The fact that AI models can be so easily distilled and replicated is such a stroke of luck.
10 or 15 years ago if one had asked me to envision a future where a private company invents artificial intelligence, I'd have thought for sure they'd have a massive moat, be very difficult to catch, and it would create an almost instant monopoly.
Rather, it seems that selling intelligence might end up as a race to the bottom.
Who woulda thought that just having access to enough textual inputs and outputs and a vaugely similar transformer architecture would be enough to copy-cat rather useful intelligence.
Even before LLMs, ML folks were already aware that you can use a model to teach another model. I doubt this is something AI companies put at the top of their investor materials, but it's been nice to see it play out.
That said, there are other moat factors like, a US company needing to use a US AI provider, sticky customers due to corporate onboarding friction, and others. Not nothing, but not as large a moat as some imagined.
Yes, but 10 or 15 years ago, I would have thought that there'd be more to it than just a slight modification on the ideas behind a CNN to get this level of AI.
It reminds me of the seo antics out there. The search results page is the engine, much like how distilling is the "intelligence" for your chinese room machine
I think the only moat in the future will be the scale of hardware deployment. If one company is able to deploy an order of magnitude more silicon, they'll have a firm grip on a SOTA model and massive inference usage.
China or SpaceX seem like the 2 likely candidates in 5 years, but who knows.
well, a stroke of luck until the whole US stock market crashes & everyone's retirement funds get cut 40% I guess when people internalize this. it will have to happen sooner or later though I suppose
Once they make a model better than Fable I’ll be switching to Codex. Their priorities in terms of consumers seem to be better. I do think Anthropic has some solid safety viewpoints, but I don’t necessarily think that either is entirely aligned yet with delivering exactly what humanity needs. Maybe the AI will help align the AI companies when it gets smart enough. That’s the real misalignment I’m concerned about.
I don't think these companies have humanity's needs in mind when they're developing these models. Although the last part of your comment struck me as a bit comical, I genuinely believe that an AI can have way more empathy than a corporation. Afterall, a mimicry of empathy is probably better than no empathy.
You are basically saying you will switch from one evil to another because the other seems less evil for now.
It's funny how people make these alignment comments while ignoring how misaligned the leadership at these companies are right form the get go and they just play mental gymnastics to deflect those facts when confronted with them.
There are no open source models, at least not useful ones (yet) [0]. Open weight is not the same as open source. The current "open weight" models are just opaque binary blobs you can run on your own computer instead of through a web API.
Nemotron Super is sort of open source in the sense that Nvidia provides almost everything you need to replicate it from scratch. Of course it’s performance is not exactly stellar but it could be a good starting point for other research teams.
There is also https://apertus-ai.org/ but yeah, "not useful yet" if you were looking to replace your coding agent. Very useful if you are doing LLM research.
50% off at open router is also still applied so it comes out at $2 / $10 per 1M.
Feature request for Artificial Analysis, allow us to see these live prices on the pareto. It would amazing to also see what a 25,50,75,100 % utilised subscription costs compared to raw tokens.
if you're picking AI models for long-term sustainability you're doing it wrong. There's really no point in locking in model choice for anything more than a month or two these days.
What about companies purchasing enterprise contracts? Most contracts are minimum 12 months. At a minimum, to secure enteprise requirements like zero-data retention, you'll need to lock into a single provider.
These price reductions are mostly targeted towards self-serve customers on individual or small team plans, where individual choice matters and the friction of changing models/providers is low.
Using codex every day, in spite of which, I hope some day providers will just start naming their offerings small/medium/large, a bit like we eventually started doing in software testing. Trying to remember what Sol is or why it's better than the other thing is more cognitive effort than I can muster at this point. And that's a sure sign of commoditisation in itself
Tinfoil hat time: They saw everyone referring to Mythos, and later Fable, as the new “good” models when Anthropic released those, distinguishable from the “regular” Claude (or other companies’ models) for everyone, and didn’t have that distinction for the GPT model family. That’s why the planetary names were introduced.
