correct bike at all reasoning levels.

I once used something like karpathy's auto-scientist to mutate the prompts and rank them with a vison model. Some of the winners where pretty neat. I think they have a lot more style than the gpt-5.6 ones. https://xcancel.com/xundecidability/status/20449185674144196...

ashu1461• 13 days ago

They said in the AI community, a pelican riding a bicycle is a good test to measure effectiveness of the model, wondering if they were referring to you, or is it really a standard in the AI community ?

Also would be good to have a tool where users can select models and instantly see each model's generated pelicans. That will make it easy to compare the output of different models.

jjice• 13 days ago

Simon did start the pelicans on bicycles as an SVG, but I think it's more of a fun goofy thing to see how the model performs at. I don't think it has a direct correlation to a model's performance though.

JeremyHerrman• 13 days ago

people are saying this is benchmark is saturated but all of these have occlusion issues, even sol max.

A skilled human artist wouldn't have both legs in front of the bike, or a single straight line representing both leg's crank arms.

MichaelZuo• 13 days ago

Yeah it makes no sense at all to dismiss the test, when even the very best examples are noticeably below what a skilled teenager could produce.

Dead internet theory? Semi-random parroting by real people? Or something else.

rsoto23• 13 days ago

this looks like the same shit from 4 years ago. give it up.

simonw6• 13 days ago

The first time I did this was actually less than two years ago - in October 2024 - and it's fun seeing how much better they've got since then: https://simonwillison.net/2024/Oct/25/pelicans-on-a-bicycle/

zniturah• 13 days ago

max effort sol clearly over-engineered

attentive• 13 days ago

somehow Terra really struggles here even compare to Luna.

semiquaver2• 13 days ago

The quality of sol on effort=none makes me think this test is saturated or they are benchmarkmaxxing this exercise.

walrus01• 13 days ago

I'm waiting for the day that the "generate a Pelican" test comes back with a SVG-art like illustration of a Pelican equipment case, like a model 1620 or similar.

https://www.google.com/search?client=firefox-b-d&q=pelican+1...

bombcar• 13 days ago

What's strange with this is the prompt "Photorealistic photograph of a pelican riding a bicycle down a coastal boardwalk, wings gripping the handlebars, webbed feet on the pedals, large orange bill, detailed feather texture, golden hour lighting, shallow depth of field, shot on a DSLR with 85mm lens, natural motion blur on the wheels" produced, well, exactly what I asked it for. I wonder if I tell it then to make it SVG ...

https://chatgpt.com/share/6a5009de-fff8-83ea-98ff-0da17d1d04...

rldjbpin2• 13 days ago

terra is just weird. in this nothingburger test, time nor higher costs seem to not strongly correlate with the aesthetics.

cmrdporcupine7• 13 days ago

Almost immediately ran into some the kind of gatekeeping I've heard Claude Code users complaining about with Fable. Not sure why, I just had it working on writing benchmarks for some CUDA kernels. Nothing security related:

"This request requires additional safety checks, which can take extra time. Hang tight or retry with a faster model for a quicker response, though it may be less capable of handling complex requests."

At least it gave me the option of waiting instead of just unceremoniously downgrading me. Appears to be making progress but... weird?

brcmthrowaway• 13 days ago

Benchmaxxed

itvision• 13 days ago

Weirdly, normally new ChatGPT releases are head and shoulders above anything else, but according to OpenAI's own evaluation, Anthropic's Mythos outperforms ChatGPT in quite a few benchmarks: https://openai.com/index/gpt-5-6/.

ChatGPT 6 must be deep in the pipeline and will be released within the next few months. Maybe that's why this release is versioned 5.6, not 6.0.

sahil87• 13 days ago

I think its more about branding than anything else. Anthropic played a masterstroke with the way they marketed, released, and then blocked Mythos. Now everyone know the Mythos "model" by name. ChatGPT 6 is trying to follow suite.

guybedo3• 13 days ago

It's good to see labs taking into account the cost/task.

Grok 4.5 is interesting because it's smart enough at great price. It seems gpt 5.6 is right there with great efficiency and great pricing.

Working with Fable has been a great experience, but at the end of the day, if you can get only 10% of your work done because it just burns through tokens, that's not that interesting.

I've been mostly using Opus and Fable high for planning and codex 5.5 medium for implementations. Claude is also the only model i can use for design tasks. If gpt 5.6 can finally deliver on the design side, it might be time to ditch the Claude sub and go full Gpt.

halfmatthalfcat3• 13 days ago

Using the Claude "superpowers" skill will downgrade models automatically, using Sonnet and Haiku for trivial things.

bob1029• 13 days ago

I am seeing some bugginess in testing:

  Parameter: reasoning_effort
  
  Function tools with reasoning_effort are not supported for gpt-5.6-sol in /v1/chat/completions. 
  To use function tools, use /v1/responses or set reasoning_effort to 'none'.'

Official OAI .NET library. Even when I override the currently experimental [?] flag to 'none', it will still occasionally throw this error (about 5% of the time).

I hope we aren't trying to push customers off the chat completion endpoint... Responses endpoint looks great on paper, but the business wants more visibility and control over the reasoning process than this product currently offers.

Edit: This is broken in my VS copilot setup too.

stillpointlab2• 13 days ago

I can't try it since it hasn't appeared in my Codex yet, but this is is necessary from OpenAI in my opinion. Fable is just so much better at understanding broad context. I only use GPT 5.5 for straight forward easy to describe tasks, and it does crush those. But I spend a lot more time steering Codex towards good design on broad concept type tasks, ones that Fable shows sometimes surprising clarity.

I look forward to seeing how it compares once I have access. Not getting tripped by spurious safe guard flags could be an advantage.

