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Weren't there headlines just yesterday that they weren't releasing this due to safety concerns?
GPT-6.1 Astra is what those headlines referred to. This is GPT-6.1 Sol.
"no homerS -- we're allowed to have one"
https://amphetamem.es/meme?id=the-simpsons_06_12_71&text=We%...
That was 6.1 Astra. And I'm assuming it's being tabled because it still doesn't match Opus 5.5.
This is a decent win though, if it really is better. 6-sol was really no good, at least in my work.
6 Sol was worse than 5.6 Sol from my own experiences. Far worse.
Will see if this remedies things.
Yup, same experience here. I used it for one day, spent the next day fixing its lousy code, then went back to 5.6.
API price cuts were obvious once they made their announcement changing how usage is counted.
These moves all make sense when you take into account the enterprise market.
https://news.ycombinator.com/item?id=49889873
Shots fired, half the price of Opus 5.5.
Wasn't 6 released like last week? I can't keep up anymore.
Yes but it was underwhelming, so they seem to have rushed 6.1 Sol out. Also Opus 5.5 may have spooked them too.
Do you need to? Do you always keep up with all the version bumps on the software you use?
It was so underwhelming that it didn't even make it to chatgpt chat interface
Ominous for the industry and investors that token price is becoming the main battleground. Could be Anthropic's rationale for IPOing this year.
Great for the consumer.
I remember when bandwidth was super expensive and now it’s dirt cheap.
Not an AWS customer, I take it? :-)
China will do to llms what they did to german cars
Why make a new account to post this comment?
It's not even anything controversial..
They may work for one of the big AI labs.
I guess I'm out of touch. What did china do to german cars?
Another piece of evidence on the pile that the sudden panic and desire to "slow down" is because they're hitting the plateau on capability
Which, honestly, is fine. A lot of juice to squeeze in efficiency and even if models got zero more capable, making the capability that is already here cheaper is a huge win for everyone (except Nvidia)
What universe do you live in that you can look at the past six months and see anything like a plateau in capability?
This is brain-rotted zitron-conspiracy territory, utterly at odds with reality.
Have we honestly seen that great a leap in the last 6 months, or just better application of what we had 6 months before that.
We are seeing multiple frontier models dropping on the same day and no one bats an eye, because it's more of the same.
The difference between 6 months ago frontier and now frontier in 3d modelling, graphics and video editing is night and day.
Not that they've hit it but that they are approaching it. The time to panic and steer the narrative is before you hit the iceberg, not after
People have been saying this since GPT-4.
Most of the impressive accomplishments we’ve seen in the last few months have been the result of huge agent swarms working together and brute-forcing solutions, not massive leaps in intelligence from standalone models. That is still an improvement in the usefulness and power of the technology, but it is NOT evidence that model intelligence is increasing faster than before.
if true then LLM related AI (post-post AI winter AI?) is probably one of the fastest inception-to-plateau tech sectors to have ever existed.
We're still improving transistors on a somewhat routine basis.
The plateau doesn't have to be perfectly flat, but it's not a straight line upward anymore either (kind of like our work on transistors, where we've kind of hit the bounds of speed in clock cycles but are improving on miniaturization and power efficiency)
It took 6 years to solve ARC-AGI 1, 1 year to solve ARC-AGI 2 and 6 months to solve ARC-AGI 3.
Nvidia can start putting weights in silicon if model development slows down.
I think they are hitting compute restrictions. And buying compute right now can be 3-4X. And the costs are increasing. If they train a larger model and demand is high, that’s a lot of compute for Codex subscriptions, which is a loss leader for them. Especially Pro 20X which they just nerfed to 10X.
I think it's more a token-cost-demand plateau. They've reached the scale and investor trillions to which they can't 10x the hardware cost of inference any more. They can't afford to compete by eating costs and there isn't appetite for more expensive inference.
So in order that they don't bankrupt each other they're looking for the legal cartel behavior coordinating a stop to growth by convincing governments to regulate them into stopping.
