Easily the most interesting part of this announcement is buried in the second to last paragraph:
"We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed. Access will initially be limited to select customers as we expand capacity."
750 tokens/s on a frontier model is going to be extremely interesting. I doubt this new version is anything but a version bump in terms of capabilities but if we can start getting these answers back faster, they end up being more useful.
Just off the top of my head, I can think of the tedious task of finding certain functionality within a codebase. I usually can't beat an AI agent harness at this task today. If the AI model is 3x faster I have less of chance.
Using gpt-5.4-mini in off-peak hours already feels like super-speed to me. That's probably no more than 100-150 tk/s. I can't imagine 750!
I've always eyed Cerebras but never had a use for it that would justify paying for the API directly. Although now that I think about it, trying out the API would probably cost less than a subscription for a month...
The ChatGPT subscription gives you access to the -spark model(s) in Codex which are blazing fast (but pretty dumb) which I think runs on Cerebras hardware too.
I have a pretty good use case for gpt-oss. The amount of time savings has actually been wild. Definitely worth a try. Just to be clear, it gets like 2000tok/s
Yep this is a glimpse into the future of 500+ t/s, which is in my opinion the next big thing that validates Jevon's paradox (the models are already smart enough)
“Smart enough” really depends on how many other people have encountered a problem close enough to yours and solved it somewhere on the open internet, IMO.
Most of the frontier models can, when prompted and tooled correctly, do a lot of “reasoning” tasks that amount to resolving how the user has explained a particular widely known paradigm.
The more difficult and obscure the issues you provide them with, the faster you notice them reward hacking by altering the criteria until they are no longer attempting to solve the problem. Using “advisor” style loops helps hold this off at the cost of tokens, but there is still a fairly short limit at which they will essentially give up if they can’t find all of the necessary information - sometimes the issue is actually worse if they find a small amount of information instead of nothing - they’ll extrapolate from that tiny piece of data and generate plausible-sounding hallucinations almost every time.
And god forbid your problem involves doing something a different way than the majority of people do it. Unless you can write a full spec on it, the models will repeatedly spiral back into adjusting everything about your problem until it matches one of the most popular approaches in their training data.
OpenAI also announced two days ago that they're starting to make Cerebras style chips themselves [0], will be interesting to see how fast SotA model inference will be by the end of the year.
I don't understand how you refer to this as "Cerebras-style". Cerebras is wafer-scale and unique. Jalapeno is an inference-optimized conventional chip.
Even if their chip is a difference maker, end of the year is wayy too optimistic. It’ll at minimum be a multi-year effort to bring it to production at scale.
I don't see any indications that OpenAI is doing wafer-scale work.
I tend to doubt they would. Cerebras notably doesn't have a kv, is wildly high bandwidth, but within/across the chip, not able to dump/restore kv super well. I doubt openai is going to build something that is as expensive to run. Also, wafer-scale is absurdly hard & weird to pull off, so I doubt that would be their first foray.
"we can start getting these answers back faster, they end up being more useful."
Dude, 10x token speed is going to be absolutely nuts. Half the "parallel subagent workflow" business seems to be driven simply as a means to avoid tapping your thumbs waiting for the infernal robot to finish something. If things come back speedy quick all the time, it should keep up with the "speed of the human" and let me stay focused on one thread instead of half a dozen. Plus the cost of screwing up gets significantly lower because you just re-fire with an adjusted prompt and iterate.
Someday these things will be 100x as fast as they are today and that is when things will get insane.
I hope this doesn't become the new norm where government becomes the bottleneck for innovation in the AI space.
It's worrying that with no formal and transparent policy framework that the government will be picking winners and losers and stifling innovation.
There's been no public policy, executive order, legislation, or otherwise on this, I wonder if anyone has filed FOIA requests for these decisions or the conversations between the Executive Branch and AI companies.
Indeed, I find quite ironic that some people in tech in the US complain about EU "regulations first" approach, but then their government seem to arbitrarily stop things from being released because, well, there is no established policy on safety guarantees or other similar aspects.
why don't you look into President Biden's October 2023 Executive Order on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (EO 14110) and what the plan was back then
On some level though we have to be cognizant of the potential for harm these models have.
LLMs are still a little loosey goosey, and we are right on the cusp (if not there already) for an agent to hack a bank and steal money for some rando teenager with a penchant for jail breaking.
The regulations are and will be negative, but don't lose sight of what LLMs can do off the leash.
Bank should be more secure, if a random person with an LLM can hack them, they should have paid 100 random blue teamers with LLMs to hack them first to get more secure. Not AI's fault.
It’s a bit in general, because if you actually read the EU AI legislation, most of it follows the right ideas and provides more safety, in the sense that OpenAI and Anthropic used to pretend to care about, but never really did.
They're not regulating though – they're arbitrarily blocking releases based on no clear criteria. The EU may be legalistic and rules-based, but I'd take that over capricious and arbitrary.
I agree. But that need has absolutely arisen. The US government is not exactly the best steward for this kind of thing, but some model other than "race each other as fast as we can" is desperately needed here.
Our AI czar, David Sacks, whined and moaned about the idea of regulation, even said Anthropic begging for some guidance was asking for “regulatory capture” and was gloating about how right he was they wanted it, 2 weeks ago.
No, it’s not leopards ate my face / irony / comeuppance, because that would involve regulation.
I understand it’s very satisfying if you wanted Anthropic “punished” for asking for real regulation to see this. I can’t deny there was a little bit of me at first that felt that way.
It’s untenable, a first order reaction, that I regret intellectually, because if you were against regulation, you’re certainly against waves whatever this is.
This applies to most things when it comes to the USG/citizens. Protectionism is communist unless they do it. Thinking about developing a nuke? Well bomb you first despite being the only people to ever use them. Free speech and press - unless we don’t like what you say.
The AI companies were all asking for the government to regulate them. The government is doing what the companies asked for them to do.
You can argue that, by government, they meant some legislative process, but I'd argue that regulation via bad executive order is much better than regulation via bad legislation because the former is tractable. I say this as an EO minimalist.
What are the proper laws and regulations? Can you point me to a proposed framework that you believe is most correct?
I have no idea how this stuff should be regulated. I do know that any sort of comprehensive legislation at this point in time has a much higher chance of being a bottleneck to innovation than an easily reversible white house directive.
Of all the terrible things to come from the odious Trump administration, them saying "hey, can we make sure these models aren't dangerous?" is one of the least bad things they've done.
Yeah pretty sure we had a whole bruhaha ~250 years ago about this question of where precisely power belonged. I for one think we mostly got it right then and would be reluctant to shift the power back to the individual sovereign and away from the people.
Ok so to be clear you agree this has not been the norm. It seemed like you were clarifying your original message but it was a change of topic, from "this has been the norm" to "this hasn't been the norm but they got what they were asking for" (or what they deserved if not exactly what they asked for). I'll dip out of that conversation.
You moved the goalposts. The government controlling what openai can and cannot do is completely different than they gating access out of their own volition.
My comment was in response to the parent's original comment: "Ok so you agree this has not been the norm," which didn't give me much to respond to. It has been edited since.