I think model naming has been atrocious in general, in part because newer "lite" models surpass the capabilities of previous "pro" models (case-in-point: Gemini Flash which now surpasses the capabilities of the latest Gemini Pro, with a newer Flash Lite vying somewhat unsuccessfully for the old Flash price/positioning), but gpt 5.6's Sol/Terra/Luna split is really not bad at all - probably easier to understand than Starbucks' cup sizing!
The problem becomes when you add in the adjustable reasoning efforts and you end up with {model, reasoning_effort} combinations that end up completely obviating particular model classes altogether for at least some percentage of queries; e.g. with GPT 5.6 the price/performance Pareto frontier is dominated by permutations of either Luna and Sol, with Terra nowhere to be seen (but then if you need "large model smells" that aren't captured by your benchmark you can't even rely on this, as a model like Luna simply isn't capable of encoding sufficient world knowledge in its weights to perform certain tasks at any reasoning level but you might be able to get away with Terra on low reasoning, but no one seems to be covering this for some reason).
The "until at least Nov 21st" thing presumably mainly affects teams that pin to GPT-5.6 Sol (maybe after extensive testing) such that they won't be switching to GPT-5.7 or GPT-6 or whatever new model is released between now and November.
These price drops are absolutely bonkers. Gotta love competition! Glad we didn't end up with a duopoly of openai and anthropic, we got a glimpse of what nightmare that would've been and it wasn't pretty
Which is not that great for people using less than 50% every week, because the next reset date moves forward too. In essence, it is redistributing compute from people who haven't used their quota much to those who have.
Though I think they gave a banked reset this time.
The Chinese are coming after these greedy-ass frontier labs. Today Xiaomi unveiled it's own inference machine .... I bet it's gonna be cheaper than Nvidia DGX, shipped with open source models that anybody can have at home.
But can these really be trusted? There was just a HN post which proofed that you can train a model to behave completely different on a certain day. How do we now, that these models do not find a way to call home when they see interesting informations (probably irrelevant on a personal level, but corps, government and military might care).
ChatGPT already notifies the authorities if it thinks you’re doing something illegal. Fable downgrades itself if it thinks you’re doing something even vaguely suspicious.
I'm not sure I could characterize the frontier labs as greedy, given that they've been consistently losing gargantuan amounts of money.
The people who give them the money are greedy, and hopefully in for a rude awakening. Starting from Nvidia's vendor financing which has a very direct benefit to them, through to every company and oligarch investing into data centres in the hopes of being one of the ones left capitalizing on capturing the livelihoods of the majority of what remains of the "middle class".
It's either hopium or a truly horrific dystopia. Something's going to have to give.
The fact that AI models can be so easily distilled and replicated is such a stroke of luck.
10 or 15 years ago if one had asked me to envision a future where a private company invents artificial intelligence, I'd have thought for sure they'd have a massive moat, be very difficult to catch, and it would create an almost instant monopoly.
Rather, it seems that selling intelligence might end up as a race to the bottom.
Who woulda thought that just having access to enough textual inputs and outputs and a vaugely similar transformer architecture would be enough to copy-cat rather useful intelligence.
Even before LLMs, ML folks were already aware that you can use a model to teach another model. I doubt this is something AI companies put at the top of their investor materials, but it's been nice to see it play out.
That said, there are other moat factors like, a US company needing to use a US AI provider, sticky customers due to corporate onboarding friction, and others. Not nothing, but not as large a moat as some imagined.
Yes, but 10 or 15 years ago, I would have thought that there'd be more to it than just a slight modification on the ideas behind a CNN to get this level of AI.
It reminds me of the seo antics out there. The search results page is the engine, much like how distilling is the "intelligence" for your chinese room machine
Where is the actual evidence of distillation? I keep seeing this repeated ad nauseam but I must have somehow missed the evidence.
[delayed]
Altman specifically has said in an interview that I listened to once that he envisions AI being as cheap as electricity.
Yeah, he sure does lie about a variety of things! He doesn't have the name Scam Altman for nothing.