There's a lot of juice to squeeze in efficiency but only so much whereas it seemed like capability was going to continue to scale with parameter count.
Maybe it's good news for everyone that model capability is now going to scale on semiconductor cost meaning huge players are going to be very motivated to make semiconductors cheap.
It's not so much that they're hitting a plateau in capability, as we're saturating long horizon benchmarks and it's not greatly improving general usability. On the other hand, newer models have been amazing for people interested in 3d, graphics, video editing, etc. The difference between Opus 5.5/Astra and earlier models is night and day even if for many coding tasks they're not a revolution.
I don't think that's the motivation, it's because both companies want to IPO and the _only_ way to even hope to be profitable is to do a whole lot less training, which costs a fortune. But unless Chinese labs go along with this gentleman's agreement (they won't), slowing down on training will bring about the inevitable Chinese model parity date more rapidly. At which point the game is well and truly over for OpenAI and Anthropic. Bit of a pickle they've gotten themselves into with the emphasis on being best, with premium prices to match.
This is literally the plan, open weight models are something like 60% of token spend, and it will get worse. many companies now have model gateways where you can slot in cheaper models via cli for cheaper. we've been using glm 5.x and it's pretty close to SOTA frontier models.
it's also why there have been so many calls for regulation and slowdowns.
Pretty standard business to identify and compete on every axis (cost, speed, intelligence, etc). Often, nobody will be able to maximize every axis so you end up with a polyhedron derived from the axes where there’s a niche for everyone.
DeepSeek understands that. Grok understands it. Every other AI company thinks they need to be the best at everything all the time and it’s weird.
If these models are so smart, can't _they_ select the right model for each task?
the right model for the task is the one that transfers the maximum amount of USD from your pocket to the provider's bank account.
No because then I'll go to the competition.
Why don't you simply ask the respective model which model is best for a specific task? :-)
Because it is more work?
Switching models is _very_ expensive in compute (you have to rerun everything from the beginning), and highly variable in cost. Cursor tried doing this for awhile, but inconsistent performance/usage means most users turned it off and pick models specifically.
I guess the question is, does the Dunning Krueger effect apply to models? The dumb ones might think they're up to the task.
These models have a knowledge cutoff that don't just prevent them from knowing about themselves (especially since most data about the model doesn't even exist until after the model is created), but they also don't know about other recent models. Sure, they can search and use other sources, even make some guesses based on the models they do know, but their default stance is more akin to "User asked about model X, model X doesn't exist, maybe it was an hallucination or mistake, let me do a web search...", but that assumes they have web search and are willing to spend tokens on it.
Personally I've taken to having a list of 3 to 4 models in default context with some ordering on which to prefer. Things like GPT 6 Luna is cheap very cheap, use it. Because otherwise the model will assume Haiku or such is the good cheap model to use.
The speed I'm having to update that document has not gone unnoticed.
What's driving the increase in release cadence here? We seem to get new models every week or so now, is this RSI?
No.
Wanting to have the newer model than the competitor, presumably.
The old "the bigger number is better", GPT announces model 6.1, the obvious thing to do next is to announce Gemini 27, and after that Claudé 3000, then a flute album.
Response to DeepSeek’s technical paper and competition.
What's that in summary?
Which paper are you referring to?
No, we're pacing ourselves to have the time to evaluate the impact each new model could have, obviously.
Chinese model pressure. Many of my SWE friends switched to Chinese models. I also use QWEN and GLM for many of the api requiring projects and dropped OpenAI and Anthropic. The only reason was the cost.
I can't recommend Chinese models enough. My personal favorite is DeepSeek v4.1 Flash but I have tried Qwen 3.8, Kimi 3 and GLM 5.3 which are equally impressive but DeepSeek is the cheapest and fastest regularly hitting 270 token per second.
And yeah I have worked with Anthropic and OpenAI models, they're good but they cost a fortune while Chinese models are already really good at a fraction of the cost.
