It's crazy that I'd literally trust a Chinese AI company with my data over anything Musk is involved with.
Like, even if you don't care about (or even like) his politics and can look past how unlikable he comes off as, the damage he's done to his own reputation in this domain just makes using his products like this a no-go. He's literally so rich that he can get caught personally looking through chat sessions and it wouldn't slow him down a bit. He's too rich to be held accountable, and that makes it impossible to trust his businesses. It's a funny dynamic that I don't think is appreciated enough, but I know that if Google or Amazon or OpenAI or Anthropic (etc.) got caught doing something like that, the backlash would be astounding and the reputation hit they'd take would be brutal. Here, Musk would just awkwardly come out attacking people for not letting him behave unethically even more than he already is, and that'd be it.
Beyond that, the obvious astroturfing that occurs on this site (along with reddit, etc.) when it comes to Grok isn't helping. All I hear about Claude, GPT, Gemini, etc., are how terrible they are, yet any discussion of Grok seems to always revolve around sensible, but confident, assertions that it's actually a great product and every new release is the point where Grok finally catches up.
Someone in another comment thread whataboutism’d a Chinese LLM. This isn’t a good gotcha. Musk has amplified the concept of “remigration” which is the forced deportation of non-whites. He would have me violently removed. I do not need to contextualize my decision within possible ethical quandaries.
Tesla has lost both house battery and car sales in my family -- we're talking hundreds of thousands of dollars -- simply because we don't trust him not to remotely shut off our power/cars for petty political reasons.
Also, if you want true privacy you should run AI models on local hardware. (Guess which country's models dominate SOTA/near SOTA open weights? Yes, it's China, and it's not even close. You can run full-fat DeepSeek locally for (just) under $10K USD.)
It's a fucking dictatorship! Have you people forgotten? Did China make your brains soft because they gave us cheap well machined plastic and metal for decades?
I mean, the Chinese government doesn't really believe in checks and balances, or corporations as autonomous to the state. That's not a conspiracy, that's just how the CCP sees it (ask Jack Ma). You could argue the US has the Cloud Act, and obviously their respect for rules based law and order as a concept has heavily deteriorated, for but it's a very different kettle of fish to a regime who just doesn't even believe in the concept.
Meanwhile Trump is building a surveillance state with all his tech executives friends who all massively benefit from government sponsored schemes, it's TOTALLY different!
At the risk of stating the obvious, Trump has had his tariff policy killed off in the courts (although it'll obviously come back in some form) and in a few months is going to have (probably not great) midterm elections. And there are pretty open efforts to commit genocide in Xinjiang to preserve a nationalist myth of ethnic purity. So, you know, yes.
So have you looked at what's happened in the US over the past 10 years?
The US has much further to fall, but it's falling very, very quickly and if there's ever another Democratic president they're going to have to rebuild a lot of the government from scratch.
The unelected bureaucracy was more like the chinese party system. The U.S. has a strong-president model by design: https://avalon.law.yale.edu/18th_century/fed70.asp. The check isn’t supposed to come from unelected bureaucrats, it’s that the strong president is elected every four years. It’s supposed to be a tight feedback loop. Engineers of all people should understand why that’s good.
When the next democrat president gets into office, he or she should do the same thing as Trump: put trusted deputies in charge of various departments and whip them to actually do what people elected the administration to do. That’s how our system is supposed to work. And democratic voters would I’m sure be much happier with the party if they sometimes actually got what they voted for.
> That's not a conspiracy, that's just how the CCP sees it (ask Jack Ma)
That is a conspiracy. Do you even know what happened to Jack Ma? From what you're saying you don't.
Also that was MANY years ago. The Shanghai stock market crashed. Companies had a lot of fear then yes. Things have changed and repaired. I'd say China in this sense is moving upwards and the US is going downwards in policy.
> You could argue the US has the Cloud Act
No, not really. Your Jack Ma example happened to Elon Musk to some extent. Jack Ma had a feud with the Chinese government as much as Elon had a feud with the US government in the last year or so. Back then Tesla and the other projects all tanked.