> The AI companies were all asking for the government to regulate them
pretty shallow take. they asked for sensible, transparent, tech aware regulations. this is not that.
I wonder what kind of scheme the administration is up to. The obvious play is a squeeze where OpenAI and Anthropic are forced to give parts of their company away, like Intel. But they could also be toying with the idea of limiting frontier AI access to companies that bend the knee, which would further cement their grasp on the tech industry.
It's worrying that with no formal and transparent policy framework that the government will be picking winners and losers and stifling innovation.
The market will demand such a framework. I suspect that's the larger idea here, in that Amodei not only wants to be in the room when that framework is written, he wants to be at the head of the table.
He apparently wants it so badly he's willing to set back his own company's IPO to make it happen, given that there can be no pure-play AI IPOs until the regulatory picture is sorted out.
I'm going to get downvoted here, but all the E/acc people that loudly allocated for Trump, someone known for amassing power by any means necessary including strong arming industry should be publicly eating crow right now. This was something that was always in the cards when you vote for someone who only cares about himself.
for america yeah. for the world the only real risks are american, chinese or corporate dominance. thats why its important to support open models wherever they come from and smaller players like mistral in france or black forest in germany.
Also applies to Chinese models. Give it 5 more months of US admin locking out US models and let's see what the market will look like for OoenAI and Anthropic IPO.
Their innovation relies on a huge amount of investment made under the assumption that they'll continue to be able to provide frontier models to a global audience. If it turns out the US government only lets them sell gimped models to non-citizens then they'll forfeit the whole global market to China and investors will flee like rats.
Unfortunately this is better than the status quo which is a totally unregulated disaster. These models are only getting more capable and cannot simply be released whenever OpenAI or Anthropic feel like the vibes are good enough. We don't let passengers fly on unvetted jumbo jets either and we prevent them from flying when they have problems.
Second of all, OP never even said anything about no regulation - they specifically said they wanted transparency which is 100% valid and better than a world where the government baby proofs everything for you
Models are already censored - and who they are or aren't uncensored for has a lot of implications which are way worse
And the jets is a terrible example - you picked one of THE highest regulated industries where NOBODY has a problem with regulation
> We don't let passengers fly on unvetted jumbo jets either and we prevent them from flying when they have problems.
This is Mr. Fart's Favorite Colors all over again. Our "vetting" process is not any more useful than the billion-dollar metal detector you can skip with a TSA Precheck. It arguably does not deter the most dangerous attacks even slightly. What happens when a mentally-ill pilot locks their copilot out of the cockpit? Well, we write off a crowd of passengers and then "vet" the next jet as a safe vehicle.
AI will be the same way. These "safety" measures are performative and do not even slightly address the actual threat surface of the technology. Arguably, it cannot even be done.
What knowledge or skills do you have to be hating on the certification process for airplanes?
It’s just getting ridiculous at this point. There are plenty of industries regulated and certified by national or international agencies. And no they don’t get to do what they want.
If you have no need for Anthropic/OpenAI's frontier model capability, you may be better served with an open-weight model that can't be taken away.
Edit:
> GPT-5 does the job.
I bring up DeepSeek V4 Flash a lot on HN, but I want to mention that according to Artificial Analysis, it trades blows with GPT-5 (high) (from August, 2025) [0]
For all intents and purposes you'll be able to move an open weight model wherever you want.
I really dislike this rhetoric, you sound like the FSF guys who are like "you're not free until you're running coreboot with zero binary blobs". Sure they have a point but also, most people are fine running regular linux.
good luck doing it to inference companies in singapore or the netherlands. or one of the decentralized networks that dont look useful right now. the world is already sick of america acting like it can do whatever and force their rules on the rest of us.
Still, with the same model being served by multiple providers, it is much less likely to disappear entirely, even if you would like to keep using a cloud provider. Worst-case scenario, you change providers. Or you use OpenRouter as a proxy.
It’s the same as the SaaS model. Price keeps going up, and to justify it they keep forcing you to upgrade to new versions with features that nobody asked for.
I've struggled with this. You definitely can have great cheap models. There are many of them open source and served profitably by neo-clouds. The big labs have basically given up on cheap models, and it is frustrating. It means applications are not likely to build as much on them anymore (we are shifting workloads from Haiku/Sonnet to Deepseek v4, for example).
I suspect the problem is that they need to charge a lot to keep revenue numbers up, and they are more worried about cannibalizing themselves than others cannibalizing them.
On Nano "it's not even close when you test it in real scenarios" - what have you seen? What kind of things can GPT-5 Mini handle that GPT-5.4 Nano cannot?
We’re using GPT-5-mini in an enterprise data-processing workflow, and we too see that GPT-5.4 nano performs materially worse for our requirements, roughly 30% worse as measured through our test suite.
Good observations. There's definitely a trend in pricing increasing but also balanced by innovations and availability of other models (both open and closed) emerging as alternatives. It's natural for the labs to explore how much they can push pricing, and for competitors to explore how they can treat that margin as their opportunity to grow their business.
Why do you think so? This game can be played forever, you just need strong marketing and orgs gullible enough to pay a higher price for a minor upgrade.
I don't see them capturing anything at this point. If inference was profitable then they could compete on price/model and capture the market. Then increase price and pay back the model training.
Feels like they are just pulling in as much as they can whilst competing on capabilities instead. At which point its a case of who can last the longest.
This is a constantly repeated conspiracy theory and is not true at all. The api costs do increase but aggregate costs per task decrease. The question is: do people need lower intelligence models at all? The answer is a resounding NO!
How many people do you see using haiku or sonnet? I see very few and most people default to the latest model and just play with thinking effort. I think three layers are good enough and supporting more is not a good UX.
No, you can't. These companies have two infrastructures: model training and model inference.
Inference needs to cache, it can't cache random model data, so it's essentially dedicated; it can't spin up models on demand, it has to know what demand is coming.
These companies are going to end up with very few models offered and that's probably generous. They might end up with just one model and you pay for removing it's safe guards.
The language used in this press release is borderline hilarious. It’s simultaneously trying to tell you how great it is while also telling it’s not THAT great. Nothing to worry about, move along.
Sol and 5.5 pro are in parity at $5 input / $30 output. What I'm inferring from this is that:
- model weight size didn't change, and this is mostly a result of better model architecture and scaled up RL
- better hardware utilization and and they're making better margins OR
- worse hardware utilization and they're okay with digging into their margins.
I think GPT writes code the best. How well will it write in version 5.6? It gives me chills.
Recently, I went head-to-head with GPT on nearly 2,000 lines of code, and GPT's solution was superior and faster. I even referenced multiple codebases on GitHub while trying, but they were incomparable to GPT.
So using GPT brings both fear and excitement.
The fear comes from realizing that this level of code is now the average for most people. The excitement comes from knowing that I can now study and learn at this level too.
I'm really looking forward to seeing how much more advanced the code will be with the upgrade to 5.6.
Yeah, Opus/GPT need multiple rounds of reviews from each other to get to clean auto review. Fable was like, it is done and indeed… crickets in bot comments. ‘No issues’ galore.