Probably just the singularity, no big deal
Its a news cycle more than anything, and its ONLY going to get much, much worse. Daily releases, or multiple daily, 30-45, by EOY. Welcome to RSI!
Competition
What I don't understand is how much people have to say about every single one. Aren't we at the diminishing returns stage yet? Is there really that much to discuss?
If you look closely at various benchmarks, you'll see that often models will improve in certain areas while regressing in others. It suggests we're already at the point of diminishing returns.
I do wonder if people switch back and forth between primary models (GPTvsClaude) that it may be a better idea to simply keep releasing updates as soon as possible in order to keep users from bouncing back and forth.
Probably one of the factors. Signed up to openai pro a few days ago, deciding between openai and anthropic, then sonnet 5.5 was released and am wondering whether I made a mistake.
Luckily it's not a mistake as now we have access to . . . dots.
(and sol 6.1, it seems)
This is it.
It's because they need subscription money and interaction data and so keeping a version bump in the wings to stop the bleeding from your competitor's version bump is the logical thing to do. It has nothing to do with RSI.
Anthropic’s IPO?
New models are distill from the actual unrelease frontier models. They are just giving us better checkpoints.
The initial response to 6 Sol was bad, and Opus 5.5 was definitely winning the public vibes war. Makes sense to rush something out
They're releasing Sol 6.1 because 1. Astra 6.1 got postponed 2. Sol 6 is shitty 3. They have to release _something_ in response to Opus 5.5
Versions is marketing, snapshots/minor variations are easy and the number must go up. Release timing is another OAI's marketing tactic.
Recursive improvement doesn't imply increased rate, another word for it is "iterative" but this probably sounds too boring for some.
It is the only way to reduce prices while making it look like a good thing.
Productivity is increasing as the models get smarter; we are ascending the singularity. I'm serious.
Opus 5.5 is better than they anticipated, it's faster, smarter, cheaper. I'm about to change provider for claude and I'm not the only one
They're pacing the frontier
Aka "we made an oopsie last week and released what should have been called GPT 6 Terra with the name GPT 6 Sol"
It's relentless, isn't it?
Astra is a pretty impressive model. Excited to try this.
I love free market competition. We're getting insane advancements every day. I remember when llms used to cost an arm and a leg for decent intelligence
This is great. But maybe part of the motivation is that 6-Sol wasn't as good as initially advertised so they needed to tweak it. I felt a clear degradation in quality in some simple refactoring tasks vs 5.6-Sol.
Guys, are we slowing down yet?
I wish they'd list the environmental cost. My employer has an unlimited AI budget so I don't care about using Astra if it's just more profit for OpenAI. I care more if it actually uses 5x more energy.
I don't understand the point of this, why just now when it comes to llms. Why wasn't anyone enraged with the environmental costs of kids playing video games. I would not be surprised the environmental cost of that is an order of magnitude bigger than what llms have.
Considering Nvidia's hard shift to crypto and now AI, I doubt videogames are even in the same ballpark.
How many DCs are devoted solely to gaming?
Considering many games make use of cloud computing for online play and similar functions, they probably make up a pretty goot bit of global cloud compute capacity. Likely quite a lot less than the big AI players, but not an insignificant amount.
The energy costs of the cloud computing required for gaming are substantially less in power - not to mention overall demand - than LLMs. Come on, we're not in the same energy ballpark here.
Yes but it adds up when you consider that just on Steam alone there are 200 million monthly active users.
An entire planet. Just Steam alone has one or two hundres million monthly active users.
If you recall history past the last 5 minutes, you will remember that people have indeed been enraged with the environmental costs of things for a long time. Its just that AI seems to have induced a mass amnesia, and people tend to forget about what happened pre 2024.
Because people find video games fun, though I suppose there's some vocal people that think of them as bad for society. In contrast the AI companies are promising a torment nexus future.
I'd be curious as to how much of internet infrastructure is dedicated to gaming though.