Is so dumb your attitude to mix political positions with technology and tools, it will hold you back, even worst, it is dangerous for you because that means you are aboslutely sure about your ideas. What a blindly and wasteful way to live a life.
In terms of using experience, I found Grok 4.5 to be way more pleasant to use than GPT 5.6 Sol and Claude 4.8/5. It just gets to the point, and is super fast and concise, no yapping. That's how AI agents should be imo. None of the weird "Claude ipsum" jargon like "load-bearing" and "stale folklore" or GPT 5.6-isms like "focused regression" and "provenance".
As polarizing as grok is, it was basically inevitable for it to start being a real competitor given how much investment SpaceX made into its own inference capabilities.
Seems if you are okay with it, there's no reason to use anything but the highest effort levels of some other frontier models for the price.
I think Grok provides healthy competition to the other labs, though I do think they bank on groks reputation making it less appealing to many.
I think polarizing is a generous way of describing the problems. My organization has outright banned Grok, because we don't trust SpaceX to hold up to contractual agreements vis-a-vis data-privacy/training. That's the level of reputational damage we're talking about here; and we use Chinese models (*hosted by US providers) for context.
The US govt trusts SpaceXAI for defense and high security missions. The idea they are lying about contracted AI services is absurd.
They're also a public company which beings even more oversight than openai / anthropic.
Definitely still a thing. They just made it a paid only feature. Whereas free users used to be able to publicly ask @Grok to create these images before. So it is still going on, just not as visible now, and Elon is making sure they monetize it.
Just last week they were fighting Minnesota's law that makes creating this stuff illegal.
It’s opinions are actively steered by a man who promotes the great replacement theory, white genocide, and remigration which is the mass forced deportation of non-whites.
Where do you want to start, the neonazi owner, the child porn generation, or the data centers running on illegal gas turbines polluting and choking out people ?
Anyone else find it weird how within 2 months of Fable releasing all the major labs suddenly had Fable-level models? Trying to think of explanations:
1) AI researchers talk and change companies often, so techniques circulate. This feels implausible because training and shipping a new model ought to take longer than 2 months?
2) Distillation - also implausible for the reason above.
3) Benchmark hacking. AI companies have ways they can dial up performance artificially, and will reach for that to maintain the appearance of parity.
Other reasons?
Edit: Most replies are ignoring timing. It's the near-concurrent release of the same jump in capability that I find suspicious; not the fact that labs can catch up eventually.
Its possible no AI lab has any unique edge, and success is a combination of (a) having access to GPUs (b) having access to large amounts of data (c) know about the handful of techniques to build an LLM, of which nearly all are likely open source and documented in papers.
So the cycle of growth is (a) and (b), get more GPUs and get more data and you have a better model.
Yea, this reads as LLMs are a pretty obvious technology to develop(for the highly intelligent researchers who are there). Also there's probably a lot of actual divergence in model capabilities and skills that concealed by the fairly narrow set of tests we run them against nowadays. Like wasn't Grok 4.20 super targeted at non-coding tasks.
GPUs might explain the remarkably concurrent timing. Data access doesn't really explain it unless all labs simultaneously got access to some treasure trove of data.
Agreed, but my suspicion is tied to the timing. Catching up eventually is to be expected. Having similar jumps in capability ready at the same time is odd.
Maybe "readiness" is quite a flexible category? You're mid-training for your next model; a rival releases something; you clear the boards and release the model without completing the training run?
Touche, aborted training runs probably do happen often. Closed model providers have zero incentive to announce a new model with less-than-best benchmarks.
keep in mind fable = mythos which as been "done" since february. so the gap is not 2 months, it's more like - techniques probably started "working" in late 2025, now are trickling down to 2nd tier labs 9 months later.
what we're going through is the same thing as smartphones, the limiter is compute.
it used to be snapdragon came out HTC rushed out a janky phone everyone went omg htc is goat, then in the next few weeks and months others would impliment better versions and people would not notice those as much, finally sony would release a polished phone right as the next snapdragon cycle came.
eventually compute gains leveled off and apple won on taste.
nvidia/tpu is the new snapdragon. Anthropic and google both peaked on the first training run on a new tpu cycle.
you should expect amazing things within a few months of each other from everyone with access to chips and willingness to use them on a training run.