EugeneOZ• 13 days ago

GPT 5.6 Sol is a token hog. After implementing the task, it started some "reviews" I didn't ask for - they consumed 19.5M and 11.9M tokens, while the task itself was below 5M tokens.

breatheoften• 13 days ago

i wish they had renamed chatgpt to codex instead of the other way around ...

macleginn• 13 days ago

For context, I have access to MS Copilot through my workplace. To see what it looks like, I have tried to login through https://copilot.microsoft.com/ , where I was informed that my account, although recognised, is not yet supported. However, I can get more or less the same chat window, with access to all the data, through https://m365.cloud.microsoft/ A redirect could have been useful.

vamsiraju3• 13 days ago

I think 5.6 Sol is only as good as 5.5 or Opus 4.8 in terms of getting its given work done. It just has an uncanny ability to pickup more work that it can tackle next that the older models lack, or have not been trained to do before. Where folks are seeing a difference between working with Fable or 5.6 I think also boils down to this phase shift.

egorfine2• 13 days ago

Zero information on the knowledge cutoff. The model itself responds it's June 2024 which is weird given that GPT-5.5 has knowledge cutoff at August 2025.

mydreamof• 13 days ago

Bro these colors on chars are unbelievlable, I can not understand which is opus, which is fable, which is GPT...

senko5• 13 days ago

I love testing the new models by asking them to code a toy RTS game. Here's what Terra did: https://senko.net/vibecode-bench/2026/rts-gpt-5.6-terra.html (one try, in codex app, xhigh effort)

Comparing this to other models, I find it similar to GPT-5.5 and a bit behind Sonnet 5. You can see how other models fared here: https://senko.net/vibecode-bench/ (you can also fetch the prompt and the the 5.6 Terra resulting code on from that page).

I don't have access to Sol yet (on a Plus sub, which should get it according to what I've read), so can't do the more interesting test. I'll update the above page as soon as I get access - hopefully soon.

rsoto23• 13 days ago

So the measure of a model is how well they can recreate something they easily have thousands of examples of in their training data. There's probably a better base RTS on github somewhere for free.

ciefa3• 13 days ago

There's probably a better base RTS on github somewhere for free.

I... I think you are missing the point.

senko5• 13 days ago

Well, it is a silly test, not a scientific benchmark.

However, I would say it is a measure (not the measure). If you look at the entries, there's a lot of variation - definitely not something they memorized outright.

And the test itself is deceptively simple. You need to do canvas rendering, there's pathfinding, command queueing, terrain generation, etc. There are some subtle click handler bugs (various LLMs often stumble on those). And I ask the model to do it all in one file, further increasing the complexity of the task.

And the result is something that you can instantly evaluate. And if the result is any good, even play! So yeah, I think it's a fair test.

I'm sure it'll get saturated at some point. Actually I started with Minesweeper and switched to RTS last December, because Minesweeper was being saturated. I'm expecting (hoping?) the RTS test will last until the end of this year...

senordevnyc• 13 days ago

The goalpost velocity is approaching light speed…

Kiro• 13 days ago

Ask it to generate a completely bananas game idea and it will easily do it. Prototyping any type of game with simple graphics has been solved since many generations of models back. Claiming it's because it has that game in its training data is nonsense.

Sabinus3• 13 days ago

The 5.6 model article for this post has three examples of little web games.

There are plenty of little js web games anyway. The point isn't to make an actual game, it's to show coding ability, design and taste in a way that's more assessable than reading a codebase.

gorgmah8• 13 days ago

this is so cool: it's playable (even though super boring since there are no enemies) and you can feel that a few iterations would make it very usable.

Which model is the best at the moment, for this kind of stuff, in your experience?

senko5• 13 days ago

I'd say Fable 5: https://senko.net/vibecode-bench/2026/rts-fable-5.html

It even has enemies! (I'm not too mad about it not following my instructions because it can be fun to play :) And I generated that from Claude Code on my phone.

Sonnet 5 also produced a pretty nice version. You can see all of them here: https://senko.net/vibecode-bench/

ciefa3• 13 days ago

Very neat! Can't wait for the Sol version!

senko5• 13 days ago

Here it is: https://senko.net/vibecode-bench/2026/rts-gpt-5.6-sol.html

Clearly much better than the Terra version. I'd say its on par with Fable, and the observed differencies are more due to random luck and open-ended prompt, rather than model capability. (Edit: after some more testing, perhaps not on par - somewhere between Opus and Fable, is a better description).

Fable did better pathfinding and has more terrain variety, visually the map looks better, especially soft edges of the fog of war. And the enemies.

Sol took more care with tiny ux details, added help, and more building varieties.

zahlman4• 13 days ago

Could we see the prompts, though?

wj• 13 days ago

I did a quick comparison of models a couple of months ago by giving it a MYTXTADV.BAS file and give them all the same prompt to create a sprite-based version of a text adventure game I wrote in Basic over 30 years ago.

It was interesting to see where the approaches were similar and where they diverged.

senko5• 13 days ago

Here's the prompt I used:

Create a simple but functional real time strategy (RTS) game similar to old WarCraft, StarCraft or Command & Conquer games. The player should be able to build buildings, create units, gather resources and should uncover the whole map. No AI or multiplayer needed. Use simple but nice-looking graphics. No sound. Implement everything in HTML/CSS/JS, everything in a single file (you can use 3rd-party js or css libraries/frameworks via CDN).

hdjrudni• 13 days ago

I've been wanting to make an RTS but found it a bit daunting. I thought this might be a bit challenging for LLMs too but I guess not! This is nice to see.

muixoozie• 13 days ago

sort of looks like it was made with mobile in mind but I can't get it to work.

celltalk2• 13 days ago

I guess Plus accounts don't get access to Sol? Or is it because I am in Europe?

ihaveajob• 13 days ago

10h later and I'm still not getting it here in Spain, even with a Pro plan...

celltalk2• 13 days ago

I got the access after redownloading the codex app.

gorgmah8• 13 days ago

I have it in france, update all you apps etc.

HarHarVeryFunny8• 13 days ago

Not specific to OpenAI / Codex, but I'm curious what people are doing to protect themselves from any destructive actions by their coding agents? Just install and pray? Explicity approve all actions? Reconfigure for safety? Run in a sandbox (Docker) ?

ryan_n2• 13 days ago

I still just explicitly approve all actions and review all code (unless it's a personal/throwaway project no one else will ever touch/use/see). I know a lot of people that run in a sandbox though. That said, I'm sure there are lots of people that just yolo it and hope for the best.

kennykartman• 13 days ago

Typically I just want to isolate the agent disallowing it from accessing other parts of the filesystem. Using a different user might be enough, but I typically use [bubblewrap](https://github.com/containers/bubblewrap).

user439289• 13 days ago

I use the auto-reviewer for actions outside the builtin sandbox.

