All the people here are focused on security and costs while I'm like "hey kicad on the announcement page!" Every clanker is an autorouter these days, eh.
GPT-6 Astra
261–270 of 1001 posts
Re: GPT-6 Astra
#262I want to take a step back: So, this is GPT-6 -- the natural number version release comparable to GPT-4 and GPT-5 from the past few years. The ARC-AGI-3 score is obviously impressive at 99.9% (we'll need to wait for more details on how they used the response API harness on GPT-6 Astra, wrt reasoning retention and compaction), but every other benchmarks seems to be a relatively modest improvement, comparable with any…
> If this is truly AGI (subject to one's definition of AGI still)
Scoring well in a benchmark that's called AGI does not make an LLM AGI.
Re: GPT-6 Astra
#263The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage they show for Opus 5 which would similarly be much higher.
Regardless, the result is still valid as the original benchmark harness is definitely unreasonably handicapped, and if a harness alone can help the LLM saturate the benchmark with a near perfect score then the combination of the two must still be effectively AGI in the sense of passing the most famous benchmark designed specifically to measure AGI progress, after multiple iterations of progressively making it harder.
I think it is fair to say that this is probably effectively AGI if the benchmarks are remotely accurate - even with Fable, I've been at the point personally where I am reasonably confident that there's essentially nothing that I am better than Fable at despite generally being substantively above average on human benchmarks. If Astra's this much better than Fable, I'm ready to call AGI here.
For the many people who resist the AGI label possibly ever being achieved, I'd be curious to hear takes on what would make you think Astra is yet to be AGI, and what would still need to be achieved for this to effectively be AGI from this point forward.
Re: GPT-6 Astra
#264GPT 6 Astra benchmarks https://cdn.thenewstack.io/media/2026/09/358eb84a-screenshot... Performance is significantly higher than Fable 5.1 Source: https://thenewstack.io/openai-gpt6-astra-benchmarks/
> Performance is significantly higher than Fable 5.1 That's not clear. Need to see independent benchmarks first.
AA benchmark: https://artificialanalysis.ai/articles/benchmarking-gpt-6-as...
TLDR: it's about the same intelligence level as Opus/Fable, but it's suppose to be 70% more token efficient than GPT 5.6 Sol. So it's currently the new leader for cost efficiency frontier.
Re: GPT-6 Astra
#265I want to take a step back: So, this is GPT-6 -- the natural number version release comparable to GPT-4 and GPT-5 from the past few years. The ARC-AGI-3 score is obviously impressive at 99.9% (we'll need to wait for more details on how they used the response API harness on GPT-6 Astra, wrt reasoning retention and compaction), but every other benchmarks seems to be a relatively modest improvement, comparable with any…
> If this is truly AGI (subject to one's definition of AGI still), then this is a very boring release of an AGI model.
Hot take: These models are never going to be 'AGI'. We're just going from a GPT4 ball that's 90% round to a GPT5 that's 99% round to a GPT6 that's 99.9% etc etc etc
I think that the harnesses and context management is really where the rubber meets the road, and the real gains are happening there.
Re: GPT-6 Astra
#266ARC AGI-3 saturated by Astra! https://arcprize.org/leaderboard
ARC has their own writeup on the result, which offers some nuance. https://arcprize.org/blog/astra tl;dr it's 62% when apples-to-apples to other models, which is still notable.
ARC's harness is just straight up broken. No serious harness removes reasoning context between each step. Not only does this significantly lower performance over all reasoning LLMs, but it also increase cost as you destroy the cache on every turn. Tossing the oldest entry when context fills up instead of using compaction is equally bad with the same issues.
Re: GPT-6 Astra
#267Maybe it is AGI and they didn't benchmax it or it is not and is worse then 5.6 sol, which if true would just be sad
Re: GPT-6 Astra
#268The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage…
It's "harnessmaxxing" all the way down. AI benchmark scene is exhibit A for Goodhart's law.
Re: GPT-6 Astra
#269This is wild: OpenAI is basically declaring that AGI is here. https://www.theverge.com/ai-artificial-intelligence/989601/o... “If we fast-forward a couple of years, and we look back and say, ‘When was it, really, that AGI was created?’ I think it’s going to be about this time, and I think it might be about this model,” OpenAI president Greg Brockman said during a Thursday press briefing. Later in the call, he added,…
Remember when the term "AGI" meant something? Pepperidge farm remembers
I think that if today's capabilities were explained to someone 10-20 years ago they would think this is definitely AGI, but they would also have expected much more disruptive changes to society as a result than what is happening. I figure that's because we have abstract intelligence without physical/grounded intelligence, and it turns out the former isn't general enough to implement the latter (remains to be seen if the word after that is "yet" or "ever"). So I think we do have AGI as conventionally understood, but our understanding needs recalibration.
Re: GPT-6 Astra
#270Anthropic should prep 5.2 and 5.3 at the same time, release 5.2, wait for Google to release their shit in a day or two later than then release 5.3 just to fuck with them :)