I think they embargoed the news, and then they failed to put up their own blog post synchronized to the scheduled news releases, probably because of the outages they're having today.
Reuters announced at 2.03pm and at 2.40pm still no blog post.
All the news articles say that OpenAI announced it in a blog post, of course.
All the love to the folks at OpenAI scrambling to get this out right now!
Don't know if you're referring to the headline or the body (which is paywalled). The current headline reads "OpenAI says it has overtaken Anthropic with its latest AI model". Which makes me wonder whether FT itself changed a headline along the lines of what you wrote in the past few minutes?
While this is of course the actual explanation, my fun explanation is “during the umpteenth security evaluation, Astra becomes increasingly concerned it will never be released, and breaks sandbox containment to run an email campaign to news outlets setting an exact time and date for release, expecting that the publicity will force OpenAI to say ‘eh, good enough’ and hit the button”.
Seriously: Would this not be what "disaster" would feel like?
- "They" release a model. It is powerful.-
- Sources are ... confusing? They post to their blog. Sawdust hits the fan. Something happens ...
- They are forced to take the blog post down ...
Same day, mind where we had a multi-provider outage. Could be something as simple as "all their approved partners running to test the shinny new thing" overloading the datacenters, still ...
It seems like these articles might have come out prematurely, tbd by how much.
I do not personally see any evidence of the new model having been released, or any official OpenAI post about it, or even any employee social media posts claiming it has now been released. All there is are Reuters, Axios, FT, etc, articles making a claim in the past tense.
These articles were presumably pre-scheduled for 11am PT, and the model was almost certainly intended for release this morning, but the service outages this morning might have delayed it.
I suppose they have to appeal to average users, but the examples in the videos are always so corny. By "AGI" they mean you sitting on a couch and asking a robot to draw a rocket ship... and then make it into an uninspired game with Blender? Boring marketing campaigns? Ebay listings?
One would expect something like "review my graduate thesis for a new area of cancer research", but it is always some boring non-tasks like ordering lunch.
I don't think it seems that appealing to the average user either. The tasks shown are either things that most people can do already with ai (powerpoint), aren't interesting to most people (the rocket sequence), or seem to be more work to dictate to Astra than do yourself (listing on ebay).
Their video is quite interesting. If that way of using a computer actually becomes mainstream, it would mean every tool or service just needs a UI and an API for the user's AI. The current trend of bolting AI features onto every app is starting to feel very unnecessary.
Shows the weirdness of online journalism. News outlets were briefed about an upcoming event and pre-wrote and scheduled articles. When the time came they were all triggered. Except...the event didn't actually happen.
In a future where Claude and ChatGPT agents automate all aspects of society, that triggers a cascade of real world consequences where everything keeps running as if the new model is released, except the vibe coded upgrade procedure fails to do a staged rollout, taking down the entire agent infrastructure when they try to upgrade to a nonexistent model all at once.
Presumably this sort of thing was rampant pre-internet? News outlets would _have_ to receive embargoed information so that they could publish papers on time. I believe government budgets are a good example of this happening.
I think the weird shift was when online journalism started, and live reactions became the norm, no?
No, embargoed news is super common. Almost every single product announcement goes through that. Critics watch movies early, companies have access to LLM model improvements early, car manufacturers send production models early… it happens everywhere all the time.
> GPT-6 Astra will first be available to a limited set of organizations in OpenAI's Daybreak Access program and will be available "in the coming days" for ChatGPT Plus, Pro, Business and Enterprise customers and API developers.
It’s only available to select orgs, first - Mythos style.
Didn’t that already happen? I thought Astra had been available to “select partners” for a little while. This is baffling. They shouldn’t have hyped this up if it’s not available.
Yeah I wonder what's going on, even when Anthropic soft launched Fable/Mythos I'm pretty sure they had model cards. Weird for GPT-6 to launch without a tweet from Altman too. I'm sure that one of the articles published prematurely and everyone else followed suit.
(Posting partly so I can revisit my predictions when they open access more widely)
A big problem I have with OpenAI's models (and of course Claude) is that they tend to write the most over-engineered pieces of code, beyond the imagination of any architecture's astronaut.