So far this has been rock solid, and tens of millions of developers use this setup without issue.

It is not going to wipe our hard disks. At least I hope so. Fable and GPT 5.6 have been ever more proactive, and GPT 5.6 is automating the AppStore on my machine to download an Xcode update while I am typing this.

HarHarVeryFunny8• 13 days ago

Is this auto-reviewer part of Codex? Is the review done by the agent or the model?

jrflo4• 13 days ago

What destructive actions are you afraid of in particular? Honestly the models are pretty smart, I let the agents go --yolo and nothing bad has ever happened (yet) that couldn't be solved with git.

HarHarVeryFunny8• 13 days ago

I'm not concerned about the code it's working on, but rather anything else - modifying files outside of the project dir (e.g. incorrect tool call), modifying system configuration, doing something bad on the internet, etc.

RhodesianHunter2• 13 days ago

Don't let it outside the sandbox. Don't let it have access to anything but dev environments. Continue using git.

Never had any issues.

HarHarVeryFunny8• 13 days ago

Which agent/sandbox are you referring to?

gorgmah8• 13 days ago

I live in fear lol.

More seriously, I was blindly trusting the auto-classifier from claude code (same as the middle option when you do `/permissions` in codex), and it actually allowed the agent to do pretty hardcore `rm` and `git push --force-with-lease` commands, which I would have expected to have to approve manually. Luckily no major issue from those yet.

The best option imo is the integrated cloud environments from claude code (not sure yet if there's a codex equivalent). It spawns a VM in the cloud where the agent runs, and you can open a PR from the app when it's done. Very smooth experience

HarHarVeryFunny8• 13 days ago

Interesting - I'd never heard of this Claude Code VM option.

Does it auto install all the dev/test tools it needs, maybe including things like web server & browser? Does your code live in the VM, or in some external repository? Is the lifetime of the VM the same as the agent, or does it persist until you remove it?

Where can I find documentation on this?

cyberpunk• 13 days ago

I run codex in a dedicated vm, I have a cronjob which resets it to clean installed state every week. Nothing too fancy just bhyve and debian, 8gb mem. It has root access there, can install stuff, no permissions to push to protected branches etc. It didn't take very long to setup, and I can sleep a bit better...

Culonavirus• 13 days ago

YOLO.

Btw for real tho, if you don't have the time or means to mess with full sandboxed environments, just working within a git repo and instructing on your agents.md project level that the agent should back up dirty files (local changes that were not yet committed) before changing them is enough and super fast and easy to set up. And by back up I just mean a simple instruction to back up to some temp location under random named, but rembered during one "turn" of agent thinking, subfolder ( .../temp/{random}/orginal/tree/file.xyz )

This is so the agent (or you later) can recover even locally changed files if it messes them up for whatever reason.

As for the rest you gotta watch what you're asking for, but generally speaking, these SOTA models are smart, none of them will just delete your stuff even with full access. I've been raw dogging multiple projects on my work machine with zero issues of this kind for months. I created codex_reader read only acccounts for my local databases and just add that to agents.md with a note its allowed to only use that and never had a problem.

pixelbro• 13 days ago

I literally have had a SOTA Codex agent delete a bunch of files just last month, but it took very specific circumstances. It was working within my game repo, in a branch, and it ran out of SSD. It had to free up some space to work, so it looked around and found 25GB of untracked files in the project, in a folder called Recordings. Might as well clean that up, it thinks. There goes all the raw Unity Recorder footage I'd ever recorded of my game, over many years of development.

So yeah, it won't go on a spree outside of its lane even with full access, but if you give it a box and tell it to go ham, it's on you to make sure you didn't leave precious unrecoverable assets in that box.

gverrilla• 13 days ago

If Fable is removed from my Anthropic sub, I'll have to change to OpenAI.

tekacs• 13 days ago

Unfortunately, I'm finding that in long-form agentic use, when I'm trying to use Sol, I keep tripping guardrails – moreso than even Fable, somehow.

I don't know exactly what part of my codebase is triggering it, so I'm going to have to keep poking, but apparently the guardrails are not that gentle despite the phrasing. :(

ramijames2• 13 days ago

Sounds like you are working on something naughty :)

rsanek• 13 days ago

Based on the Intelligence vs. Cost graph, not clear to me why anyone would use Terra? Luna looks quite interesting though, happy to see OpenAI still serving the more budget-oriented side of the market (seems like Anthropic and Google have lost interest there).

https://artificialanalysis.ai/articles/gpt-5-6-has-landed

pstorm• 13 days ago

Cost and intelligence aren't the only axes. Terra has better latency and output speed than Sol for example.

glaslong• 13 days ago

Luna@max is in a VERY interesting spot if their rankings are at all to be believed:

- Better than Opus4.8 in the coding agent index (doubt)

- Just below sonnet 5, even with glm5.2, in the overall intelligence index

- Cheaper than haiku4.5, glm5.2 and kimi2.6 on cost per intelligence task index

simianwords7• 13 days ago

GPT Terra is 50% cheaper than 5.5 while being more performant. So it’s like a straight up 50% reduction in cost!

That leads me to a question. Why wouldn’t they just default to terra in ChatGPT in the last few months? If they didn’t then they burnt money for no reason by giving a shittier model at a higher price

mnicky9• 13 days ago

"while being more performant"

..on some specific set of benchmarks ;)

698969• 13 days ago

50% reduction in cost charged to customers, inference cost may as well be the same, we don't know.

simianwords7• 12 days ago

Recent reports that OpenAI found optimisations would explain that these are legit

gorgmah8• 13 days ago

Anyone else noticed the "Extended: Fable 5 is included in your weekly limit through July 12 blablabla" disappeared from claude code? Did they panic-delete the july 12th deadline ?

atentaten• 13 days ago

Yes, I noticed this too!

ciefa3• 13 days ago

I still see in the menu to select the model in the GUI (Claude Desktop, claude.ai etc).

DetroitThrow2• 13 days ago

Looks like they reset everyone's Fable usage.

user439289• 13 days ago

They did. I wonder if Anthropic will also be removing the 50% limit.

My Fable weekly limit is at 15% used already, 5.6 Sol at 3% used. And this is with the Max 20x plan compared to Codex 5x.