Given that the number one cost of inference is memory and compute, and the incremental cost of each is energy, cost per inference is roughly proportional to energy consumption.
Did you care about this when it came to your other computing needs? What PC/laptop are ypu running and how efficient is that?
Look at Neuralwatt. They report energy usage with every call as well as aggregate statistics.
I want to energymaxx. Every home should have a nuclear generator for free limitless clean energy. Do not energysimp, we want prosperity for all we must energymaxx and invest heavily in solar/battery/nuclear.
A night of no sleep this one will be.
Okay, now price cut 6 Sol (and rename it to Terra again).
GPT-6 Sol released a week ago. Shortest model life ever?
Taking GPT-6 "Sol" outside behind the shed and giving it a merciful end is about the best outcome possible.
Huge misstep releasing it.
Bro, I'm a visual thinker
Sorry, I'm GenX. Growing up they showed us "Old Yeller" in the school gym every year like that was some kind of treat.
The misstep was naming it Sol - it was Terra-level all along.
I wonder if releasing this soon sort of validates the rumor that Sol 6 was just the Terra model they bumped up and slashed the price.
Then Opus 5.5 caught them off guard and now they're actually releasing the correct sized model.
If that were true, they’d have axed their margins.
Whether it was or wasn't, Terra's absence shows Sol has replaced it as the new middle model.
Looking at the token prices, if this is half as good as 6-Astra for 3D model creation in Blender, it's going to be an absolute game changer.
Opus 5.5 is definitely better at coding, but nothing even comes close to 6-Astra for work in 3D graphics...
How is it with animations?
I have played around a little bit with fixing some rigging problems and was impressed, but Opus even warned me it was bad at animations cause it can only really grab screenshots to process static content.
You need to use the Blender MCP. There is an official plugin for this now, so the third party one can be avoided.
I've only dabbled but yes with SOTA models it is very good at animating and really most Blender tasks you can think of. Certainly if you are coming at Blender at below expert level it makes it far more accessible and fun to work with.
There are still rough edges of course. But try the official MCP out with Astra and judge for yourself.
Have you tried fable? (I did small experiements and was satisfied, but maybe there are reasons to switch?)
From the results of a lot of YouTubers in the space, I think Opus 5.5 is pretty competitive with Astra in 3D. It's slightly worse at spatial detail but better at aesthetics and little touches.
This is the actual big announcement. 50% cheaper cache than GPT-6 Sol will get you far more mileage on Codex.
Exactly half as expensive as Opus 5.5 in every API pricing metric
And half as good. I didn't have great experiences with Anthropic models in the past, but Opus 5.5 seems to have turned a major corner. It is churning through tasks significantly more quickly and efficiently.
Suggest trying it out yourself: Ask for something difficult from GPT-6 Sol and Opus 5.5 and watch what each one does. The difference is stark.
I'm not an OpenAI simp, but how anyone can have any opinion on the performance of these models in less than a day - let alone a few hours - is beyond me.
Try it, it's that good compared to openai current offering.
I get better results and usage our of my $20 claude sub than my $100 openai sub... it's that ridiculous
The usage allowances are now insane, like they were when the Max plans were introduced. The $100 plan is usable again for real tasks.
Only takes 5-10 minutes to test your favorite one shot comparison prompt.
If 5-10 minutes is enough, you need a more ambitious one-shot goal.
Yeah totally agree, people keep jumping in w/ strong views hours after release, eg: https://news.ycombinator.com/item?id=49045430
For my personal experience, antropic model have better user experience except for 4.7 and 4.8 though. 4.7 and 4.8 feels like expensive downgrade of 4.6 to me (I didn't know why these two should even exist)
However it's less willing to obey your instruction so it's less usable for general runtine flows.
A pity I have to use claude code to try this, that I can't use the tools I know and love and have built around (opencode).
(I did use some CC for Fable when it came out, and it was... ok. Not the worst thing ever.)