>> I am on the opposite camp. Open models are starting to perform better. GPT 5.5 keeps on messing things up.
I'm working in a 600k+ LoC codebase that has complex domain-specific logic and lots of moving parts. I find that Codex 5.5 is pretty good at surgical fixes, but does not go out of its way to explore and figure out what those surgical fixes might break. So I only use it to work on parts of the system that are pretty isolated from everything else so that risk of regression is small.
Tracking model performance on Artificial Analysis makes me think these models are constantly optimized/tuned in some way or another. GPT 5.5 was scoring in the mid 60's when it was first released, now it's almost 10 points higher.
Maybe I'll know once I try it? Honestly, for small functions or methods, I don't think there's a huge difference between models. But the larger the code gets, the more noticeable the difference seems to be.
Personally, I think this kind of coding experience varies from person to person
sadly with all the labs benchmaxxing I feel like you just have to try the model for a while to really evaluate how good it is, especially for each individual use case
-Why do you cut API boundaries this way?
-Why do you change the order of struct fields?
-Why do you deliberately insert padding?
Most of it depends on the background and context. Sometimes you add it, sometimes you don't. To understand this tacit knowledge, you need access to senior developers. But their attitude often depends on how promising the student is and what background they come from. On top of that, you don't have to rely on the respondent's mood, authority, or availability.
Programming is fundamentally a field that requires seniors. In my case, I had no such seniors at all. I learned to code by buying codebases from failed companies and studying them. My first job didn't hire me as an employee—they hired me as the CEO of a subcontracting company (because that was structurally more advantageous for the contract). So I wasn't given the patience to learn programming fundamentals gradually. I had to pay penalties if I failed. Most of the projects I worked on were the kind where failure meant bankruptcy for me. Naturally, there was no one to teach me.
Most of my knowledge comes from reverse-engineering the code I purchased.
People say LLM code contains falsehoods, but commercially sold code has always had falsehoods too. Honestly, if we're just talking ratios, LLM code has fewer falsehoods.
In that sense, I still think it's a matter of context. If LLM code is false, was human code ever really true? LLMs do lie. They generate plenty of incorrect code. But humans do the same thing. If a problem comes up, you just look it up then and there. For me, LLMs and humans aren't all that different.
When I searched for papers on using LLMs, I found that typically, you can have an LLM generate code and then ask it to find GitHub projects similar to that code. Then you can learn by looking at the pull requests and seeing how they structure things
In the old days, if I wanted to understand why memory offsets, padding techniques, or data layout structures were written a certain way, I had to stare at a senior programmer's code all day or wait for them to reply. But LLMs, while they do flatter me, explain things at a level I can actually understand. And LLMs don't get annoyed.
Are these models still relevant for people outside the US? I get the impression we're stuck on GPT 5.5 and Opus 4.8 pretty much permanently now, and relying on Chinese models in future.
Not only that, but using Opus 4.8 [1m] right now outside the US, and suddenly I only have a 500k context window. I really hope this is just a strange Claude Code bug, but I had access to a 1 Million window before, and it wouldn't entirely surprise me if context window length becomes another US export restriction.
The Anthropic page here seems to say that Max users should have access to the full 1 Million window for 4.8:
> Additionally, we’re introducing a new `ultra` mode that goes beyond the capabilities of a single agent by leveraging subagents to accelerate complex work.
I'm curious about how does this work? Do the subagents also get to use the same tools? Will the client be flooded with tool calls? Why extra pricing for a new "model" when the same thing can happen in the client with more controls?
And if it's an army of subagents, why do they compare it to Fable and Mythos? Those models with similar harness would probably bench better I'm guessing
If it's anything like ClaudeCode's ultracode, it's nothing new or revolutionary.
It's essentially a bunch of subagents being called by a deterministic script written by the main model thread, each eating tokens for lunch and output of which is synthesized by an orchestrator agent.
Yeah, I'm interested too. My guess for the reason, if not purely to eke out more performance, is so they can cleanly gather real-world data on this kind of usage.
Don’t all the major harnesses (pi, Claude code, codex) utilize sub agents? Def if you direct it to, but I’ve seen at least pi spin them up without explicit instruction.
Deep Research has been using the Orchestrator -> Subagents -> Synthesizer loop since the beginning. It's just strange that they'd put a loop benchmark next to actual model benchmarks.
Maybe it's a tune of the base model that works especially well with the subagent loop?
How can I become a trusted organization/partner? For my SaaS[0] where we generate 3D models using code it would be an absolute game changer to have such speedy generations. This would mean AI could do 10 iterations in the time it makes 1 now.
"We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed. Access will initially be limited to select customers as we expand capacity."
This seems like it would be the largest and first closed-source model Cerebras has offered till date
> We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed.
This is really exciting. I work on voice AI, and we're still using 4.1/4.1 mini since none of the frontier models come close on latency. I'm excited to be able to have more interactive experiences, I think it'll unlock new ways of working with these models.
> We don’t believe this kind of government access process should become the long-term default. It keeps the best tools from users, developers, enterprises, cyber defenders, and global partners who need them.
I'm very glad to see them say this explicitly and prominently.
Unfortunately we're not in a position where we can promise an exact date, but we expect it to take weeks (not days or months). It's the best coding model we've ever trained and we're bummed we can't release it to everyone yet. When we do launch, we'll share a lot more evals and testimonials and demos that help show what it's good/bad at. Personally hoping that both GPT-5.6 Sol and Fable 5 get broadly released soon so that everyone (myself included) can try them head to head.
You don't have to mention details, but is it internally a topic that your CEO hasn't even publicly criticized the Anthropic model freeze and are open ai folks seeing through the Musk/xai game that is in play here?
Agent Arena (Dynamic ranking of models on how well they orchestrate tools for real-world agentic tasks, based on signals like tool reliability, task completion, and steerability.)
Top 10, Highest rank to lowest
Claude Fable 5 (High), Claude Opus 4.8 (Thinking), GPT 5.5 (xHigh), Claude Opus 4.7 (Thinking), GPT 5.5 (High), Claude Opus 4.7, Claude Opus 4.6, GPT 5.5, GPT 5.4 (High), GLM 5.2 (Max)
Text Arena
View overall rankings across various AI models in text-to-text tasks across math, coding, creative writing, and other open-ended domains.
"We believe in broad access, and we plan to make GPT‑5.6 Sol, Terra, and Luna generally available in the coming weeks. As part of our ongoing engagement with the U.S. government, we previewed our plans and the models’ capabilities ahead of today’s launch. At their request, we are starting with a limited preview for a small group of trusted partners whose participation has been shared with the government, before releasing more broadly. During this preview, we will continue testing and coordinating closely with partners as we work toward broader availability. We don’t believe this kind of government access process should become the long-term default. It keeps the best tools from users, developers, enterprises, cyber defenders, and global partners who need them. We are taking this short-term step because we believe it is the strongest path to broader availability in the coming weeks, while we work with the Administration to develop the cyber Executive Order framework and a repeatable process for future model releases."
This amount of courting the current administration is pretty scary imo.
> This amount of courting the current administration is pretty scary imo.