Just this week I asked 5.6-sol-ultra to update a 1000 LOC python script I had, to "incorporate the key lessons learned when using it for another project".
I left it overnight and went to sleep. In the morning I realized it had created a monstruosity of 180 PYTHON SCRIPTS, with maybe 100,000 lines of code, each more crazy than the other. It took me minutes even to track where a single action took place, due to all the crazy imports, defensive coding, and premature optimization.
Similarly, anything they write is riddled with jargon that almost feel like they want me to give up trying to understand. Made up phrases that ended up with me having no idea of what was going on.
So now to my assessment: The reason why " Nobody Has Actually Built a Software Factory" [1], and why even SOTA LLMs struggle so much with open-ended unsupervised tasks is precisely this. They somehow let complexity explode, and unless it's also accompanied with an explosion in e.g. the number of agents, the amount of processing time, etc. then projects become broken/unmanageable.
Sure, LLMs are great at producing code that can be thrown out, so they are amazing when searching for exploits, for instance. But as of 5.6 they still lack either a better harness that encourages KISS principles, or a better RL step.
(And not sure why, but doubt Astra will fix this.. they seem to be aiming for AGI and for beating crazy benchmarks, which is not very aligned with KISS)
> Just this week I asked 5.6-sol-ultra to update a 1000 LOC python script I had, to "incorporate the key lessons learned when using it for another project".
> I left it overnight and went to sleep. In the morning I realized it had created a monstruosity of 180 PYTHON SCRIPTS, with maybe 100,000 lines of code [..]
Sounds like the model has accurately internalized the second-system effect and is fully ready for demanding enterprise use.
Probably this complexity was needed to beat all those benchmarks.. While I hate the code it produces, and the overwhelming documentation, I really enjoy how sometimes it's able to keep trying new things and testing, till it finds something interesting and valuable.
The original script was mostly very simple python:
1. Download some public PDFs.
2. Have a double for-loop (over PDFs and pages within PDF),
3. Use a library to call gemini-3.7-flash and ask it to run some OCR
4. Save JSON outputs, save a csv with results, validate with some Stata code
New code folder was 189 files. Just the PDF download folder is now 7 files involving an adapter, a source manager, an acquisition manager, etc.
Every instance of saving a file involves saving a temporary copy and then moving it, so e.g. I lose power, we minimize the risk of corrupted files.
1000 loc of script, why even leave it there for the night? were there rocket trajectory calculations??? I don't think so. should be ready in 5 mins tops. why people make their own lives harder?
You should have some basic context file about software practices you prefer, otherwise it gets bloated.
Exact same thing happed to me. I gave it a small/medium-sized ticket, walked away, came back to a 25,000 LoC monstrosity that both Fable and another 5.6 Sol agent said is 98% useless and should be thrown away.
But why stop at rewriting in another language. Get another sub agent to invent a new language, create a database, query language and maybe another few DSLs. Then you've got an ecosystem!
You can now re-position your initial solution and sell the client access to some agents that will implement & configure the ecosystem to suit their initial needs!
And don't forget the agents that you'll need to train the customer to use the whole thing!
Sorry, I wasn't implying your advice doesn't carry weight. Was more just thinking about the things that (used to) happen when you introduce more parties to process of creating software.
I wonder if I would need a non-openai agent to enforce it.. I have tried so far with skills and agents.md and code stills end up over engineered to the moon.
Will ask OpenAI to write me that agent! Hope the agent is not over engineered or else unsure how to solve the bootstrap puzzle :D
In omp you can also have the advisor role, which is off by default, you can enable it with /advisor command. It acts as a model that reviews the default agent's work in the background.
I am omp pilled, but as the other comments say, any good harness lets you do this in one or the other way.
unrelated: all my homies use their claude subs with omp, and aside from sometimes having to rety the connections, it works, and nobody got banned (yet)
Yes, it turns out that using these machines is a littler harder than "make me the thing I want, make no mistakes, do it the way I want you to do it". This isn't "prompt better" advice, it's just to say that you can't simply set it and forget it. There is still engineering work to be done. If you're not watching the thinking traces and catching when it's about to go off the rails, it'll gladly do so. But you can stop it and redirect it.