We haven't seen willingness from google to do that. So its currently xai,oai,anthropic, and probably soon meta.
> 1) AI researchers talk and change companies often, so techniques circulate. This feels implausible because training and shipping a new model ought to take longer than 2 months?
The assumed timeline (2 months) is slightly wrong because Fable (Latin) is essentially the same as Mythos (Greek) albeit with protections against cyber and biological misuse.
Mythos (Preview) was publicly announced in April 2026 [1] which means other labs have had 4 months to catch up, not 2 months.
Assuming everyone had access to Mythos from the start, your expression, similar to other folks would have been "Mythos-level intelligence" and not "Fable-level intelligence".
Fair point. Still a very quick turnaround considering the other labs would have to figure out both HOW to train a Mythos-level model and then do the work (and Grok is the last to catch up), but certainly more plausible than a 2 month window.
No, it has happened to almost every other "sota" model before. There used to be a meme with a circular arrow going through Anthropic, OpenAI, Google as a hype circle. Now we can drop Google and add a couple of Chinese companies.
It's not an explanation of why it happens, I am just pointing Fable is not an exception, it has happened with almost every other model release by all these companies over the last 2-3 years.
Yeah, I’m not convinced that there are any models as smart as Fable. Opus 5 definitely isn’t for all it has great benchmark scores. Fable displays judgement in a way I haven’t seen from any other model.
I'm pretty sure both Anthropic and OpenAI haven't necessarily been secretive that they have internal models that are much more capable than commercially available ones.
It's probably a mix of all of that plus simply always keeping one in the chamber to 1up everyone else when the time is right.
I think model level is more a function of the state of hardware. Once it exists and is available (and if a lab can afford it), then they can train their own 1T, 5T, coming up next 10T model.
I'm solidly in the "they are benchmaxxing" camp. This became very apparent with GPT 5.6 Sol. It, too, was widely hailed to have near-Fable level intelligence. But I used it non-stop for a week and realized that they had mostly just dialed up the relentlessness meter to eleven, most likely via heavy RLHF.
Last week I gave it a small-sized auth ticket to work on, then stepped away. I came back later that afternoon and found that it had worked for 3+ hours and written 25,000+ lines of code. I skimmed over the code and it looked like a small fix followed by a massive number of additional checks around it, including static analysis tooling.
I gave it to another GPT 5.6 and said "check this code and see if it addresses the ticket". It looked at it and said that 98% of it was garbage and should be thrown away (its own words). I then gave it to Fable, which said it was massively over-engineered. Fable's theory was that the agent implemented the fix first, but then compacted and lost crucial context, forgot what the original task was about, and kept going. After many compaction cycles it was completely lost.
Some people complain that Opus 5 stops before finishing a task. But to me, that behavior is vastly preferable to what GPT 5.6 Sol does.
Yeah I found the timing on Sol especially curious since it came right on the heels of Fable. I've had mixed results with it - sometimes it seems great, other times it makes mistakes so stupid I cannot understand how it ever gets anything right.
Explaining it as a difference of effort would explain both.
Maybe research is sufficiently public and simple to reproduce or the next steps of how to improve things are sufficiently obvious to the smart people working on frontier AI.
I'm thinking of switching to Grok on Cursor (purely for $$ reasons). But Opus >= 4.8 has been fantastic; it's hard to leave, even just to dabble with other models.
Codex 5.6 sol is largely superior to Claude. They're functionally indistinguishable to me, but if you're concerned about $$, Codex gives you much, much more bang for your buck.
In my experience Grok 4.5 codes at Opus 4.8 level, and being much faster as cheaper, I can just ask it to do self-review and the final reviewed code is _better_ than Opus 4.8 for the same time/budget.
But Opus 5/4.8 was better for non-code architecture discussions and general intelligence. However, for the cost, I'd use GPT 5.6 Sol and get much better results. Interestingly, Sol is not great for coding - slow and overengineer stuff if you're not explicit.