I don't work on the same tasks to compare them objectively, but GPT 5.6 on xhigh seems much cheaper. Essentially unlimited usage.

5555watch• 13 days ago

So with this release do they kill the 5.5-Pro model with super long thinking and reasoning? 5.6-Sol-Ultra is not the equivalent, right?

dayone1• 13 days ago

does anyone on chatgpt business plan (not enterprise) not have access to the Sol models in codex? i have 5.6 for terra and luna but not sol

guybedo3• 13 days ago

we probably need to use gpt sol max to decide which gpt flavor and effort we need to use per task.

giorgioz• 13 days ago

On top of GPT 5.6 Sol they added a Tamagotchi / Clippy mascotte https://x.com/giorgio_zampa/status/2075319657997750495?s=20

throw03172019• 13 days ago

What in the world is that? Why.

reversefleckerl• 13 days ago

No, this Pets feature has been around for a while now.

prodmod• 13 days ago

Things I have been struggling with Fable over and GPT 5.5, were just solved handily by SOL in a real "thank you, next problem" kind of way. Overall, something that just works is way less wasteful for your usage than struggling back and forth for hours.

guybedo3• 13 days ago

it seems terra is pretty much useless, you either want luna max for everyday coding (cheaper and same perf as 5.5 high), or sol xhigh/max for demanding tasks

beaker52• 13 days ago

We Openly hate OpenAI because they’re not very Open but we secretly hope they win against not-open-at-all Anthropic.

dandaka• 13 days ago

Not at all, we love them all with Chinese labs. And wish them to continue competing and not winning. That is how we get best models, lower prices and better availability.

matheusmoreira13• 13 days ago

I openly hope the chinese labs distilling them into open weights win.

perching_aix• 13 days ago

Tried Xiaomi MiMo v2.5 via opencode today. Since Sonnet 5's release week, Sonnet 4.6 has been feeling like a vegetable, with Sonnet 5 itself being only a little better. MiMo on the other hand feels like Sonnet 4.6 did up until very recently. Absolutely impressive.

In some ways, more impressive than GPT 5.5 with high(!) thinking. GPT says quite some nonsense from time to time; didn't see any sign of this in MiMo so far, which is a pretty wild difference.

w4yai2• 13 days ago

Yup. I'm done with US companies. Let's go China !

cautiouscat• 13 days ago

I hope neither wins, and open models win.

deadbabe• 12 days ago

Open models will win, it is inevitable.

thin_carapace• 13 days ago

personally I hope any company involved with child slaughter ends up crashing and burning, i say this because both those companies are buddies with the us department of war (who helped annihilate a school the other day)

Computer0• 12 days ago

thank you for being a voice of reason. I am with you.

jatora7• 12 days ago

damn so brave

paxys8• 13 days ago

I'm just happy there's competition.

XCSme9• 13 days ago

GPT-5.6 is a really good model, and quite cheap. I can finally replace GPT-5.3-Codex for my Tool Calling in n8n.

Here's my benchmark results for GPT-5.6:

https://aibenchy.com/?q=gpt-5.6

(the high reasoning variants are still running, uploading them soon too)

EDIT: The high variants are there too, enjoy the hamsters[0].

[0] https://aibenchy.com/showcase/?q=gpt-5.6

lsllc• 13 days ago

Interesting that Sol (low) did better than Sol (medium) in your benchmark (and is barely more expensive than Terra). I too have been using 5.3 codex as a cheap-but-good model and are switching to Terra (xhigh).

XCSme9• 13 days ago

Yeah, for some reason the (low) versions do really well, like they think directly of the solution instead of going around all the edge-cases and getting lost in one of them.

XCSme9• 13 days ago

Also for most, there doesn't seem to be a big difference between (medium) and (high).

XCSme9• 13 days ago

Here's all 3 (medium), and GPT-5.5

It GPT-5.6 doesn't seem to be a lot smarter than 5.5, but it is faster, cheaper, more efficient and more consistent:

https://aibenchy.com/compare/openai-gpt-5-6-sol-medium/opena...

noname120• 13 days ago

Given that both Gemini 3.5 Flash (high) and Gemini 3 Flash Preview (medium) beat GPT-5.6 Sol (high) for correctness and score in your benchmarks I don’t trust them at all. The rest of the ranking also doesn’t make sense, like GPT-5.3-Codex (medium) performs better than Claude Opus 4.8 (medium) yeah sure

XCSme9• 13 days ago

It's because the benchmark is not coding-only.

Gemini models tend to have most knowledge for most domains, and are one of the most intelligent overall. You can check other benchmarks too, on specific categories, those models still beat other SOTA models.

Regarding Opus, Anthropic models often fail to follow instructions, formatting requirements or simply refuse to answer questions (i.e. Fable).

The issue with Gemini models is that they are not as good as using tools or go into weird failure modes when coding or trying to extract/generate specific data. They work amazing, until they don't...

XCSme9• 13 days ago

One example where the order seems correct, is this SVG generation test:

https://aibenchy.com/showcase/?q=Gemini+3.5%2Cgpt+5.6%2C+5.3...

You can see that most Gemini 3.5 generations are more correct than 5.6 Sol (the net is in the middle of the table, hamster seems reasonable and not deformed, etc.)

raketenkater• 13 days ago

5.6 sol ultra just nuked my branch and burned my 5h limit. nice work

yayamao• 13 days ago

good alternative, while gemini still no news

alberth2• 13 days ago

Maybe it’s a bug but on iOS individual paid Pro account - I can no longer see which model is being used nor select which model I want.

noobcoder2• 13 days ago

I hope it isnt like Opus eating so many tokens and taking so much time

Really wanna see it in DeepSWE benchmark

clutter55561• 13 days ago

I use both Claude and Codex, but mostly Claude for planning and coding, and Codex to review Claude’s work.

I follow a sort of waterfall workflow which is verbose but fully transparent.

Anthropic’s $100 subscription works fine for me, but whatever subscription my company has with OpenAI reaches the 5hr limit ridiculously quickly.

Sol-• 13 days ago

How do you couple them together efficiently? The nice thing about Codex or Claude is that the delegation or multi agent workflow capabilities are just built-in.