That’s ironic – I interpreted that paragraph with the opposite slant: positively. If that’s what the government mandates then these companies, in the end, have little choice, so was at least relieved to see them publicly pushing back.
They absolutely do have a choice, Anthropic and OpenAI could fight it in court. Iran showed Trump is a coward, he wouldn't risk tanking the only industry still keeping the stock market growing.
It’s all speculation but I think he would have no qualms about tanking the only industry keeping the stock market growing. But given Kushner’s OAI investments, Trump stands to benefit personally from not tanking the industry.
That's hardly a speculation that he cares very much about the stock market, more than any of his predecessors. It's also why he takes a L instead of going into an adventure in Tehran. Last but not least, "it's the economy, ..." is on everyone's mind, including his
“Wouldn’t it be a shame if we export controlled all of your models and revoked the visas and green cards of all of your non US researchers. You should really reconsider challenging our orders in court. Also remember you have 16% public support and if the president endorsed it a national data center moratorium would pass with bipartisan majorities.”
"Cool, cool, hey, what percentage of economic growth is directly attributable to the growth of our companies again? And thanks for revoking our researchers' permits, enjoy them helping out China!
Also, oops, looks like our model weights got leaked on 4chan. How unfortunate."
I wonder what's going to happen when the administration rolls over to the OtherTeam(tm). If they've established a good relationship with Team A then Team B is automatically going to hate their guts.
seems pretty smart to me. opens doors and provides opportunities that those that don't court the government will miss out on. of course, if they're principled, that's okay (regardless of which admin it is), but the reality is most companies aren't. gotta get a leg up somehow.
Anthropic's fear-mongering and marketing is the reason we have these restrictions in the first place.
Despite their virtue signaling, Anthropic is the only major lab that has never released an open weights model, has been caught intentionally nerfing a model after release (Opus 4.6), intentionally and silently degrades performance for suspected competitors and AI researchers, complains incessantly about distillation when everyone is doing it (and after they settled for pirating books), and wants to pull the ladder out from everyone trying to catch up.
They're anti-consumer and only concerned with holding the power themselves.
I'm not a fan of Altman, but Anthropic is the worst actor in the space, and I hope they lose.
I mean it's fear-mongering until it isn't. I think people have become a bit too comfortable with dismissing the dangers of misaligned AI as simply "marketing hype".
Everyone in the space was talking about the automation of work from about day 2. People couldn’t stop themselves from talking about the way it was going to end work, and tech firms were firing people left right and center over AI.
Notably, Anthropic is the firm that stuck to its guns with the US Government, meaning they likely believe in their own spiel.
What about openai's fear mongering, or googles, or JP Morgans, or Frank Herbert's, or Arthur C. Clarke's or Samuel Butler's?
If you can't envision plausible scenarios where very bad things happen because of a malevolent actor, ChatGPT 6, and a little bad luck - you need to think harder.
I mean, it seems like common sense - a limited beta test before widespread rollout. I'm not convinced they'll ever come up with a good framework for dealing with the cyber & bio issues, but getting triggered by a beta test rollout seems overboard.
It is common sense, and with literally any other administration in the past century it would seem like a good idea.
I have zero confidence that this particular administration has any interest in regulating the industry for the good of the country, much less for the good of humanity. They will use regulation to maximize personal profit for themselves and their cronies, at the expense of the nation. I would not have thought that of any other US administration in the past 100 years.
In the longer run, it probably won't matter. If the level of corruption we see currently becomes the norm, then the US is facing much bigger problems than counter-productive industrial policy.
I do not like the fact that this forces people to remember on more hierarchy of "Sol vs Terra vs Luna". OpenAI was supposed to simplify their naming since at least 2025.
What I find amusing is that people where mocking EU for regulations and now this is happening in the US.
I know that Europe is behind in AI but still...
It does not introduce incompatibilities with earlier 5.x models? Frontier models are at a point now that there will never be a need for another major version bump, aside from those chasing marketing gimmicks. They are smart enough to adapt.
New request/response schema, new capabilities, or really anything that would break your existing workflows if you changed “5.5” to “5.6” in your application.
There have been many leaps forward in the past - tool calling, reasoning, agentic loops etc. 5.6 doesn’t have any of this. More intelligence doesn’t necessarily warrant a major version bump.
All of these LLMs are getting better at being at an LLM
But GPT-5.5 is as useful an LLM can be; it has solved lemmas I've thought about for a year, it can implement typed STLCs in Rust when I give it a formal grammar, it can help me analyze Postgres planner dumps.
It's great at tasks that have short solutions but
- they cannot learn based on a project
- their long term planning capabilities are worse than worms
- they are unconfident in decision making
- their internal representations are disgusting compared to JEPA
- they don't have any "system
clock" like humans and computers do
- LLM architecture is not modular like computer architecture or human brain architecture
There's so many issues with LLMs. I wish that companies can start working on the next generation of architectures before the bubble pops
Totally agree! They also conflate things all the time (a major type of hallucination) and IIUC that can’t be solved with the current architecture, just patched over
AFAIK there is no difference between "generation" and "version". Version naming/numbering depends on how good it turns out to be, and competition. If the competition releases something then you need to push something out too.
Calling it 5.6 creates the least possible expectations, and therefore more potential for positive feedback.
The Sol/Terra/Luna naming is interesting. I wonder what Anthropic are considering for their next models? "Terminator", "Armageddon"?
I think it makes more sense to make it so that major versions are different pretraining runs, and minor versions are simply the same pretraining run that was finetuned to different degrees. But it seems that that isn't cool anymore.
Musk steals Dario and they both train Epic on Mars. US Space Force promptly finds oil on Mars and launches an armada in the next window. In the meantime rocks painted black drop on Mar-a-Lago.
Anthropic broke with US Gov over wanting restrictions and n how they use their model. OpenAI was more than happy to bend over backwards and hide behind a misleading press release.
The idea that OpenAI is the one who are meaningfully pushing back against the USGov is risible.
The sooner the USG figures out a standard process for approving releases the better. There are many differing opinions on how much to regulate AI, but I think we can all agree ad-hoc policy sucks.
Haven't we established defensive and offensive security usage are intractably entangled? I.e. "patch all [security] bugs, make no mistakes" gives one a list of potential exploits to hand off to less capable models.
Doesn't that undermine all good-faith discourse on cybersecurity safeguards, controlled usage etc? Or is that overstating the case (I'm not a security researcher myself so kinda parroting).
At least they plan to give the public all versions. Feels infinitely better than whatever the hell is happening at Anthropic.
> "Yeah, we've got the absolute best model out there. Trust us. Truly scary."
> "O-ok? May I see it?"
> "Gtfo. Here's a worse version of it for you plebs."
> "Um, thanks?"
> "Lmao, actually no. The current admin fell for our scare marketing. Here, have this even worse crazy expensive token burner that gets more hardware limited every week."
You can say what you want about OpenAI, but their corporate strategy feels so much more solid.
I think that there are some OAI employees on Hackernews. I do believe that they should give access to ya, because after all it would allows us to generate pelicans :-D
What is the consensus on who becomes part of the said small group of trusted partners and if they weren't so opaque about it. I'd expect comparatively big names like Simon to be included within such but Alas its not reality.