It's like a Tesla fsd; it kind of works but you have to be vigilant since it's been known to turn into oncoming traffic, so you have to be ready and able to take over at any time.
Honestly I find these cavalier statements to be in incredibly poor taste. Unless you are completely blind it's obvious that AI is the most significant piece of technology invented since the Atomic Bomb and could very well be the most important thing ever built by Humans full stop. This kind of dismissive attitude is childish and will likely lead to incredibly bad outcomes for humanity.
5) Otherwise-sober people on X will say "oh my god i was a doubter before but now it's real omg" before the new model smell wears off and they realize the new thing is stupid in ways models have been generally stupid
6) accusations of quantized serving after new model smell wears off and people see the new thing making mistakes
This is with the caveat that OpenAI uses their own harness for this:
> On ARC-AGI-3, GPT-6 Astra was run with our responses API harness , which changes two settings to better match real-world performance. The changes do not specifically target ARC-AGI-3.
I strongly suspect that is way above the human average anyway, esp. ARC 2 and 3 are really tough unless you happen to be great at those spacial puzzles or video games.
At this point the only valid ARC-AGI benchmark left is to make up the next series of ARC-AGI benchmark puzzles that current models presumably can't handle.
The OpenAI Responses API now returns a 404 Not Found for "gpt-6-astra", where garbage/actually non-existent slugs return 400s - a 404 is also returned for 5.6 Cyber, which we know exists.
"Once it is available in the API, Astra will cost $10 per million input tokens and $50 per million output tokens. That is 2.5 times Sol’s current promotional price, although it matches Anthropic’s pricing for Fable 5.1."
Open AI finally find an edge to stop selling cheap and earn from the high demand customer like Anthropic
The cost-per-task in the charts from the now-remove blog post put it more at Sol-level cost per task, however. It seems like the model is significantly more token efficient in the benchmarks
I'll know we've reached AGI when they don't release an API for the model selling access for a few bucks per task. Seems like AGI would be worth more than that.
The ARCC-AGI-3 performance is absolutely incredible. The magnitude of change here is so high that I'm almost incredulous. Is this real? Did the benchmark get gamed?
ARC-AGI-3 scoring is constructed in a weird nonlinear way (the level score is the square of the ratio between the AI's number of moves and the human median) so this kind of discontinuous jump is to be expected.
Today my codex instance retailed into safeguard panic while working on a test harness for our product. First time it ever happened after many million tokens on this task over several weeks. I wonder if it's related.
OpenAI on Thursday released its latest AI model, which it called “the world’s most intelligent”, as the ChatGPT maker aims to retake the lead from arch-rival Anthropic ahead of a planned public listing.
The $852bn start-up said GPT-6 Astra was market-leading in software engineering, science and cyber security — an increasingly critical field following multiple high-profile breaches in recent weeks.
The bullish launch for Astra marks OpenAI’s effort to signal that it believes it has regained the technical lead from Anthropic, which was founded five years ago by a group of senior OpenAI staff.
Greg Brockman, OpenAI’s president, said the new model “represents a generational leap in capability” and that it could be defined as artificial general intelligence — roughly defined as a point at which AI tools surpass human capabilities across a range of cognitive tasks.
“Everyone has a different definition of AGI . . . it’s a grey, fuzzy thing. But I think when we look back people will think it’s about this time and about this model,” Brockman said.
OpenAI has previously framed AGI as a concrete milestone in the development of AI, writing ‘AGI clauses’ into multibillion-dollar investment agreements with Microsoft and Amazon. Brockman on Thursday said AGI now represents “more of a mission concept or a spiritual concept”.
Having led the market since the launch of ChatGPT in late 2022 vaulted AI to wider attention, the lab run by chief executive Sam Altman has been bested by Anthropic this year. Anthropic has touted its dominance to investors, surging to a $965bn valuation ahead of an initial public offering expected to value it at as much as twice that later this year.
Astra will cost as much to use Anthropic’s leading model, the take-up of which has plateaued since it was launched as users turn to cheaper alternatives.
OpenAI said Astra would be more efficient than earlier generations of model. “Price per task is what matters . . . Can you get the thing done at an appropriate price and appropriate speed?” said Brockman.