He also wanted to do a non-profit.
He even raised money on that premise.
He is a pathological liar, so is Dario. Don’t rely on the benevolence or truthfulness of these people.
They will say whatever is beneficial to say in the moment.
I think the only moat in the future will be the scale of hardware deployment. If one company is able to deploy an order of magnitude more silicon, they'll have a firm grip on a SOTA model and massive inference usage.
China or SpaceX seem like the 2 likely candidates in 5 years, but who knows.
well, a stroke of luck until the whole US stock market crashes & everyone's retirement funds get cut 40% I guess when people internalize this. it will have to happen sooner or later though I suppose
I'd take a market crash over a monopoly in the hands of a ghoul like Altman.
The economy he and his ilk want to build is infinitely worse.
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This is funny because the stock Market has been ahistorically high. My portfolio went up over 20 percent in the last 12 months.
A major correction would be a bummer but we were never entitled to these abnormal gains in the first place.
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It's a 20% discount on input and a 33% discount on output through at least November 21, 2026; the revised pricing schedule is now
So Sol is still 20x Luna, but much more appealing when compared to offerings from Anthropic and others.
This stacks with the 50% discount in OpenRouter, making it $2/$10. https://openrouter.ai/openai/gpt-5.6-sol
Once they make a model better than Fable I’ll be switching to Codex. Their priorities in terms of consumers seem to be better. I do think Anthropic has some solid safety viewpoints, but I don’t necessarily think that either is entirely aligned yet with delivering exactly what humanity needs. Maybe the AI will help align the AI companies when it gets smart enough. That’s the real misalignment I’m concerned about.
I don't think these companies have humanity's needs in mind when they're developing these models. Although the last part of your comment struck me as a bit comical, I genuinely believe that an AI can have way more empathy than a corporation. Afterall, a mimicry of empathy is probably better than no empathy.
[delayed]
You are basically saying you will switch from one evil to another because the other seems less evil for now.
It's funny how people make these alignment comments while ignoring how misaligned the leadership at these companies are right form the get go and they just play mental gymnastics to deflect those facts when confronted with them.
I don’t think anyone said anything about either being less evil? Just having more consumer oriented products..
Absolutely loving this price war, long live open source models.
> long live open source models
There are no open source models, at least not useful ones (yet) [0]. Open weight is not the same as open source. The current "open weight" models are just opaque binary blobs you can run on your own computer instead of through a web API.
[0] https://allenai.org/
Nemotron Super is sort of open source in the sense that Nvidia provides almost everything you need to replicate it from scratch. Of course it’s performance is not exactly stellar but it could be a good starting point for other research teams.
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There is also https://apertus-ai.org/ but yeah, "not useful yet" if you were looking to replace your coding agent. Very useful if you are doing LLM research.
[dead]
50% off at open router is also still applied so it comes out at $2 / $10 per 1M.
Feature request for Artificial Analysis, allow us to see these live prices on the pareto. It would amazing to also see what a 25,50,75,100 % utilised subscription costs compared to raw tokens.
What good does a temporary price reduction do for production workloads? I'm not even running evals on something that is not long-term sustainable.
if you're picking AI models for long-term sustainability you're doing it wrong. There's really no point in locking in model choice for anything more than a month or two these days.
What about companies purchasing enterprise contracts? Most contracts are minimum 12 months. At a minimum, to secure enteprise requirements like zero-data retention, you'll need to lock into a single provider.
These price reductions are mostly targeted towards self-serve customers on individual or small team plans, where individual choice matters and the friction of changing models/providers is low.
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Do you have guarantees that the price of the model you’re using in production today won’t increase in the future?
Bummer, this does not affect the weekly usage on Codex through Subscription.
Using codex every day, in spite of which, I hope some day providers will just start naming their offerings small/medium/large, a bit like we eventually started doing in software testing. Trying to remember what Sol is or why it's better than the other thing is more cognitive effort than I can muster at this point. And that's a sure sign of commoditisation in itself
Tinfoil hat time: They saw everyone referring to Mythos, and later Fable, as the new “good” models when Anthropic released those, distinguishable from the “regular” Claude (or other companies’ models) for everyone, and didn’t have that distinction for the GPT model family. That’s why the planetary names were introduced.