I should clarify that I've had plenty of preview access in the past, but clearly this has got a little bit delicate over the past few weeks!
I also don't like writing about preview models that I'm not 100% sure are the same as the general release model, because I don't want to review something which turns out not to be the model everyone else gets to use.
He is not an ML researcher or engineer, he is a passionate AI enthusiast blogger. He mostly does SVGs and other low effort checks (sometimes with major flaws, as people have pointed out a few times in the HN comments).
Properly evaluating the model across all fronts requires a deep understanding of LLMs, how they work, the trade offs behind new architectures and the relevant research papers. It also takes a lot of time to build a proper evaluation framework so basically you can't just vibe code that if you want something that is solid.
Yeah, we'll share a lot more details and evals when we can release GPT-5.6 widely. We focused on cyber (and bio) here to help explain why it's being held back for now. We would have loved to launch it to everyone - it's the best coding model I've ever used - and we plan to do so as soon as we can ('coming weeks').
> As part of our ongoing engagement with the U.S. government, we previewed our plans and the models’ capabilities ahead of today’s launch. At their request, we are starting with a limited preview for a small group of trusted partners whose participation has been shared with the government, before releasing more broadly.
The clowns in the US administration can barely remain coherent from one sentence to the next.
Having them be the gatekeepers of technological progress in 2026 is fucking lame.
What happened to the nano/mini/standard/pro naming scheme, which worked perfectly fine and is intuitive to understand? Why does OpenAI insist on having the most inconsistent and confusing model and product names possible?
I'm going to pre-register my prediction that GPT-5.6 Sol is significantly behind Claude Fable 5, as evaluated by general consensus once time has passed for people to get familiar with both.
Claude will win on "vibes" and it'll be close in coding but considering how incremental Fable is above 5.5 in terms of overall smarts, there's no way 5.6 isn't considerably smarter on the whole.
Fable is allegedly a massive model (estimates between 6-10+ trillion, with a few hundred billion active). If 5.6 is just an incremental upgrade over 5.5 (at the same model size) then it won't be able to fully compete with Fable just yet.
"Affordable" depends on what you need. When a task is able to be achieved by two different calibers of model, it's obviously more cost effective to use the less capable model, in the same way that you wouldn't hire a math PhD to do simple addition.
If what you need is only possible with the more capable model then the "affordability" of the less capable model is sort of irrelevant. If what you need is a novel mathematical proof, it doesn't matter that a high school student is "more affodable". You need the math PhD.
As "old" models get more and more capable, it's going to be an increasingly important skill to be able to adequately recognize when a task requires a frontier model and when it doesn't, so that the less capable (and therefore cheaper) model can be used.
I’m countering this prediction by stating that Fable and Sol will be somewhat similar - this has always been the trend and I see no reason why this should stop now.
What a party pooper the current US government is... I'm not excited right now at all, while normally a new GPT release would be so much fun to test out.
Those taking issue with the clear deference to the current U.S. administration would seemingly prefer it be the exact same degree of preemptive compliance and collaboration, just done behind closed doors as it was with the Biden administration. The sausage is apparently far more palatable when you only find out about the overreach, pressuring, implied threats, and censorship years later in House Judiciary Committees. Or even better if you don’t through use of NSL gag orders or implied threat of lawfare!
1. Naming convention is copied from Anthropic and honestly is more catchy than a number (amongst normal people)
2. How in the world did Anthropic have to do all the theatrics about Mythos just to have OpenAI release an equivalent or stronger model a month later without any drama???
3. Cheaper models are just don’t fit any usecase imo and OpenAI knows it so they keep increasing the floor - I’m still convinced task per capability is reduced with each release
4. How in the world would open source models keep up with the multi layer security? Either this security is all theater or we will finally see a ceiling in open source models because by definition they can’t have those protections
5. Cybersecurity things are boring to me because it’s all zero sum cat and mouse games
Are GPT 5.5 and Opus 4.8 the last models we're going te be allowed to use in Europe? Is there going to be a cut, and we're only be allowed to use less capabale models outside of the US?
I mean, if they deem Fable 5 to powerful to share with the rest of the world, what's left for us?
Flagged activity can also trigger account-level review across relevant conversations and risk signals, consistent with our terms and policies around content retention and review. Looking beyond a single conversation helps our systems distinguish persistent malicious behavior from legitimate dual-use security work, where similar technical concepts may appear in very different contexts.
Fascinating!
Every conversation you have with these "more capable" models will be monitored and joined up and then your entire account might one day be tagged as Distiller or Cyber Threat Actor or whatnot. When combined with identity verification (which isn't discussed in this press release), expect people to be falsely flagged and banned from ever using OpenAI models again.
Wish I could find the thread from last week where discussions of exactly this kind of thing were dismissed as daft and outlandish.
> falsely flagged and banned from ever using GPT models again
That would be the best case scenario. More realistically a few wrong prompts is going to get you on a government list, and if you’re an immigrant some dark cell.
I didn't know that I was color blind, but thanks to those charts, I think I need to see a doctor...
I mean, you can read them even without the colors, but who on earth thought that those are a good set of colors? Oh, I forgot it was probably someone on 'Sol'.
> We don’t believe this kind of government access process should become the long-term default. It keeps the best tools from users, developers, enterprises, cyber defenders, and global partners who need them.
My brother in Christ, then why did you (and your competitors) spend years telling the government you needed them to tie your hands behind your back? Did you really think they'd just give you a crown that says "Gatekeeper Of All Neural Networks"?
In the past few years, that's been primarily Anthropic, right? A lot of the really regulation-oriented people at OpenAI went to Anthropic, particularly after the failed attempt to oust Sam Altman as CEO (that was in late 2023).
brother from another mother here: I don't think they were begging for overreach from the executive branch, likely would have preferred legislation, especially the kind that could be molded by lobbyists.
Note that GPT 5.5 currently is $5 input / $30 output (short context) so Sol is in the same class, while Terra if the benchmarks are as claimed is indeed a half-price GPT 5.5 at comparable performance.
With the $200/month plan I’ve never ran into any limits or issues. The product can be used every day for extensive sessions and development. What is everyone doing that makes them talk about tokens versus dollars?
From what my own experiences are, and what's on their checkout page, $100 is 5x base usage and $200 is 20x. If $100 was 10x, then I personally would drop down. They want people to go to the highest tier.
Can't buy cheaper as a selling point when Deepseek is basically free when hitting cache? Unsubsidized too, cloudflare and digital ocean can be the model provider for similar pricing.
"We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed. Access will initially be limited to select customers as we expand capacity."
750 tokens/s on a frontier model is going to be extremely interesting. I doubt this new version is anything but a version bump in terms of capabilities but if we can start getting these answers back faster, they end up being more useful.
Just off the top of my head, I can think of the tedious task of finding certain functionality within a codebase. I usually can't beat an AI agent harness at this task today. If the AI model is 3x faster I have less of chance.
750 tokens/s for their largest model is going to be nuts
I've always eyed Cerebras but never had a use for it that would justify paying for the API directly. Although now that I think about it, trying out the API would probably cost less than a subscription for a month...