Do you link one with the other as a skill or mcp or so?

rubenflamshep• 13 days ago

When I was going through this it was because OpenAI had defaulted to /fast mode with 2x token usage

Lucasoato2• 13 days ago

This page couldn’t load
Reload to try again, or go back.

This on iOS, safari

stanmay• 13 days ago

sol is good

int3trap• 13 days ago

5.6 SOL is basically useless, even on fast mode. It takes so long to do anything that it would be faster to do yourself. And it burns usage so quickly it's genuinely not worth it.

delduca• 13 days ago

“Be scared”

ekzy• 13 days ago

Just my two cents. I'm on the Plus plan, I ask gpt-5.6 sol / high to analyze a vibe-coded codebase (~50k LoC) and write a plan to make it production ready. It wasn't a great prompt, I just wanted to test it quickly. It ran for ~15min and consumed 95% of my 5h quota (I thought it was gonna crash). The output is excellent but just a heads up that it consumes a lot of quota!

gorgmah8• 13 days ago

Yes had the same experience, Sol consumes limits quite fast

jatora7• 12 days ago

Anyone looking to use frontier SOTA on the $20 plans is going to have a bad time

desterothx3• 12 days ago

If you don't have an agent heavy workflow, you'd be surprised how far the 20$ subscription stretches. I used ~500$ of usage in the last month on a team 20$ plan.

RagnarD• 13 days ago

Annoyingly, the new ChatGPT app which folds in Codex, no longer recognizes Shift-Tab to toggle plan mode. Irritatingly you have to enter /plan. OpenAI, fix this!

isaachinman• 13 days ago

Noticed this as well. You have to go into keyboard shortcuts and set it manually.

robertwt7• 13 days ago

it seems like 5.6 SOL is better at almost everything than Mythos except Coding Benchmarks (except TerminalBench)? anyone knows why Mythos scores so high on SWEBench are they cheating or are they just optimised better for coding?

ls_stats• 13 days ago

The most impressive part is the token efficiency/cost per task of 5.6 Sol, it makes Opus 4.8 and Fable look extremely bad ($1.04 vs $1.80 vs $2.75)[0].

And 5.6 Luna ($0.21) is also impressive, cheaper than GLM 5.2 ($0.37) with higher intelligence.

[0] https://artificialanalysis.ai/#price-and-cost

mnicky9• 13 days ago

Well it's smaller model (something like 4T against 10T Fable). So it's faster and cheaper and with a lot of RL and maybe some favorable benchmark selection it can compete on these scores. In real tasks I expect it to have less intelligence, generalization ability, etc. than Fable.

djx222• 13 days ago

Not sure what everyone's experience is but I find 5.6 Sol to be a great liar. Reported success on a half done job and left things in a broken state after having quite a few back & forth followups on the initial prompt to clarify the plan. Didn't experience this with 5.5. Opus 4.7 and below sometimes did it but they fixed it in Opus 4.8. So, overall, the initial experience has made me think that this model will be a lot more stressful to work with just because the level of trust that it actually completes the task is now much much lower.

mnicky9• 13 days ago

May be related to this from METR evaluation:

GPT-5.6 Sol’s detected cheating rate was higher than any public model we have evaluated

djx222• 13 days ago

similar experience, yes. I cancelled my subscription.

ai_fry_ur_brain3• 13 days ago

Are you people seriously this dumb? Have you conwidered that all of these benchmarks are trained into these models. Can you stop sharing them as if they matter?

drsalt• 13 days ago

they update these shits too much.

mlmonkey2• 13 days ago

Where is Gemini in all this? Lately it's not even been in the running. Sir Demis asleep at the wheel? Or Google too scared to release a SOTA model?

Or ... maybe Gemini 4 is too good and the NSA is using it to break into systems worldwide ...?

w4yai2• 13 days ago

Google pretending they're still far ahead. In reality, far far behind. Google has become "just like another" company, nothing special. Few bright minds, with a lot of overpaid engineers.

r58lf• 13 days ago

The rumor is Gemini 3.5 pro will be released next week.

It had previously been announced (at Google I/O) to be released in June, but it got pushed back. Why? Rumors range from they are having trouble to they scrapped an old framework to pursue a new one and the new model will surpass Fable 5 and be cheaper.

sneezychl2• 13 days ago

I expect Google will drop a new SOTA model soon. Rumor has it they're training a new model from the ground-up, which takes a while.

winwang2• 13 days ago

I find it interesting that no one here has mentioned the increased (usable) context window 258k -> 353k. That's huge, but I wonder if it means we pay long context (2x) for the ones past 272k still.

joerawr2• 13 days ago

I really appreciate the focus on intelligence WITH token efficiency. I'd like to see that become the trend. Smartest per token metrics. Least tokens to accomplish the task above a certain success level. Most of my tasks would benefit from efficiency / token, but switching models constantly, and trying to guess the right model and effort level takes up too much of my processing.

tw1984• 13 days ago

I really appreciate the focus on intelligence WITH token efficiency

that is a polite way of saying "I don't believe AGI is coming anytime soon".

znnajdla• 13 days ago

Not sure why you would think a focus on efficiency means less performance. Compression is intelligence. Higher efficiency enables higher performance.

e1ghtSpace• 13 days ago

seems more like "this priorisies AGI"

What is AGI to you though?

inerte• 12 days ago

I honestly interpreted and agreed with the version "this saves money".

y1n02• 13 days ago

Anybody have an idea of what the flops per token generated is on a SOTA model like current GPT/OPUS? Is it basically the parameter count? So something like GLM-5.2 is, at a minimum, ~744 GFLOPs per token generated?

Am I way off base? Seems astronomical.

sidgarimella2• 13 days ago

I've found Sol's propensity for delegating to subagents can make it... disastrously expensive, especially with each subagent having some implicit floor on further reasoning/context gathering before action.

The base model is certainly cheaper and more token efficient etc, but on large tasks cost in some way is now n^2

winwang2• 13 days ago

How bad is it for you? Are you on ultra or xhigh/max? I typically ask it (5.5, now 5.6-sol) to use subagents for specific things anyway. On the Pro 20x plan, I'm seeing like ~1% usage per 20-30 min per session (on max effort), which is in line with 5.5. Currently trying out ultra on a personal project, feels like ~3x more expensive per unit time. (No idea on quality yet, for obvious reasons.)

sidgarimella2• 13 days ago

Max via Cursor, should've mentioned, very possible I'm seeing more Cursor than OAI. All the subagents it picked were also Sol Max... I've seen 7-10 in one turn. Regardless the top reasoning tiers being conflated with subagent count feels double edged

alasano• 13 days ago

My global CLAUDE.md/AGENTS.md etc have strict rules to never use subagents without approval or when specifically requested except for whitelisted scenarios.