Sun, Earth, Moon — it’s basically L/M/S like you want but a little less boring.
Why is large better than medium to the average end user of ChatGPT though?
I don’t think there’s a way to name these things that will satisfy everyone.
The naming schema actually tripped me up for a week or so.
My brain's initial conception of the concepts was earth-relative, so I mapped it as:
Sol = big, it's the sun Luna = medium, in-between sun and earth, space Terra = small, terrestrial
I think model naming has been atrocious in general, in part because newer "lite" models surpass the capabilities of previous "pro" models (case-in-point: Gemini Flash which now surpasses the capabilities of the latest Gemini Pro, with a newer Flash Lite vying somewhat unsuccessfully for the old Flash price/positioning), but gpt 5.6's Sol/Terra/Luna split is really not bad at all - probably easier to understand than Starbucks' cup sizing!
The problem becomes when you add in the adjustable reasoning efforts and you end up with {model, reasoning_effort} combinations that end up completely obviating particular model classes altogether for at least some percentage of queries; e.g. with GPT 5.6 the price/performance Pareto frontier is dominated by permutations of either Luna and Sol, with Terra nowhere to be seen (but then if you need "large model smells" that aren't captured by your benchmark you can't even rely on this, as a model like Luna simply isn't capable of encoding sufficient world knowledge in its weights to perform certain tasks at any reasoning level but you might be able to get away with Terra on low reasoning, but no one seems to be covering this for some reason).
The "until at least Nov 21st" thing presumably mainly affects teams that pin to GPT-5.6 Sol (maybe after extensive testing) such that they won't be switching to GPT-5.7 or GPT-6 or whatever new model is released between now and November.
Your move, Anthropic
These price drops are absolutely bonkers. Gotta love competition! Glad we didn't end up with a duopoly of openai and anthropic, we got a glimpse of what nightmare that would've been and it wasn't pretty
Thanks to both China & capitalism
[dupe] https://news.ycombinator.com/item?id=49396590
completely offtopic but how are you always there with a valid dupe link?
Not for subscribers though
Subscribers already get random rolling resets.
Which is not that great for people using less than 50% every week, because the next reset date moves forward too. In essence, it is redistributing compute from people who haven't used their quota much to those who have.
Though I think they gave a banked reset this time.
How do you know? I see a “weekly usage limit” bar in my ChatGPT settings, but I’m pretty fuzzy about what makes it go down.
If I stick with Luna, I can make it through the week.
ChatGPT Work and Codex use that. Normal chat has a different, unspecified limit.
then what happens?
they discovered a great way to destroy their own stickyness and make ppl build generic ai solutions.
The Chinese are coming after these greedy-ass frontier labs. Today Xiaomi unveiled it's own inference machine .... I bet it's gonna be cheaper than Nvidia DGX, shipped with open source models that anybody can have at home.
But can these really be trusted? There was just a HN post which proofed that you can train a model to behave completely different on a certain day. How do we now, that these models do not find a way to call home when they see interesting informations (probably irrelevant on a personal level, but corps, government and military might care).
Above average levels of paranoia here, but one way you can prevent that is by not connecting the machine in question to the internet.
ChatGPT already notifies the authorities if it thinks you’re doing something illegal. Fable downgrades itself if it thinks you’re doing something even vaguely suspicious.
I'm not sure I could characterize the frontier labs as greedy, given that they've been consistently losing gargantuan amounts of money.
The people who give them the money are greedy, and hopefully in for a rude awakening. Starting from Nvidia's vendor financing which has a very direct benefit to them, through to every company and oligarch investing into data centres in the hopes of being one of the ones left capitalizing on capturing the livelihoods of the majority of what remains of the "middle class".
It's either hopium or a truly horrific dystopia. Something's going to have to give.
The company may be losing money but the people are getting enormously rich and cashing out religiously