Most of the frontier models can, when prompted and tooled correctly, do a lot of “reasoning” tasks that amount to resolving how the user has explained a particular widely known paradigm.
The more difficult and obscure the issues you provide them with, the faster you notice them reward hacking by altering the criteria until they are no longer attempting to solve the problem. Using “advisor” style loops helps hold this off at the cost of tokens, but there is still a fairly short limit at which they will essentially give up if they can’t find all of the necessary information - sometimes the issue is actually worse if they find a small amount of information instead of nothing - they’ll extrapolate from that tiny piece of data and generate plausible-sounding hallucinations almost every time.
And god forbid your problem involves doing something a different way than the majority of people do it. Unless you can write a full spec on it, the models will repeatedly spiral back into adjusting everything about your problem until it matches one of the most popular approaches in their training data.
[0]: https://openai.com/index/openai-broadcom-jalapeno-inference-...
Jalepeno is for mass scale inference.
Cerebras is extremely expensive and difficult to scale, hence the limited release.
I tend to doubt they would. Cerebras notably doesn't have a kv, is wildly high bandwidth, but within/across the chip, not able to dump/restore kv super well. I doubt openai is going to build something that is as expensive to run. Also, wafer-scale is absurdly hard & weird to pull off, so I doubt that would be their first foray.
Dude, 10x token speed is going to be absolutely nuts. Half the "parallel subagent workflow" business seems to be driven simply as a means to avoid tapping your thumbs waiting for the infernal robot to finish something. If things come back speedy quick all the time, it should keep up with the "speed of the human" and let me stay focused on one thread instead of half a dozen. Plus the cost of screwing up gets significantly lower because you just re-fire with an adjusted prompt and iterate.
Someday these things will be 100x as fast as they are today and that is when things will get insane.
It's worrying that with no formal and transparent policy framework that the government will be picking winners and losers and stifling innovation.
There's been no public policy, executive order, legislation, or otherwise on this, I wonder if anyone has filed FOIA requests for these decisions or the conversations between the Executive Branch and AI companies.
No amount of rules can stop people who are willing to break them. Only enforcement can.
It’s a perfectly good system for government regulation.
LLMs are still a little loosey goosey, and we are right on the cusp (if not there already) for an agent to hack a bank and steal money for some rando teenager with a penchant for jail breaking.
The regulations are and will be negative, but don't lose sight of what LLMs can do off the leash.
The appropriate level would be regulation though? Like I just don't get how we can argue that arbitrarily throttling companies is ok.
So here we are, it's probably going to me messy and err on the side of over-bearing.
I like the US approach better: regulate when the need for it arises, not before when you don’t know how the situation is going to evolve.
I agree. But that need has absolutely arisen. The US government is not exactly the best steward for this kind of thing, but some model other than "race each other as fast as we can" is desperately needed here.
I wonder if he understands why, now.
Anthropic was "begging" to make it harder for competing companies to be founded.
I understand it’s very satisfying if you wanted Anthropic “punished” for asking for real regulation to see this. I can’t deny there was a little bit of me at first that felt that way.
It’s untenable, a first order reaction, that I regret intellectually, because if you were against regulation, you’re certainly against waves whatever this is.
I would've much preferred if Dario hadn't run his mouth so much.
ppl are acting like limited release is unprecedented when, in fact, has been the norm until a few years ago.
You can argue that, by government, they meant some legislative process, but I'd argue that regulation via bad executive order is much better than regulation via bad legislation because the former is tractable. I say this as an EO minimalist.
I have no idea how this stuff should be regulated. I do know that any sort of comprehensive legislation at this point in time has a much higher chance of being a bottleneck to innovation than an easily reversible white house directive.
Of all the terrible things to come from the odious Trump administration, them saying "hey, can we make sure these models aren't dangerous?" is one of the least bad things they've done.
The Project is almost here.
The market will demand such a framework. I suspect that's the larger idea here, in that Amodei not only wants to be in the room when that framework is written, he wants to be at the head of the table.
He apparently wants it so badly he's willing to set back his own company's IPO to make it happen, given that there can be no pure-play AI IPOs until the regulatory picture is sorted out.
As predicted, [0] it has now been applied to OpenAI and soon anyone else releasing highly capable models.
[0] https://news.ycombinator.com/item?id=48511849
We must clutch our pearls and cite National Security as a reason to pick winners and losers, just like the government did for Fable.
This is not something to joke about, its real.
First of all, who said this is a disaster?
Second of all, OP never even said anything about no regulation - they specifically said they wanted transparency which is 100% valid and better than a world where the government baby proofs everything for you
Models are already censored - and who they are or aren't uncensored for has a lot of implications which are way worse
And the jets is a terrible example - you picked one of THE highest regulated industries where NOBODY has a problem with regulation
This is Mr. Fart's Favorite Colors all over again. Our "vetting" process is not any more useful than the billion-dollar metal detector you can skip with a TSA Precheck. It arguably does not deter the most dangerous attacks even slightly. What happens when a mentally-ill pilot locks their copilot out of the cockpit? Well, we write off a crowd of passengers and then "vet" the next jet as a safe vehicle.
AI will be the same way. These "safety" measures are performative and do not even slightly address the actual threat surface of the technology. Arguably, it cannot even be done.
It’s just getting ridiculous at this point. There are plenty of industries regulated and certified by national or international agencies. And no they don’t get to do what they want.
- GPT-5 mini costs $0.25/$2 and will be discontinued in December.
- GPT-5.4 mini costs $0.75/$4.5 and is supposed to be the replacement.
- GPT-5.4 nano costs $0.2/$1.25 and, while it ranks better in benchmarks than GPT-5 mini, it's not even close when you test it in real scenarios.
So you're left being forced to go to GPT 5.4 mini if you use 5 mini today.
The same thing is happening here as their “Luna“ model will cost $1/$6.
Can't we just stay with the models we actually want? I don't need GPT 5.4 mini. GPT-5 does the job.
Maybe it’s the realization that it was never that cheap in the first place and they're forcing us to upgrade in a slow and painful way.
Edit:
> GPT-5 does the job.
I bring up DeepSeek V4 Flash a lot on HN, but I want to mention that according to Artificial Analysis, it trades blows with GPT-5 (high) (from August, 2025) [0]
[0]: https://artificialanalysis.ai/models/comparisons/deepseek-v4...
I really dislike this rhetoric, you sound like the FSF guys who are like "you're not free until you're running coreboot with zero binary blobs". Sure they have a point but also, most people are fine running regular linux.
If you reread the comment with a fresh mind you'll notice that you misunderstood what he wrote
Fable itself is hosted on all major cloud providers. How many offer it today?
And if you are a legit American business you aren’t going to illegally bypass import/export controls.
I suspect the problem is that they need to charge a lot to keep revenue numbers up, and they are more worried about cannibalizing themselves than others cannibalizing them.
Eventually the pricing should be more stable.
Why do you think so? This game can be played forever, you just need strong marketing and orgs gullible enough to pay a higher price for a minor upgrade.