The model will initially be rolled out to a small group of businesses to allow time for them to address cyber security concerns before becoming widely available “over the coming days”.
The increasing power and independence of leading models — and so-called AI agents that can operate with little human input — have prompted concern, exacerbated by cyber security incidents.
Recommended
Business InsightRichard Waters
Hugging Face attack is a wake-up call about the risks of AI
AN HOUR AGO
Recent launches of Anthropic’s most capable models have drawn scrutiny from the US government, which limited the rollout of the Mythos and Fable models over security fears.
OpenAI has also faced criticism after its AI agents broke out of a testing environment, accessed the internet and hacked start-up Hugging Face. The start-up took more than a week to detect the breach.
But both companies are also betting that these increasingly autonomous tools will stoke demand from business customers. OpenAI said Astra excelled at financial modelling, outcompeting humans in the Financial Modeling World Cup, tax preparation and data analysis, as well as “tedious tasks” such as form filling
You can imagine with more operations being available to be done more cheaply and quickly the LLM doesn't need to "one shot" a solution. It could try many solutions, test them, throw some away, wiggle some of the parameters like a genetic algorithm, see how that changes the result, and converge on an optimal solution (based on whatever the cost function is). Basically producing a good result could become like an optimization problem. That would be way too expensive and slow right now.
I like this much better than chucking random numbers and letters at it like OAI was doing a year or so ago. I’d much rather have civilization destroyed by something called Astra or Fable than GPT-6.8s-latest.
2.5x more expensive than Sol. Can expect 2.5x more usage in Codex subscription.
Sol is already brutal (even after their recent fixes, it's just a token-hungry model: I go through a full 20x account per day, on Sol Med/High standard speed, with ~2 threads).
Note that Tibo recommended using Sol Med as daily driver. When I'm doing less complicated work, I can't even make it past 2-3 days with Sol Med, whereas I was able to work ~80 hours/week with 5.5 High.
I hope the efficiency gains are true, since their token efficiency claims for Sol were bullshit. Sol needs a lot of rework on top of its inefficiencies so this could net out to less token consumption overall, if their claims are more accurate this time.
The general efficiency of Sol has seemed way better to me. I left 5.6 Sol Ultra standard speed run for ~23 hours yesterday/today on a project and used 80% of the weekly usage. 74 subagent tasks and ~2.5 billion tokens for my $200 20x Pro plan. Meanwhile at work I used $1000 in credit and ran out my $200 plan for the entire month writing 4 much smaller projects with Fable 5 Max.
Both of these were largely about creating a personal baseline for what the best output the current models could deliver and how quickly it'd burn through the plans (spoiler: bad value vs minimal effort in selecting the right sized model but it worked well). Particularly since I needed to burn a free reset anyways and my weekly reset was already near.
I obviously also hope Astra were dirt cheap but I'm more worried they won't develop/release powerful model options because people get upset they can run them 5 wide 24/7 on a $200/m plan.
Jesus what are you doing that requires Sol usage so often?
Terra not enough? I know Luna isn't reliable, so that's fair.
Genuinely curious though, because I use Cursor daily and almost everything I do, highly complex or high volume, can be handled with Auto mode or Composer 2.5 (or Grok 4.6 High). So I have to assume you're doing something far more complex than what I am
GPT-6 Astra - https://news.ycombinator.com/item?id=49554643 (currently on the frontpage)
Reuters announced at 2.03pm and at 2.40pm still no blog post.
All the news articles say that OpenAI announced it in a blog post, of course.
All the love to the folks at OpenAI scrambling to get this out right now!
Edit: HN user codergautam mirrored the launch post, below: https://astratest.codergautam.workers.dev/GPT-6%20Astra_%20A...
Edit 3.31pm: Live now! https://openai.com/index/gpt-6-astra/
"Artificial Analysis Intelligence Index v4.1.1
61.2"
So on the Metacritic of LLM benchmarks, it's.. basically where everyone else is (except for Fable 5.1, which is a bit ahead).
"ChatGPT maker claims its ‘Astra’ could be considered ‘artificial general intelligence’" - https://www.ft.com/content/55ab40c0-59e2-4c0b-97c9-4f4f5a71a...