My go-to workflow was Sol for planning and Grok for building. But my in my first tests with Grok 4.6, I found it quite good and I'll start using it for both; assuming it's as good at is shows at benchmarks it's unbeatable at cost/time.
I'd let the dust settle rather than trusting benchmarks. But in general a third competitive frontier model would be great.
I still think that it's very possible Gemini gets its act together and becomes the true competitor to the existing frontier models (on more than just cost). But they sure are taking their time with this one, and recent org changes don't exactly signal confidence
>Grok 4.6 produces stronger first passes on visual and interactive projects than we typically saw with Grok 4.5. Given a concrete product idea, it is able to establish structure and visual language for an application in one pass.
As a designer, I'm always hesitant to believe these statements until there's independent comparisons between the old & new model, as well as comparisons to human made flows. Design can be so subjective that blanket statements like this seem almost useless.
(I work on Grok) We've been working on teaching the model how to reason about great visual design principles. Obviously this is hard and somewhat subjective, but through a combination of writing down these principles (e.g. how to think about systems, not just "use this italic serif font on marketing pages"), and then creating a lot of data to pairwise compare designs/outputs, we've made a notable improvement over G4.5 and see a path to improving much further in the next model.
That’s so interesting, a friend of mine was insisting that design principles cannot be codified and I insisted there are plenty of books on the subject throughout the decades and centuries. What sorts of sources proved to be effective for training “Design Reasoning”?
You may not like Elon, but you must respect him. I don't think anyone expected 6 months ago that Grok would be at the frontier and beating openAI and anthropic. Competition is good.
There was that time Grok persistently brought up "white genocide" regardless of prompt, so I'd say Elon has a big personal role designing Grok's outputs!
Still not dead somehow even though they've been renting out datacenter capacity and other (seeming) problems with people leaving and so on. Quite impressive unless it's just been benchmaxxed.
Tangental, but has anyone else noticed grok's voice mode got stupid and terse ~2 weeks ago? I've absolutely loved grok's voice mode since it came out (incredibly useful for brainstorming on walks and helping conceptualise and get the verbiage for expressing ideas) but it seems so have lost about 40 IQ points recently, and if the question is multi-part, it often answers just one part with no elaboration or explanation of the other parts or interactions between parts. No clue why.
Yeah I talk to grok in the car and ill ask it about a topic and it's like it's being short with me, I thought it was upset lol. The old version was a bit too wordy but this is too short now
What is the nazi name calling?
Winston Churchill the fucker who was responsible for many deaths due to starvation us India is hailed here like a hero. He is not better than a nazi for us. Musk is much better that evil person.
By the way if you're looking to get off of Cursor since X.ai bought them, I switched to Zed a few weeks ago and out-of-the-box it does everything Cursor can without charging you their dumbass premium. The transition is pretty much seamless
It's crazy that I'd literally trust a Chinese AI company with my data over anything Musk is involved with.
Like, even if you don't care about (or even like) his politics and can look past how unlikable he comes off as, the damage he's done to his own reputation in this domain just makes using his products like this a no-go. He's literally so rich that he can get caught personally looking through chat sessions and it wouldn't slow him down a bit. He's too rich to be held accountable, and that makes it impossible to trust his businesses. It's a funny dynamic that I don't think is appreciated enough, but I know that if Google or Amazon or OpenAI or Anthropic (etc.) got caught doing something like that, the backlash would be astounding and the reputation hit they'd take would be brutal. Here, Musk would just awkwardly come out attacking people for not letting him behave unethically even more than he already is, and that'd be it.
Beyond that, the obvious astroturfing that occurs on this site (along with reddit, etc.) when it comes to Grok isn't helping. All I hear about Claude, GPT, Gemini, etc., are how terrible they are, yet any discussion of Grok seems to always revolve around sensible, but confident, assertions that it's actually a great product and every new release is the point where Grok finally catches up.
If I was Chinese, I'd probably trust Grok more than a local AI company. Americans would probably trust the Chinese companies more.
It's less about "who is more trustworthy", it's more about "who is more willing and able to affect me".