See Uber, Netflix, etc.
Feels like they are just pulling in as much as they can whilst competing on capabilities instead. At which point its a case of who can last the longest.
Doesn't feel like Uber/Netflix.
How many people do you see using haiku or sonnet? I see very few and most people default to the latest model and just play with thinking effort. I think three layers are good enough and supporting more is not a good UX.
For my use case a model from a year ago is good enough
will trigger re-evaluations of models by other labs + inference providers
Inference needs to cache, it can't cache random model data, so it's essentially dedicated; it can't spin up models on demand, it has to know what demand is coming.
These companies are going to end up with very few models offered and that's probably generous. They might end up with just one model and you pay for removing it's safe guards.
Recently, I went head-to-head with GPT on nearly 2,000 lines of code, and GPT's solution was superior and faster. I even referenced multiple codebases on GitHub while trying, but they were incomparable to GPT.
So using GPT brings both fear and excitement.
The fear comes from realizing that this level of code is now the average for most people. The excitement comes from knowing that I can now study and learn at this level too.
I'm really looking forward to seeing how much more advanced the code will be with the upgrade to 5.6.
On the contrary, pi + glm + DeepSeek… bliss.
Fable was a different kind of beast though. Rip.
For most important work (complex, cross-domain inquiries etc.), I still rely on Codex GPT 5.5 though.
I'm working in a 600k+ LoC codebase that has complex domain-specific logic and lots of moving parts. I find that Codex 5.5 is pretty good at surgical fixes, but does not go out of its way to explore and figure out what those surgical fixes might break. So I only use it to work on parts of the system that are pretty isolated from everything else so that risk of regression is small.
Seems odd that their announcement has zero coding benchmarks, with the closest related thing being terminal bench.
Personally, I think this kind of coding experience varies from person to person
Well, GPT referenced every GitHub code base, no wonder it won! :)
-Why do you cut API boundaries this way? -Why do you change the order of struct fields? -Why do you deliberately insert padding?
Most of it depends on the background and context. Sometimes you add it, sometimes you don't. To understand this tacit knowledge, you need access to senior developers. But their attitude often depends on how promising the student is and what background they come from. On top of that, you don't have to rely on the respondent's mood, authority, or availability.
Programming is fundamentally a field that requires seniors. In my case, I had no such seniors at all. I learned to code by buying codebases from failed companies and studying them. My first job didn't hire me as an employee—they hired me as the CEO of a subcontracting company (because that was structurally more advantageous for the contract). So I wasn't given the patience to learn programming fundamentals gradually. I had to pay penalties if I failed. Most of the projects I worked on were the kind where failure meant bankruptcy for me. Naturally, there was no one to teach me.
Most of my knowledge comes from reverse-engineering the code I purchased.
People say LLM code contains falsehoods, but commercially sold code has always had falsehoods too. Honestly, if we're just talking ratios, LLM code has fewer falsehoods.
In that sense, I still think it's a matter of context. If LLM code is false, was human code ever really true? LLMs do lie. They generate plenty of incorrect code. But humans do the same thing. If a problem comes up, you just look it up then and there. For me, LLMs and humans aren't all that different.
The Anthropic page here seems to say that Max users should have access to the full 1 Million window for 4.8:
https://support.claude.com/en/articles/8606394-how-large-is-...
I was already setting up my infra to experiment with GLM 5.2 and its 1 Million token window before this happened. I think I'm glad I did.
The excuse they give is borderline childish. I get the thing about slow rollout, make sure partners get to fix the bugs, etc...
But bad actors are hard working motivated entities with tens of thousand of fake ids, and american citizens working for them, for pennies.
All while the ones like or you sit at a crossfire which is borderline useless.
I cant wait to see what Qwen did with the massive distillation they made out of Opus 4.8 and Fable aka Mythos aka pretty sure they jailbroke it.
I'm curious about how does this work? Do the subagents also get to use the same tools? Will the client be flooded with tool calls? Why extra pricing for a new "model" when the same thing can happen in the client with more controls?
And if it's an army of subagents, why do they compare it to Fable and Mythos? Those models with similar harness would probably bench better I'm guessing
It's essentially a bunch of subagents being called by a deterministic script written by the main model thread, each eating tokens for lunch and output of which is synthesized by an orchestrator agent.
It's for sure a codex harness feature.
EDIT: yeah, it's the same thing. https://github.com/openai/codex/blob/main/codex-rs/core/test...
Maybe it's a tune of the base model that works especially well with the subagent loop?
[0]: GrandpaCAD.com
This seems like it would be the largest and first closed-source model Cerebras has offered till date
This is really exciting. I work on voice AI, and we're still using 4.1/4.1 mini since none of the frontier models come close on latency. I'm excited to be able to have more interactive experiences, I think it'll unlock new ways of working with these models.
Multiple weeks!
Not just 5 work days, but at least 10!
I'm very glad to see them say this explicitly and prominently.
(I work at OpenAI.)
Agent Arena (Dynamic ranking of models on how well they orchestrate tools for real-world agentic tasks, based on signals like tool reliability, task completion, and steerability.)
Top 10, Highest rank to lowest
Claude Fable 5 (High), Claude Opus 4.8 (Thinking), GPT 5.5 (xHigh), Claude Opus 4.7 (Thinking), GPT 5.5 (High), Claude Opus 4.7, Claude Opus 4.6, GPT 5.5, GPT 5.4 (High), GLM 5.2 (Max)
Text Arena View overall rankings across various AI models in text-to-text tasks across math, coding, creative writing, and other open-ended domains.
Top 10, Highest rank to lowest
claude-fable-5, claude-opus-4-6-thinking, claude-opus-4-7-thinking, claude-opus-4-6, claude-opus-4-7, muse-spark, gemini-3.1-pro-preview, gemini-3-pro, claude-opus-4-8-thinking, gpt-5.5-high
This amount of courting the current administration is pretty scary imo.
That’s ironic – I interpreted that paragraph with the opposite slant: positively. If that’s what the government mandates then these companies, in the end, have little choice, so was at least relieved to see them publicly pushing back.
They absolutely do have a choice, Anthropic and OpenAI could fight it in court. Iran showed Trump is a coward, he wouldn't risk tanking the only industry still keeping the stock market growing.
Also, oops, looks like our model weights got leaked on 4chan. How unfortunate."
https://www.nytimes.com/2026/06/04/podcasts/the-daily/trump-...
Despite their virtue signaling, Anthropic is the only major lab that has never released an open weights model, has been caught intentionally nerfing a model after release (Opus 4.6), intentionally and silently degrades performance for suspected competitors and AI researchers, complains incessantly about distillation when everyone is doing it (and after they settled for pirating books), and wants to pull the ladder out from everyone trying to catch up.
They're anti-consumer and only concerned with holding the power themselves. I'm not a fan of Altman, but Anthropic is the worst actor in the space, and I hope they lose.
https://news.ycombinator.com/item?id=48465269
I mean it's fear-mongering until it isn't. I think people have become a bit too comfortable with dismissing the dangers of misaligned AI as simply "marketing hype".