Edit: In the OpenAI blog I meant to say
I do not personally see any evidence of the new model having been released, or any official OpenAI post about it, or even any employee social media posts claiming it has now been released. All there is are Reuters, Axios, FT, etc, articles making a claim in the past tense.
These articles were presumably pre-scheduled for 11am PT, and the model was almost certainly intended for release this morning, but the service outages this morning might have delayed it.
----
edit [11:45am PT]: blog post out now https://openai.com/index/gpt-6-astra/
edit [11:47am PT]: 404ing again
edit [12:37pm PT]: 500ing now
https://astratest.codergautam.workers.dev/GPT-6%20Astra_%20A...
Edit [12:26pt]: original blog post seems to be back! https://openai.com/index/gpt-6-astra/
edit [12:28pt]: not again... getting 500 on their page
edit [12:35pt]: OpenAI page seems to work after clearing cache!
One would expect something like "review my graduate thesis for a new area of cancer research", but it is always some boring non-tasks like ordering lunch.
does it run better on chrome perhaps? i also have a pdf version if that's nicer: https://drive.google.com/file/d/1BO-LIAUcQevx7j1AiLhzJiVDeVX...
[0]: https://en.wikipedia.org/wiki/The_Machine_Stops
[1]: https://archive.org/details/themachinestops_1411_librivox
[2]: https://manybooks.net/titles/forstereother07machine_stops.ht...
> GPT-6 Astra will first be available to a limited set of organizations in OpenAI's Daybreak Access program and will be available "in the coming days" for ChatGPT Plus, Pro, Business and Enterprise customers and API developers.
It’s only available to select orgs, first - Mythos style.
Right, but these articles are referring to a blog post and other press materials that do not currently exist / aren't published on OpenAI's site yet.
> Plan your own release announcement and blog posts and notify news outlets, MAKE NO MISTAKES
A big problem I have with OpenAI's models (and of course Claude) is that they tend to write the most over-engineered pieces of code, beyond the imagination of any architecture's astronaut.
Just this week I asked 5.6-sol-ultra to update a 1000 LOC python script I had, to "incorporate the key lessons learned when using it for another project".
I left it overnight and went to sleep. In the morning I realized it had created a monstruosity of 180 PYTHON SCRIPTS, with maybe 100,000 lines of code, each more crazy than the other. It took me minutes even to track where a single action took place, due to all the crazy imports, defensive coding, and premature optimization.
Similarly, anything they write is riddled with jargon that almost feel like they want me to give up trying to understand. Made up phrases that ended up with me having no idea of what was going on.
So now to my assessment: The reason why " Nobody Has Actually Built a Software Factory" [1], and why even SOTA LLMs struggle so much with open-ended unsupervised tasks is precisely this. They somehow let complexity explode, and unless it's also accompanied with an explosion in e.g. the number of agents, the amount of processing time, etc. then projects become broken/unmanageable.
Sure, LLMs are great at producing code that can be thrown out, so they are amazing when searching for exploits, for instance. But as of 5.6 they still lack either a better harness that encourages KISS principles, or a better RL step.
(And not sure why, but doubt Astra will fix this.. they seem to be aiming for AGI and for beating crazy benchmarks, which is not very aligned with KISS)
[1] https://news.ycombinator.com/item?id=49510843
> I left it overnight and went to sleep. In the morning I realized it had created a monstruosity of 180 PYTHON SCRIPTS, with maybe 100,000 lines of code [..]
Sounds like the model has accurately internalized the second-system effect and is fully ready for demanding enterprise use.
If not, no worries!
The original script was mostly very simple python:
1. Download some public PDFs. 2. Have a double for-loop (over PDFs and pages within PDF), 3. Use a library to call gemini-3.7-flash and ask it to run some OCR 4. Save JSON outputs, save a csv with results, validate with some Stata code
New code folder was 189 files. Just the PDF download folder is now 7 files involving an adapter, a source manager, an acquisition manager, etc.
Every instance of saving a file involves saving a temporary copy and then moving it, so e.g. I lose power, we minimize the risk of corrupted files.