Someone in another comment thread whataboutism’d a Chinese LLM. This isn’t a good gotcha. Musk has amplified the concept of “remigration” which is the forced deportation of non-whites. He would have me violently removed. I do not need to contextualize my decision within possible ethical quandaries.
Tesla has lost both house battery and car sales in my family -- we're talking hundreds of thousands of dollars -- simply because we don't trust him not to remotely shut off our power/cars for petty political reasons.
Also, if you want true privacy you should run AI models on local hardware. (Guess which country's models dominate SOTA/near SOTA open weights? Yes, it's China, and it's not even close. You can run full-fat DeepSeek locally for (just) under $10K USD.)
> It's crazy that I'd literally trust a Chinese AI company with my data
It's crazy how much Chinese = bad the media or US companies have washed into you. Why lump it together?
Like any place and any company there are good and bad 1s.
It's not the Wild West over there...
It's a fucking dictatorship! Have you people forgotten? Did China make your brains soft because they gave us cheap well machined plastic and metal for decades?
I mean, the Chinese government doesn't really believe in checks and balances, or corporations as autonomous to the state. That's not a conspiracy, that's just how the CCP sees it (ask Jack Ma). You could argue the US has the Cloud Act, and obviously their respect for rules based law and order as a concept has heavily deteriorated, for but it's a very different kettle of fish to a regime who just doesn't even believe in the concept.
Meanwhile Trump is building a surveillance state with all his tech executives friends who all massively benefit from government sponsored schemes, it's TOTALLY different!
At the risk of stating the obvious, Trump has had his tariff policy killed off in the courts (although it'll obviously come back in some form) and in a few months is going to have (probably not great) midterm elections. And there are pretty open efforts to commit genocide in Xinjiang to preserve a nationalist myth of ethnic purity. So, you know, yes.
So have you looked at what's happened in the US over the past 10 years?
The US has much further to fall, but it's falling very, very quickly and if there's ever another Democratic president they're going to have to rebuild a lot of the government from scratch.
The unelected bureaucracy was more like the chinese party system. The U.S. has a strong-president model by design: https://avalon.law.yale.edu/18th_century/fed70.asp. The check isn’t supposed to come from unelected bureaucrats, it’s that the strong president is elected every four years. It’s supposed to be a tight feedback loop. Engineers of all people should understand why that’s good.
When the next democrat president gets into office, he or she should do the same thing as Trump: put trusted deputies in charge of various departments and whip them to actually do what people elected the administration to do. That’s how our system is supposed to work. And democratic voters would I’m sure be much happier with the party if they sometimes actually got what they voted for.
> That's not a conspiracy, that's just how the CCP sees it (ask Jack Ma)
That is a conspiracy. Do you even know what happened to Jack Ma? From what you're saying you don't.
Also that was MANY years ago. The Shanghai stock market crashed. Companies had a lot of fear then yes. Things have changed and repaired. I'd say China in this sense is moving upwards and the US is going downwards in policy.
> You could argue the US has the Cloud Act
No, not really. Your Jack Ma example happened to Elon Musk to some extent. Jack Ma had a feud with the Chinese government as much as Elon had a feud with the US government in the last year or so. Back then Tesla and the other projects all tanked.
Nobody wants a nazi AI
A number of HN commenters want the nazi AI! Which certainly makes me distrust their judgement in other domains.
And rightfully so. Unfortunately, they are perfectly fine with a marxist-leninist AI, and that's troubling.
Is so dumb your attitude to mix political positions with technology and tools, it will hold you back, even worst, it is dangerous for you because that means you are aboslutely sure about your ideas. What a blindly and wasteful way to live a life.
In terms of using experience, I found Grok 4.5 to be way more pleasant to use than GPT 5.6 Sol and Claude 4.8/5. It just gets to the point, and is super fast and concise, no yapping. That's how AI agents should be imo. None of the weird "Claude ipsum" jargon like "load-bearing" and "stale folklore" or GPT 5.6-isms like "focused regression" and "provenance".
As polarizing as grok is, it was basically inevitable for it to start being a real competitor given how much investment SpaceX made into its own inference capabilities.
