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GPT-5.6

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Re: GPT-5.6

#831

Post by davedx »

hk__2 wrote: post #142
nilkn wrote: post #97

Earlier quoted context omitted.

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…

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.

A bit slower? I think for most of my tasks, Claude takes easily 2x longer for almost everything, even things like just analyzing code. It churns tons of tokens for quite simple things.

IMO that's exactly why it's a bit better at actual problem solving.

You absolutely do not "always have to correct" Codex. I'm not sure what you're doing, but I'd say 80-90% of its edits on my side it doesn't need any revisions.

Re: GPT-5.6

#832

Post by igravious »

steve_adams_86 wrote: post #650
inciampati wrote: post #118

Earlier quoted context omitted.

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.

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…

(subjective i know but) it's better than legitimately good

Re: GPT-5.6

#833

Post by davedx »

nilkn wrote: post #97
Syntaf wrote: post #6

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?

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…

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.

Re: GPT-5.6

#834

Post by muixoozie »

senko wrote: post #439

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 cod…

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

Re: GPT-5.6

#835

Post by killix »

nvarsj wrote: post #313
Syntaf wrote: post #6

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?

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.

[flagged]

Re: GPT-5.6

#836

Post by Razengan »

Jcampuzano2 wrote: post #152

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 confus…

> 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?

Re: GPT-5.6

#837

Post by Schlagbohrer »

XCSme wrote: post #601
10xDev wrote: post #234

Earlier quoted context omitted.

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.

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.

This shows up in OpenAI's graphs on their announcement page. There is a peak performance datapoint in the graphs past which (to the right on the graph indicating more resources spent) peformance declines. And it's on every graph on that page!

Re: GPT-5.6

#838

Post by Schlagbohrer »

andai wrote: post #802
10xDev wrote: post #234

Earlier quoted context omitted.

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.

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... "Fortun…

What do you mean bigger? Bigger functional context window?

Re: GPT-5.6

#839

Post by thomas_witt »

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?

Re: GPT-5.6

#840

Post by XCSme »

noname120 wrote: post #820
XCSme wrote: post #597

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

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

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...

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