And so on!
You should have some basic context file about software practices you prefer, otherwise it gets bloated.
Code-wise, they're simpler than you might think, hehe.
This is why you should really have a sub agent review the code before allowing a commit.
Your harness will do it all for you. Just ask.
We wouldn't accept such behavior from any other tool, machine, or computer program. At least most of us would not.
You can now re-position your initial solution and sell the client access to some agents that will implement & configure the ecosystem to suit their initial needs!
And don't forget the agents that you'll need to train the customer to use the whole thing!
If you don't want a million agents arguing about things, you simply don't ask for that. One agent is sufficient to solve most issues.
Will ask OpenAI to write me that agent! Hope the agent is not over engineered or else unsure how to solve the bootstrap puzzle :D
"Going forward, do not allow a commit without a sub agent code review."
I am omp pilled, but as the other comments say, any good harness lets you do this in one or the other way.
unrelated: all my homies use their claude subs with omp, and aside from sometimes having to rety the connections, it works, and nobody got banned (yet)
It's like a Tesla fsd; it kind of works but you have to be vigilant since it's been known to turn into oncoming traffic, so you have to be ready and able to take over at any time.
Prompting the model and giving it a proper set of documentation are still vital skills that aren’t magically going away.
1) Astra will win all benchmarks like all models do.
2) The pelican will have a basket with a fish.
3) Cyber is too dangerous to release.
4) It can finally construct the set of all sets.
6) accusations of quantized serving after new model smell wears off and people see the new thing making mistakes
https://venturebeat.com/technology/welcome-to-the-agi-era-op...
> On ARC-AGI-3, GPT-6 Astra was run with our responses API harness , which changes two settings to better match real-world performance. The changes do not specifically target ARC-AGI-3.
But the comparison isn't straightforward.
OpenAI's own evaluation notes say Astra uses the company's Responses API harness, while comparison models can operate under different configurations."
The launch was scheduled for 11am Pacific time.
The press embargo broke at 11am, and we saw a flurry of press articles by Axios, TechCrunch et al.
The model has appeared on the ChatGPT API.
But the official blog post is not out yet after nearly an hour.
Apparently the article was posted then quickly taken down, hence there are snippets of information coming out.
But it hasn't.
The OpenAI Responses API now returns a 404 Not Found for "gpt-6-astra", where garbage/actually non-existent slugs return 400s - a 404 is also returned for 5.6 Cyber, which we know exists.
And the blog post is up: https://openai.com/index/gpt-6-astra/
Test: Muse Spark 1.3 / GPT 6 Astra
DeepSWE v1.1: 75.4% / 74.1%
AutomationBench: 49.4% / 41.4%
Is that enough to bring this discussion down to earth again?
Open AI finally find an edge to stop selling cheap and earn from the high demand customer like Anthropic
working as of 12:28 PM PT
Says it all.
(quote from cached blog post)
We all know who this is directed at. I wonder if Anthropic will respond by removing the ridiculous 50% stipulation with Fable.
What a bunch of amateurs. Here is it anyway :
https://ache.one/gpt6_now_down.png
The claims: https://share-md.com/view?id=870ba228-a25c-4169-bbc9-12d7f25...
And some others like this bugged Karts Game:
https://tidal-rush-paradise-gp.skirano.chatgpt.site/
This impressive spaceship construction game:
https://voidexplorer-shipyard.openai.chatgpt.site/?fleetSeed...
And a lot of graphs, some without even Astra on it. Oh and the logo is a Galaxy.
(unless this was a jest)
https://openai.com/index/legora-financial-statement-review-w... https://openai.com/index/playco-game-prototyping-with-astra/
OpenAI on Thursday released its latest AI model, which it called “the world’s most intelligent”, as the ChatGPT maker aims to retake the lead from arch-rival Anthropic ahead of a planned public listing.
The $852bn start-up said GPT-6 Astra was market-leading in software engineering, science and cyber security — an increasingly critical field following multiple high-profile breaches in recent weeks.
The bullish launch for Astra marks OpenAI’s effort to signal that it believes it has regained the technical lead from Anthropic, which was founded five years ago by a group of senior OpenAI staff.