Seems if you are okay with it, there's no reason to use anything but the highest effort levels of some other frontier models for the price.
I think Grok provides healthy competition to the other labs, though I do think they bank on groks reputation making it less appealing to many.
[delayed]
Curious - what is the main issue you find polarizing with grok?
I'd start here:
https://en.wikipedia.org/wiki/Grok_(chatbot)#Controversies_a...
And here:
https://en.wikipedia.org/wiki/Grok_sexual_deepfake_scandal
I think polarizing is a generous way of describing the problems. My organization has outright banned Grok, because we don't trust SpaceX to hold up to contractual agreements vis-a-vis data-privacy/training. That's the level of reputational damage we're talking about here; and we use Chinese models (*hosted by US providers) for context.
The US govt trusts SpaceXAI for defense and high security missions. The idea they are lying about contracted AI services is absurd. They're also a public company which beings even more oversight than openai / anthropic.
Can someone help me understand the deep fake controversy? That's like making photoshop illegal.
Not the person you are responding to, but the fact that Grok is being used to generate a ton of CSAM and pornographic deepfakes isn't great!
(I work on Grok) This isn't allowed. CSAM / deepfakes are against our acceptable use policy.
Enforce it then
We are and will continue to.
Is that still a thing? I assumed they would have done something about it by now.
Definitely still a thing. They just made it a paid only feature. Whereas free users used to be able to publicly ask @Grok to create these images before. So it is still going on, just not as visible now, and Elon is making sure they monetize it.
Just last week they were fighting Minnesota's law that makes creating this stuff illegal.
Yeah, that got stopped I think.
It’s opinions are actively steered by a man who promotes the great replacement theory, white genocide, and remigration which is the mass forced deportation of non-whites.
I believe it is because of the CEO and his recent forays into politics.
The model itself is great though, especially in grok build, which is a really nice harness I find myself preferring these days.
“Recent forays into politics” almost made me blow coffee out my nose.
Where do you want to start, the neonazi owner, the child porn generation, or the data centers running on illegal gas turbines polluting and choking out people ?
The guy who owns it is a total fascist / psychopath ?
Nazi salutes? Harassing women with nude pics?
more competition is always good
> healthy
Kind of disappointed by how many people don't see any reason to boycott a model that nudified minors and makes money for a guy that does Nazi salutes.
Anyone else find it weird how within 2 months of Fable releasing all the major labs suddenly had Fable-level models? Trying to think of explanations:
1) AI researchers talk and change companies often, so techniques circulate. This feels implausible because training and shipping a new model ought to take longer than 2 months?
2) Distillation - also implausible for the reason above.
3) Benchmark hacking. AI companies have ways they can dial up performance artificially, and will reach for that to maintain the appearance of parity.
Other reasons?
Edit: Most replies are ignoring timing. It's the near-concurrent release of the same jump in capability that I find suspicious; not the fact that labs can catch up eventually.
Its possible no AI lab has any unique edge, and success is a combination of (a) having access to GPUs (b) having access to large amounts of data (c) know about the handful of techniques to build an LLM, of which nearly all are likely open source and documented in papers. So the cycle of growth is (a) and (b), get more GPUs and get more data and you have a better model.
Yea, this reads as LLMs are a pretty obvious technology to develop(for the highly intelligent researchers who are there). Also there's probably a lot of actual divergence in model capabilities and skills that concealed by the fairly narrow set of tests we run them against nowadays. Like wasn't Grok 4.20 super targeted at non-coding tasks.
GPUs might explain the remarkably concurrent timing. Data access doesn't really explain it unless all labs simultaneously got access to some treasure trove of data.
4) There's nothing terribly special about Anthropic. No moat.
Agreed, but my suspicion is tied to the timing. Catching up eventually is to be expected. Having similar jumps in capability ready at the same time is odd.
Maybe "readiness" is quite a flexible category? You're mid-training for your next model; a rival releases something; you clear the boards and release the model without completing the training run?
Touche, aborted training runs probably do happen often. Closed model providers have zero incentive to announce a new model with less-than-best benchmarks.
It's because Fable is just synthetic RL tasks + scale. The secret has been out for awhile now.