Everyone in the space was talking about the automation of work from about day 2. People couldn’t stop themselves from talking about the way it was going to end work, and tech firms were firing people left right and center over AI.
Notably, Anthropic is the firm that stuck to its guns with the US Government, meaning they likely believe in their own spiel.
If you can't envision plausible scenarios where very bad things happen because of a malevolent actor, ChatGPT 6, and a little bad luck - you need to think harder.
I mean, it seems like common sense - a limited beta test before widespread rollout. I'm not convinced they'll ever come up with a good framework for dealing with the cyber & bio issues, but getting triggered by a beta test rollout seems overboard.
I have zero confidence that this particular administration has any interest in regulating the industry for the good of the country, much less for the good of humanity. They will use regulation to maximize personal profit for themselves and their cronies, at the expense of the nation. I would not have thought that of any other US administration in the past 100 years.
In the longer run, it probably won't matter. If the level of corruption we see currently becomes the norm, then the US is facing much bigger problems than counter-productive industrial policy.
Who knows what they will fix, block or change in the model between the preview and GA time. Open models can't arrive soon enough.
If this is the new norm, we as workers should all start look for jobs in those companies.
There have been many leaps forward in the past - tool calling, reasoning, agentic loops etc. 5.6 doesn’t have any of this. More intelligence doesn’t necessarily warrant a major version bump.
So the next naming scheme might be FTX, Madoff and Enron? :^)
But GPT-5.5 is as useful an LLM can be; it has solved lemmas I've thought about for a year, it can implement typed STLCs in Rust when I give it a formal grammar, it can help me analyze Postgres planner dumps.
It's great at tasks that have short solutions but
- they cannot learn based on a project
- their long term planning capabilities are worse than worms
- they are unconfident in decision making
- their internal representations are disgusting compared to JEPA
- they don't have any "system clock" like humans and computers do
- LLM architecture is not modular like computer architecture or human brain architecture
There's so many issues with LLMs. I wish that companies can start working on the next generation of architectures before the bubble pops
If it was the next generation, why isn't it a major version change..?
Calling it 5.6 creates the least possible expectations, and therefore more potential for positive feedback.
The Sol/Terra/Luna naming is interesting. I wonder what Anthropic are considering for their next models? "Terminator", "Armageddon"?
Even Apple adopted and standardized on it for their latest platform releases.
Really glad to see some reasonably prominent pushback against this government overreach.
The information has been reporting that the government wants to individually approve which companies get access and when.
Imagine the wonderful opportunities for corruption and influence peddling, not to mention, excluding any companies that don’t support Trump
The idea that OpenAI is the one who are meaningfully pushing back against the USGov is risible.
I hope this means then fable will also get released again.
and dario's you naughty boy who you dont agree with politically.
Let 5.6 free, keep fable chained and anthropic instantly sees rev loss and has to cave.
Doesn't that undermine all good-faith discourse on cybersecurity safeguards, controlled usage etc? Or is that overstating the case (I'm not a security researcher myself so kinda parroting).
> "Yeah, we've got the absolute best model out there. Trust us. Truly scary."
> "O-ok? May I see it?"
> "Gtfo. Here's a worse version of it for you plebs."
> "Um, thanks?"
> "Lmao, actually no. The current admin fell for our scare marketing. Here, have this even worse crazy expensive token burner that gets more hardware limited every week."
You can say what you want about OpenAI, but their corporate strategy feels so much more solid.
What is the consensus on who becomes part of the said small group of trusted partners and if they weren't so opaque about it. I'd expect comparatively big names like Simon to be included within such but Alas its not reality.
I also don't like writing about preview models that I'm not 100% sure are the same as the general release model, because I don't want to review something which turns out not to be the model everyone else gets to use.
(I work at OpenAI.)
The clowns in the US administration can barely remain coherent from one sentence to the next.
Having them be the gatekeepers of technological progress in 2026 is fucking lame.
I'm looking at you Codex.
Is it just me, or does it seem like Anthropic has been more of a pioneer the past few years, and OpenAI tries to copy features they like?
Heck there's Fart coin, Harambe coin, Dog Wif Hat coin, you name it coin...
If what you need is only possible with the more capable model then the "affordability" of the less capable model is sort of irrelevant. If what you need is a novel mathematical proof, it doesn't matter that a high school student is "more affodable". You need the math PhD.
As "old" models get more and more capable, it's going to be an increasingly important skill to be able to adequately recognize when a task requires a frontier model and when it doesn't, so that the less capable (and therefore cheaper) model can be used.
These models aren't even that smart and they are already trying to control them and lock them down to a handful of people.
Then these executive and VC wonder why people hate AI and are against them.
Because the future is heading toward intelligence for the rich and you stuck with whatever model they want you to have.
The next step is banning open source models.
The future is not looking so bright if these models are already going locked down to whoever the government what's to have them.
This is no different than the government banning books because they don't want you to learn.
https://news.ycombinator.com/item?id=48678789
https://news.ycombinator.com/item?id=48683021
Anyone know the latest around Fable being re-released after gov smackdown?
1. Naming convention is copied from Anthropic and honestly is more catchy than a number (amongst normal people)
2. How in the world did Anthropic have to do all the theatrics about Mythos just to have OpenAI release an equivalent or stronger model a month later without any drama???
3. Cheaper models are just don’t fit any usecase imo and OpenAI knows it so they keep increasing the floor - I’m still convinced task per capability is reduced with each release
4. How in the world would open source models keep up with the multi layer security? Either this security is all theater or we will finally see a ceiling in open source models because by definition they can’t have those protections
5. Cybersecurity things are boring to me because it’s all zero sum cat and mouse games
I mean, if they deem Fable 5 to powerful to share with the rest of the world, what's left for us?
Every conversation you have with these "more capable" models will be monitored and joined up and then your entire account might one day be tagged as Distiller or Cyber Threat Actor or whatnot. When combined with identity verification (which isn't discussed in this press release), expect people to be falsely flagged and banned from ever using OpenAI models again.
Wish I could find the thread from last week where discussions of exactly this kind of thing were dismissed as daft and outlandish.
That would be the best case scenario. More realistically a few wrong prompts is going to get you on a government list, and if you’re an immigrant some dark cell.
I mean, you can read them even without the colors, but who on earth thought that those are a good set of colors? Oh, I forgot it was probably someone on 'Sol'.
My brother in Christ, then why did you (and your competitors) spend years telling the government you needed them to tie your hands behind your back? Did you really think they'd just give you a crown that says "Gatekeeper Of All Neural Networks"?
Sol Ultra ≈ Pro
Sol ≈ Standard
Terra ≈ Mini
Luna ≈ Nano
Beam me up Scotty. No intelligent life forms on this planet.
If you're asking what the average person can do, then the civic perogative is political action to help elect more AI-cognizant leaders.
> GPT‑5.6 is priced per 1M tokens across three model sizes:
> Sol is $5 input / $30 output;
> Terra is $2.50 input / $15 output
> Luna is $1 input / $6 output.
The OpenAI casino has never been more ready to take your money on gambling even more tokens.
Edit: yeah. https://claude.ai/share/06fefe02-4299-44da-8c5a-42607f54ca77