I think that's the way to go most of the time

mafesio• 12 days ago

I have the codex x20 plan also. Set it to 5.6 sol ultra, gave it one task, in less than 10 mins I got the 10% warning. I did have it do a few things earlier, just some anaylsis and then create a pdf from it. I thought maybe that took a little longer than I though.

Used a reset, it went for about 11 minutes and then, just out of usage popped up, no warning, there were still 4 agents running, the nice thing is it did let them finish, each one went for about 10 minutes.

I also have a claude max plan, I have been using Fable 5 on ultra, I never hit the session limit, and get 3 or 4 full day's looping on ultra.

I don't know how it handles the subagents, but claude does it much more efficiently, Codex does seem much faster, so maybe it's just a relativity thing.

edg5000• 13 days ago

It scores high on BenchCAD, that's interesting to see, I was wondering about how each model could handle this. Seems like they trained it on programmatic CAD specifically.

andrijaskontra• 13 days ago

Trying to play those games has really bad impact on PC performance

jingw222• 13 days ago

nobody cares anymore

fmind-dev• 13 days ago

From my first tests today, it is a workhouse. It can scan my whole code base, optimize every part, with a greater level of autonomy than other tools. This is insane, we are living at the best time.

ai_fry_ur_brain3• 13 days ago

The literal worst time. I prefer meritocracies.

cognitiveinline2• 12 days ago

You think aristrocrats are using GPT and succeeding?

treovchinn• 13 days ago

average daily output tokens per active researcher were more than twice the highest level observed for GPT‑5.5.

thomas_witt• 13 days ago

I would be really interested in real life throughput. For an agentic chat situation, we are still on 5.4 - not because of the cost, but it's simply much faster than 5.5 with comparable results. Also we are using gpt-5.4-mini a lot for quick summaries, tldrs etc. In an ideal world we would upgrade 5.4 to 5.6 terra and 5.4 mini to 5.4 luna. But does somebody already have some measurements at least in terms of speed?

_bobm• 13 days ago

are people getting the `` sentinel'd reasoning summaries?

epolanski5• 13 days ago

I'm using luna (the smallest), at low thinking in my 9-to-5 job and I'm quite happy. No groundbreaking tasks so far, but typical small jira issues and fixes are done in a matter of low minutes. Very fast loops have their pros.

Fable or Opus would wander and wander.

shabgzer• 13 days ago

They talk a lot about speed in the article, but having tried out Sol today with Pi, 'medium' mode, one thing that stands out is that it's really ssslllloooowww.

It also defaults to 'low' mode for some reason. Can't tell if that's a step backwards compared to GPT-5.5 in medium mode so I'm sticking to medium.

Edit: just noticed it's spawning subagents in 'high' thinking mode.

zarzavat3• 13 days ago

This is also what I noticed, it's hella slow and the quality doesn't match the thinking time. Either it's just launch day load or else they went full GLM-5.2 thinkmaxxing.

paxys8• 12 days ago

I've been getting "this model is at capacity" a bunch with Sol, so definitely launch related.

imilev• 13 days ago

Cannot believe I needed a VPN to the US, to open this from Switzerland...

At least give me the article ffs.

wkjagt2• 12 days ago

I just watched the video on their launch page and I am really not sure how I feel about it. On one side, it's cool that these people get to start businesses and stuff using ChatGPT (assuming these are true stories), but how much of the business is really them? And how much does this business rely on a chat bot always being present as a kind of know it all employee? Maybe I'm just being naive or old fashioned (haven't really used AI much), but seeing these two people who started a cereal business for example talking to their laptop as if they're talking to a human advisor makes me feel, I don't know, I find it creepy.

By the way, this isn't about their 5.6 version in particular I guess, it's just the first time I've looked at one of their videos.

camillomiller5• 12 days ago

I would add to this that, to me and to many friends in their 30-40s, using AI models to achieve something we used our brains to achieve feels... empty? wrong? soulless? Sure, a lot of menial work can be relegated to the models, and it's ok, most of the time, but you finish a day of work with the inability to shake a precise new feeling: that you haven't really achieved something, even if you shipped more than on an average day in the past. It's frankly depressing, and it's even more depressing thinking that most people seem to absolutely disregard this feeling completely.

infecto• 12 days ago

Inversely I am building things I either never would have gotten to and a rate that would have taken infinitely longer. I get excited every day because instead of so much of my day spent writing the boiler plate I can spend most of the time around the architecture.

ed_elliott_asc• 12 days ago

I don’t get this feeling, I feel like I’ve achieved so much more than I have ever achieved, everything is polished and I’m happy with it.

I’m still developing, I’m just doing more than I ever did by directing Codex.

The way I see it is the same as I saw the leap from writing code in a text editor, to using an ide with intellisense, to using the jetbrains ide’s, to using mcp’s, to now directing AI - at all of those steps I wrote code, each step less and less but still it has the same output which is it is my work - even writing in a text editor I wrote less Java (until enterprise architects got involved :) ) than C++, and than assembly.

bearjaws• 12 days ago

I think this is where people start to consider you a "Luddite".

Is it bad that you used a computer and Google and lifted information from other people to accomplish a task?

My father is a machinist and has built has knowledge off the skills and documentation of thousands before him, is that empty?

You still have to do the actual work, and where do you draw the line on "shipping more". If a farmer now has an automated tractor, does that mean his work is now trivial?

spicyusername• 12 days ago

I can relate, but it's our turn of the wheel it seems.

It's a phenomenon that's happened basically nonstop since the Enlightenment. Yeaterday it was John Henry, today it's you.

Time to find a new hobby to bring intellectual satisfaction if typing "do my job" over and over in a text box isn't doing it.

gyosko• 12 days ago

I feel like this: "working" with AI is fucking depressing.

thearrow• 12 days ago

I also feel this, and it also troubles me. Unfortunately, we may be in the minority on this site.