Cache doesn't help you much when you are compacting every 5 minutes...
I was shocked at how quickly I ran out my $100/mo subscription with a single agent (sol medium).
cache is typically 10%, is this OAI setting a new level at half, 5%?
So yesterday we were consumed with how this was being delayed because of safety, yada yada.
Guess not?
Astra 6.1, this is Sol 6.1
That model was implied to be GPT 6.1 Astra, not Sol.
I see where you are coming from. But 6.1 Sol seems like a new frontier in pricing, not intelligence. I do think the deceleration stuff was mostly bluster, but I don't think this release in particular contradicts it too much.
I can blow through my weekly on astra in a few hours; hopefully this really is as good.
I get decent results telling it to use Luna subagents for implementing commits.
Cache is priced at $0.1/M, 50% as sol 6 and sonnet 5.5.
$2/10 is pretty cheap for a frontier model...
I stopped using LLMs. I shit you not. My life got better.
So when does Anthropic answer? Tomorrow?
You live in a ping-pong.
Why they are not even benchmark model against Anthropic or anybody ?
GPT 6.0 Sol was so terrible—I wonder if 6.1 Sol will be good?
Let's all boycott and move to Claude until they release 6.1 Astra. I don't like to be teased.
When is the alleged "safety" concern satisfied? Does this mean releasing new capability to consumers is going to get a lot slower? Lower price for 6 Astra capability via this 6.1 Sol is exciting, but that is because of Astra capability not merely the low price point.
When do we get the next jump in capability? When is 6.1 Astra released?
Isn't Anthropic doing the same, with Opus 5.5 being out while Fable/Mythos is still on 5.1?
Is this due to a similar safety concern or just because it's not ready yet for one (or more) of a myriad of possible reasons?
The coverage around 6.1 Astra seems deliberately playing into the dubious, recently headline "safety" narrative in a way that feels distinct. But you may be correct in which case, I would take the correction on board and maybe suggest a different alternative.
Although in theory if OpenAI was boycotted in this way the market pressure would force them to release. Then everyone moves back over there. Then Claude faces the same pressure. So even so, I think it could still work even if you have to trade off who you are boycotting from time to time.
Without more details on the credibility of the "safety" concern this seems like a totally coherent action for customers to take. We shouldn't put up with teasing.
It's just vibe versioning, right? Fable 5 is a beloved product, it gets a .1 bump to feel close. Opus 5 and Sonnet 5 had a mixed reception, they get a .5 bump to create a sense of distance.
The real announcement is the ultra fast mode ... Astra at 300t/s is insane!
I am afraid to ask for the price multiplier here. And it will burn your weekly allowance not in 1 day, but in 3 hours now? Or just one?
Where do you see this?
i'm watching the keynote
Still not available to me
didn't 6 sol just come out a couple weeks ago?
Other comments have already addressed this.
the race to the bottom on models is well underway. huge IPO's only really make sense for DC/HW lockups, and going vertical.
It is hard to trust these scores. GPP 6 Sol has been so bad for few days.
They need to fix Astra first. My main issue is with GPT in general is that unless steered it goes into building AI “sloppiness”/machinery that is not “needed”.
The good part is that this kind of behaviour also makes it good to find subtle bugs or debug issues that Fable/Claude just cannot get/fix even when you point it.
The GPT 6 release was ... horrible.
Sol 6 was so bad that I switched over to Opus 5.5 exclusively.
Huge regression compared to Sol 5.6, often doing really dumb things. Same for Luna.
Even Astra is very unreliable for coding. Sometimes it is great, but it also often does very stupid things.
I'm a bit sour on OpenAI right now and skeptical that 6.1 will be much different.
How does this jive with the exponential growth claims? Theoretically sol models are better than the 4 series models I was using at the beginning of the year, but in practice the results don’t seem to be much better. They always nerf the models over the course of the release so it _looks_ like the next version is better but I haven’t seen actual capability growth since ~January, and I’m pretty sure that was all tooling/harness improvements.