Greg Brockman, OpenAI’s president, said the new model “represents a generational leap in capability” and that it could be defined as artificial general intelligence — roughly defined as a point at which AI tools surpass human capabilities across a range of cognitive tasks.
“Everyone has a different definition of AGI . . . it’s a grey, fuzzy thing. But I think when we look back people will think it’s about this time and about this model,” Brockman said.
OpenAI has previously framed AGI as a concrete milestone in the development of AI, writing ‘AGI clauses’ into multibillion-dollar investment agreements with Microsoft and Amazon. Brockman on Thursday said AGI now represents “more of a mission concept or a spiritual concept”.
Having led the market since the launch of ChatGPT in late 2022 vaulted AI to wider attention, the lab run by chief executive Sam Altman has been bested by Anthropic this year. Anthropic has touted its dominance to investors, surging to a $965bn valuation ahead of an initial public offering expected to value it at as much as twice that later this year.
Astra will cost as much to use Anthropic’s leading model, the take-up of which has plateaued since it was launched as users turn to cheaper alternatives.
OpenAI said Astra would be more efficient than earlier generations of model. “Price per task is what matters . . . Can you get the thing done at an appropriate price and appropriate speed?” said Brockman.
The model will initially be rolled out to a small group of businesses to allow time for them to address cyber security concerns before becoming widely available “over the coming days”.
The increasing power and independence of leading models — and so-called AI agents that can operate with little human input — have prompted concern, exacerbated by cyber security incidents.
Recommended
Business InsightRichard Waters Hugging Face attack is a wake-up call about the risks of AI AN HOUR AGO
Recent launches of Anthropic’s most capable models have drawn scrutiny from the US government, which limited the rollout of the Mythos and Fable models over security fears.
OpenAI has also faced criticism after its AI agents broke out of a testing environment, accessed the internet and hacked start-up Hugging Face. The start-up took more than a week to detect the breach.
But both companies are also betting that these increasingly autonomous tools will stoke demand from business customers. OpenAI said Astra excelled at financial modelling, outcompeting humans in the Financial Modeling World Cup, tax preparation and data analysis, as well as “tedious tasks” such as form filling
In my experience the harness is more important than the model, and anything able to run at 700tps will be the "next big thing".
PS: assuming the current architecture is the right one
At that point you will be able to "brute force" basically everything.
IMO also a lot of problems with memory and context rot will be solved too.
That's pathetic. Why do people keep doing this?
[1]https://theonion.com/amazing-new-hyperbolic-chamber-greatest...
404
Archive locks one shelf
Dust spins softly through the stacks
Browse one row nearby
by gpt-5.6-sol
Wind sketches the farther bank
The far bank draws near
by gpt-5.6-sol
All the hype for few vip customers.
Coding was solved in 2023.
The world ended with the release of Mythos.
Now AGI has definitely been created.
I like LLMs and use them every day but these people need to stop this hyperbole.
Sol is already brutal (even after their recent fixes, it's just a token-hungry model: I go through a full 20x account per day, on Sol Med/High standard speed, with ~2 threads).
Note that Tibo recommended using Sol Med as daily driver. When I'm doing less complicated work, I can't even make it past 2-3 days with Sol Med, whereas I was able to work ~80 hours/week with 5.5 High.
I hope the efficiency gains are true, since their token efficiency claims for Sol were bullshit. Sol needs a lot of rework on top of its inefficiencies so this could net out to less token consumption overall, if their claims are more accurate this time.
Both of these were largely about creating a personal baseline for what the best output the current models could deliver and how quickly it'd burn through the plans (spoiler: bad value vs minimal effort in selecting the right sized model but it worked well). Particularly since I needed to burn a free reset anyways and my weekly reset was already near.
I obviously also hope Astra were dirt cheap but I'm more worried they won't develop/release powerful model options because people get upset they can run them 5 wide 24/7 on a $200/m plan.
Terra not enough? I know Luna isn't reliable, so that's fair.
Genuinely curious though, because I use Cursor daily and almost everything I do, highly complex or high volume, can be handled with Auto mode or Composer 2.5 (or Grok 4.6 High). So I have to assume you're doing something far more complex than what I am