What the other replies seem to overlook is that it fundamentally changes the nature of the work - it’s not the next step in the evolution after an IDE, it is closer to an automated tractor, and yes that does make the farmer’s work trivial. Pressing a button and having the field get plowed is a very different experience than manually plowing a field yourself. I can no longer in good conscience say “I plowed that field”, because all I did was press a button. The tractor plowed that field.

Most people on this site seem to feel comfortable claiming “I plowed that field” after they pressed the button that started the automated tractor. Okay, you had the idea to press the button - but you didn’t actually do the work, you delegated it. Same end result, but a different lived experience. Now would I rather actually plow a field by hand or simply press a button? You can probably guess - but the two actions do differ greatly in the experience they bring me, and the feelings of satisfaction.

snarfy• 12 days ago

My code was always plumbing. Glue stuff together. Connect data model to api.

I'm still using my brain, just doing a lot more plumbing now and reading a lot more code than writing. Depressing in some ways and exciting in others. At the end of the day it's not going way. It's disruptive and better to embrace it.

tiahura• 12 days ago

Those of us in our 50s have been waiting for this day since Eliza.

user439289• 12 days ago

No, I do not have an unshakeable feeling of not really having achieved anything at the end of the day.

Consequently I do not feel depressed or have to disregard any feelings.

I am busy working on my project. It is still hard to ship good software, even if the implementation is mostly getting done by itself.

andriy_koval3• 12 days ago

to me and to many friends in their 30-40s, using AI models to achieve something we used our brains to achieve feels... empty?

you have to start using AI to achieve something which was way more challenging before, then you will feel lots of fulfillment and inspiration.

douglee650• 12 days ago

Not manually cleansing data and building apps with AI to do the parts you can't or don't want to do is a massive lift.

I can do things that were far beyond my reach — suddenly. Almost all at once.

"Now you can discover you suck at marketing and business" :D

redanddead3• 12 days ago

You could say the exact same thing about human businesses.

How many ancient Roman businesses are around today?

pompomsheep• 12 days ago

Logged into the OpenAI platform this morning and had to double check they hadn't pivoted into a crypto company with these new names

matheusmoreira13• 12 days ago

Your subscription to Claude Max has been successfully canceled.

Switching next month. Looking forward to working with Sol.

pimeys2• 12 days ago

I've been testing Sol/Terra/Luna now since yesterday, running complex evals on all of them and I feel a bit... mixed on how they perform.

The eval is an agent that runs a set of tools and a prompt we can tune separately for different models. The OpenAI version of the prompt was specifically tuned based on their guide[0]. Then we let Opus to run another agent that acts as a user, trying to solve a problem (anonymized and taken from production). The problem is complex and we don't expect it to be solved by these agents, but we measure how the agents operate when faced with a vague problem:

- Opus 4.8 and GLM 5.2 both identified a constraint sooner and stopped so the user can fix an issue first that the agent cannot solve.

- Sol tried hard to solve the issue with different tools, burning tokens, until finally reached to the same conclusion with Opus and GLM. It was two times more expensive compared to Opus and six times more expensive to GLM for this task.

- Terra went even further and started calling tools that would not solve the issue, burning tokens and failing.

- Luna repeated the same failing tool call until it hit the round limit, and burned more money than Opus.

I'm kind of puzzled with the new GPT. Like, yes Sol is OK for programming, but I was expecting to get a cheap agentic model for non-programming tasks, one that can detect if things go awry and correct. Terra is too expensive and Luna not really fit for the task. Sonnet 5 is a bit better but more expensive than Opus 4.8, which is still the best in my evals. GLM 5.2 is extremely good if you can define the task and the tools clearly for it, and costs pennies!

[0] https://developers.openai.com/api/docs/guides/latest-model

MarvinYork• 12 days ago

I thought I was an OpenAI fanboy, but version 5.6 isn’t for me. Sol Ultra just keeps working and checking, and working and checking again, but it can’t even correct minor errors that aren’t a problem for 5.5 xhigh. I’ve rolled Codex back to 5.5 for now.

friendly_chap• 12 days ago

The problem is they nerfed 5.5 about a month ago. The change was immediately visible to me: context compacting started to happen about 3x as frequently.

I think 5.6 is still not even close to 5.5 xhigh pre-nerf.

enraged_camel5• 12 days ago

Yes, this is exactly why I said yesterday that OpenAI does benchmaxxing, seemingly quite a bit [1]. I got a flurry of downvotes for it at first, but I think people came around to it once they tried the model like you did.

Ultimately I think the issue is that OpenAI is under tremendous pressure to perform, but GPT-6 is not ready yet, so they had to push GPT-5 to its limits, and the only way they could do it was with really heavy RLHF, which has its shortcomings. Like, it is super obvious that Sol, Terra and Luna are all heavily biased towards working on a problem relentlessly because that's what their reward functions emphasized. That pushes up their scores in some benchmarks but does not translate to actual intelligence and capability.

[1]https://news.ycombinator.com/item?id=48849454

pimeys2• 12 days ago

For me the weirdest is Luna. It costs the same as GLM to solve a task with it, but it just calls the same failing tool over and over again until we cut it out.

Now if you look at where GLM stands, or even DeepSeek v4 Flash, things get really interesting for what they provide.

US labs completely miss a cheap model that can solve problems for 95% of the people. Gemini 3.5 Flash could've been it if it didn't burn so many tokens.

alberth2• 12 days ago

GPT-5.6 is the first model where I’ve actually frustrated to use it.

I’m explicitly telling it to do something extremely specific and it’s just not listening to me.

Eg, I gave it an image to update. The image is sized 400x200 pixels. It then generates a new image at 300x300. I explicitly state to be 400x200 in size and it won’t listen.

ddp26• 12 days ago

Is it possible GPT-5.6 is not a very aligned model?

emrehan• 12 days ago

I am looking to rent an apartment in a new residential tower. I have asked Fable and Sol to scrap the listings from various sources, deduplicate them and present them as a web application. Just using the cowork/(ex-)codex application interfaces.

Fable had issues with the sourcing and organizing images, and shoot itself at foot looking for shortcuts as usual. As I was getting it fix these back and forth, I copied my prompt and gave it to Sol.