Eh. What? Is this common sentiment?
I mean Opus 5.5 is absolutely fantastic, unreasonably and unexpectedly so, but Astra was great and as far as I can tell SOTA until, when was it, 3 days ago, no?
(Sol 6 idk, have not used it much for coding really. Seemed to work just fine when Astra used it in Codex as subagents)
On r/codex the sentiment seems to be quite wide-spread.
DeepSeek and GLM made it impossible for "sota" to price any way they want.
GPT 6 Sol is obsolete after only one week! I am glad that they are not afraid to update the models more frequently. The Navier-Stokes thing revealed that it took them only a week or two to train a model more capable than Astra, and I want the pace of public releases to keep up with that.
I got a popup in my Codex just now saying "Try out 6.1 Sol!" and so I clicked the button to try it, and intriguingly, it set my model selector to "GPT-6 Astra Light" which makes me think 6.1 Sol may be in some way just a lighter/distilled version of Astra? defo interesting, not sure if I should read too much into it though. I see no option for directly selecting 6.1 Sol in my Codex Desktop UI.
Astra Light is the default option in the UI, so likely a bug
Came here only to check if the pelican spam has made it to the top again.
“OpenAI's new Pro 500 plan offers OpenAI's highest usage allowance and comes with access to its new "Ultrafast" feature — it also costs $500 per month.
At the same time, OpenAI is also making its existing $200 Pro plan less appealing. In Codex and Work, $200 Pro subscribers will see their included usage decrease from 20x of what the company offers to Plus users, down to 10x of that same allowance. In ChatGPT, meanwhile, GPT-6 Pro message caps will decrease from 200 to 100 per week.”
https://www.engadget.com/2272106/openai-adds-dollar500-pro-s...
Yikes
OpenAI is deeply unprofitable, particularly on those pro plans.
The only way is for prices to go up. Way up.
They released GPT 6 Sol literally 6 days ago. We've accelerated to a weekly model release cadence. That seems like...a big deal.
It's more like they released GPT 6 Sol too early because they were under pressure and now they are releasing the real version. You cannot do anything more than minor post-training in a week.
Implying they don't have like 3 or 4 "models" (different quants, post training, plain renaming) on the back burner at any point in time to do exactly that
Typically how long does codex take to update with the right model metadata for the release of a new model?
{"type":"item.completed","item":{"id":"item_0","type":"error","message":"Model metadata for `gpt-6.1-sol` not found. Defaulting to fallback metadata; this can degrade performance and cause issues."}}
OAI and Anthropic are locked in an unwindable race. Fighting over the same pool of users while cost is growing at geometric pace.
Impressive improvements, but GPT 6 Sol came out 7 days ago, and this one will behave differently. The panicked pace is becoming a liability, maybe they should have waited and released this as the 6.0 release
I guess they released this because GPT-6 Sol was underwhelming, they didn't even release it to ChatGPT. It was basically GPT-5.6 Terra for the price of Sol. However, who doesn't like price cuts? Astra for the fifth of the price? Wow, OpenAI have been quite generous recently, I still have not forgotten their 90% price cut with GPT-5.6 Luna, and now this? Astra was truly a milestone, and now they are offering similar "intelligence" for cheaper price. Incredible.
One thing I wish was better communicated is the mileage we get for our subscriptions. I do not fully understand how much usage I get with each model and their reasoning effort on 5h and weekly limit in Codex. I am asking because I know switching to Astra would consume my 5h usage limit quite rapidly, so I avoid it. If I knew how much mileage I would get from each model and respective reasoning effort, then I would be able to plan my workflow better and know when to upgrade model for a task. In almost all cases, GPT-6 Luna (XHigh) have been enough. That's why I appreciate its discount, because its dirt cheap, yet highly capable.
In other news:
It’ll be interesting to see what happens to the economics of this business if we hit a wall on peak intelligence but keep finding cool ways to lower prices.