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GPT-6 Astra

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Re: GPT-6 Astra

#931

Post by fxd »

embedding-shape wrote: post #866
tappio wrote: post #857

I feel that for some time now, the biggest constraint when working with models is not their intelligence, but their speed. It does not matter how smart the model is, it will make mistakes, because the instructions are ambiguous and new facts are found during implementation. The biggest problem I've had working with software developers has always been the lag between seeing the results and steering towards the right d…

> It does not matter how smart the model is, it will make mistakes It does matter, otherwise why are we all using GPT 5.6 rather than GPT 3.5? Because it's way smarter, makes less mistakes and therefore finishes tasks faster. The smarter the model is, the faster it can complete what you actually wanted. > Regardless, working on the wrong things is time wasted Agreed. And "smart" for me, would mean understanding what…

[flagged]

Re: GPT-6 Astra

#932

Post by Iolaum »

mark_l_watson wrote: post #930

Please, I have a question: in September 2026, what is the price differential between buying GPT inference tokens vs. a $20/month subscription? I have moved to just using Google Gemini occasionally paying for tokens, no subscription, and it is OK, given my low level of use. I would like to add gpt-6 astra to my toolbox, but I probably would use it infrequently.

$20 per month should get you far enough if you use luna, it's a decent model. If you plan to try astra you need to try make it use as little context as possible to protect your usage limit - or bank a reset mid task to allow it to keep going.

If you use a decent part of a subscription - of any tier - you could be saving a lot of money. According to YT that could even be ~80-90% less than paying for tokens but take that with a grain of salt.

Re: GPT-6 Astra

#936

Post by MichaelMoser123 »

"""OpenAI called the model a "generational leap" for areas such as cybersecurity, professional work, software engineering, and science, with the company's president Greg Brockman saying that it could eventually be seen as the arrival of artificial general intelligence"""

https://en.wikipedia.org/wiki/GPT-6_Astra

according to Sam Altman from last year, an LLM should 'solve quantum gravity', if it is to count as AGI. Did anything change since then?

https://www.businessinsider.com/sam-altman-openai-david-deut...

Re: GPT-6 Astra

#937

Post by wrsh07 »

dannyw wrote: post #672
jumploops wrote: post #476

I think the thing I'm most excited about is the increase in _user prompting_. If I give a poorly constrained/ambiguous prompt, I don't want the model one-shotting assumptions left and right. The demos of Fable/GPT-6 are impressive, but "real AGI" should act more like a collaborator than either a peon or overachiever. It's a tough balance to get right, and although this has been possible to achieve with additional pro…

Anecdotal experiences from my external early testing of Astra: if you love Sol (like I do) and wished it was smarter at everything, but especially better at high-level tasks and discussions; I think you'll LOVE Astra. Astra retains the best parts and overall 'grounded collaborator and executor' of Sol in my testing (harness: codex CLI); while being a significant leap in capabilities & higher-level thinking. When you…

Off topic, but ooc what do you do such that you get early access to the models?

Re: GPT-6 Astra

#939

Post by EFLKumo »

It's said Astra is based on a newly pretrained model. Personally I hope it solves the problem that GPT speaks weirdly (which can also be spotted on Claude models after Opus 4.8 but GPT's is more severe) because IMO the way GPT couldn't get how to write good code (obviously it's trined to write code which pass benchmarks, but never code which sound good, with pursuit towards simplification and code aesthetic in mind) is extremely similar with how it couldn't get how to speak like a human.

However, it seems like OpenAI didn't pay much attention on these perspectives and I didn't find if Astra could write a more elegant code, or communicate more naturally, etc., which made me somehow a little disappointed.

They indeed mentioned the code Astra delivered is closer to production grade but production-grade code is different from what I want since there can be a kind of messy code blowing up your whole architecture design with control flows nobody truly understands but just passes all tests perfectly. There is no difficulty in maintaining this kind of code because you only need to paste the problems into Codex. And we all know this sounds incorrect. I don't know if my appetite towards a good code (no matter how) is sound but I just imagined frontier labs to give more attention on this.

Note: fwiw Fable 5.1's release page says it's better at these perspectives of coding and per my experience, yes it is.

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