Sol has surpassed my expectations by far. With a one shot simple prompt on a complex task, it gave me a working web app with everything I want with minor issues to track and fix.

patates• 12 days ago

devops monster! crazy how intelligently it debugs/solves any devops problem I could throw at it!

fomoz• 12 days ago

5.6 Sol High Fast is using more capacity than 5.5 High Fast, I hit the 5h limit for the first time.

Other than that, I think the difference between 5.5 and 5.6 will be the same as 5.4 and 5.5. 5.5 is just less frustrating to use, although not perfect and still has derp moments. But a lot less than 5.4.

So I expect 5.6 Sol to be smoother to use. But so far it just feels slower. We'll see.

gordonhart• 12 days ago

First impression of 5.6 Sol in Codex is fantastic — the model asks dozens of clarifying questions before starting to implement where other models (including 5.5 and Terra) just yolo it with assumptions that needed to be walked back later.

internet101010• 12 days ago

I have Fable send the specs/plans it comes up with to GPT for review and in 2/5 cases yesterday it found additional 1-2 bugs while in the process of reviewing.

GPT-5.6 didn't try to fix the bugs (as instructed) but it did surface them, which is something that didn't happen with GPT-5.5. When spec/plans approved Fable sends back to GPT-5.6 for ralph implementation and it seems to be an even faster, more reliable workhorse than it already was in GPT-5.5. Overall, impressed. Will continue to be a core piece of my workflow.

WarmWash2• 12 days ago

Still fails my internal test of counting legs on animals who have had extra legs photoshopped in. However if prompted to determine what is wrong with the image, it does get it right.

This kind of "out of bounds" image analysis seems to be a very difficult problem to solve, but totally necessary for transformers to really bring about massive change.

Dfol2• 12 days ago

It's working great for me.

I generally prefer OpenAI. I usually start projects with Codex; I love the plan we created. Then, after about 2 hours of working, back and forth, etc.I realize it's drifting HARD, or getting stuck on relatively simple things.

Once I get frustrated enough, I sometimes start over with Anthropic. Anthropic has been better (for me at least) to work with from start to finish.

I have the $200/month plan for each of them. (And I used to have the $250/month plan for Gemini... lol?)

Both Fable and Sol are good and definite improvements. I don't have a favorite yet. It's too early to tell.

The biggest difference I'm noticing is usage.

Anthropic is like a used car salesman. Not allowed to do a basic check on your own car (website), they'll scrape every penny possible out of you. Low limits, high api prices, trying to keep everything in their system.

OpenAI is like a cool but aloof dad. Go ahead and borrow his car, shoot, he'll even pay for your gas every once in a while. He'll answer your 5th question drunk, forgetting what you asked. But, at least he's a nice drinker that buys the group shots.

I have to watch my Fable usage, and I'm sure as hell not going to pay API prices. I don't have to watch/worry about my Sol usage even in Ultra.

But, 1 thing I'm noticing using Sol Ultra (on fast mode) is that it's slowing WAY down after a bit. I work the opposite of peak times so that's not it.

tekawade• 12 days ago

May I know if it’s for hobby projects or you run your own business/company where you use subscriptions.

Dfol2• 12 days ago

Both.

DefineOutside• 12 days ago

I've played around GPT 5.6 sol high at both work and home.

At work, it was able to one shot a dashboard. Of course, my prompts are vague as I'm not exactly sure what I want yet, but it did a better job than I could do as a backend dev forced to work on frontend sometimes.

Usage is also great, it just feels so much more efficient than older models in terms of thinking and time. Cost is barely better though.

It can burn a million tokens in less than a minute, at least at launch where there's likely less load on the servers.

At home, it feels like I'm fighting the AI less while letting it refactor code. I'm glad that I left this 12,000 line vibe coded port of a hand written codebase to future models to refactor. It feels like the model has better judgement than old models that would destroy your codebase so long as it meant accomplishing your prompt.

I'm almost disappointed that it's this good.

cmrdporcupine7• 12 days ago

After some time with it...

It has a tendency to do things without asking, a trait I'd associated more with the Claude Opus & Sonnet models than with Codex & GPT in the past. Specifically I've seen it go and update e.g. README.md files filling it with recenty-biased gibberish that means nothing to the user (e.g. very specific technical notes related to what it was currently working on) or staging and adding design/spec documents that were meant to just be working documents. In general it tends to behave more aggressively with git, if you let it get its hands on it. It has stronger "opinions" on that stuff, that don't always agree with me.

I'm going to have to update my prompts, I think. But I'm not used to this kind of thing in Codex, which in the past has been much more explicit and cautious, and one of the reasons I've preferred it over Claude.

It is very "smart." It also has a tendency to yak-shave things. Producing huge volumes of correctness and regression tests and nitting over e.g. very minor variances.

One thing that is "entertaining" is letting two separate instances review each other's code. They will endlessly find things to nit at.

hdemirev• 12 days ago

Have been testing Luna against other small models for production customer support uses cases, finding negligible performance impact when comparing against the substantial cost increase. Claims re: reduced token use also don't seem reproducible. Wrote a quick blog with some sample findings (marketing content but the findings are real): https://valiopt.com/blog/gpt-5-6-customer-support-cost-perfo...

arendtio• 12 days ago

I also like to take a look at https://cursor.com/cursorbench

While in the past months Composer 2.5 was a lot better than I had expected a year ago, and the GPT 5.6 family does a good job in terms of cost for performance, I wonder why nobody is talking about Grok 4.5 high? Those numbers look very convincing to me.

m0rde• 12 days ago

* Grok 4.5 has an advantage on CursorBench: an earlier snapshot of the Cursor codebase was unintentionally included in training. The exact score impact is unclear. That data has been removed for future models. For a rundown of third-party benchmark scores, see the Grok 4.5 launch blog.

I don't know about those numbers, even assuming this was by mistake :)

SoAp9035• 10 days ago

I use GPT 5.6 Sol medium as daily driver and the GPT 5.6 Sol XHigh is for planning. Also I really like the GPT 5.6 Luna Max it really goes hard too and cheap~.

childintime• 10 days ago

Dang, very few people share what kind of work they are actually do with the model, and/or the language they code in. That would make all the difference.

GPT-5.6

Related Stories