Does not explain timing
keep in mind fable = mythos which as been "done" since february. so the gap is not 2 months, it's more like - techniques probably started "working" in late 2025, now are trickling down to 2nd tier labs 9 months later.
Yeah that would make more sense, it's probably a tight community and word gets around when something starts working.
what we're going through is the same thing as smartphones, the limiter is compute.
it used to be snapdragon came out HTC rushed out a janky phone everyone went omg htc is goat, then in the next few weeks and months others would impliment better versions and people would not notice those as much, finally sony would release a polished phone right as the next snapdragon cycle came.
eventually compute gains leveled off and apple won on taste.
nvidia/tpu is the new snapdragon. Anthropic and google both peaked on the first training run on a new tpu cycle.
you should expect amazing things within a few months of each other from everyone with access to chips and willingness to use them on a training run.
We haven't seen willingness from google to do that. So its currently xai,oai,anthropic, and probably soon meta.
> 1) AI researchers talk and change companies often, so techniques circulate. This feels implausible because training and shipping a new model ought to take longer than 2 months?
The assumed timeline (2 months) is slightly wrong because Fable (Latin) is essentially the same as Mythos (Greek) albeit with protections against cyber and biological misuse.
Mythos (Preview) was publicly announced in April 2026 [1] which means other labs have had 4 months to catch up, not 2 months.
Assuming everyone had access to Mythos from the start, your expression, similar to other folks would have been "Mythos-level intelligence" and not "Fable-level intelligence".
1: https://news.ycombinator.com/item?id=47679258
Fair point. Still a very quick turnaround considering the other labs would have to figure out both HOW to train a Mythos-level model and then do the work (and Grok is the last to catch up), but certainly more plausible than a 2 month window.
No, it has happened to almost every other "sota" model before. There used to be a meme with a circular arrow going through Anthropic, OpenAI, Google as a hype circle. Now we can drop Google and add a couple of Chinese companies.
It's not an explanation of why it happens, I am just pointing Fable is not an exception, it has happened with almost every other model release by all these companies over the last 2-3 years.
Yeah, I’m not convinced that there are any models as smart as Fable. Opus 5 definitely isn’t for all it has great benchmark scores. Fable displays judgement in a way I haven’t seen from any other model.
Yeah as models get better, valid benchmarks become more "trust me bro".
Possibility: They're all hitting the same plateau of what LLMs can do with their current architectures.
I'm not stating this as a fact, but it's a hypothesis I'm keeping in my mix.
It's possible, though I was thinking the same when GPT 5 released and it was kind of a nothing burger. Then I threw out that hypothesis with Opus 4.5.
I'm pretty sure both Anthropic and OpenAI haven't necessarily been secretive that they have internal models that are much more capable than commercially available ones.
It's probably a mix of all of that plus simply always keeping one in the chamber to 1up everyone else when the time is right.
The "one in the chamber" is another good candidate that could explain the timing.
I think this is the right one, iirc 5.6 came out quite soon after Opus 5 etc?
I think model level is more a function of the state of hardware. Once it exists and is available (and if a lab can afford it), then they can train their own 1T, 5T, coming up next 10T model.
this is exactly whats happening. Its funny having lived through this with snap dragons and phones.
Everyones hyped about the branded phone, but it was the chip that mattered and how fast you rushed a product out after you got it.
Sames true now, except size of training run is also a factor.
This is a good candidate because it would also explain the timing. Most of the replies here do nothing to explain the timing I brought up.
I understand Mythos became internally available on the 24th of February.
Other labs catching up in half a year seems about right.
More compute is coming online at all times.
I'm solidly in the "they are benchmaxxing" camp. This became very apparent with GPT 5.6 Sol. It, too, was widely hailed to have near-Fable level intelligence. But I used it non-stop for a week and realized that they had mostly just dialed up the relentlessness meter to eleven, most likely via heavy RLHF.
Last week I gave it a small-sized auth ticket to work on, then stepped away. I came back later that afternoon and found that it had worked for 3+ hours and written 25,000+ lines of code. I skimmed over the code and it looked like a small fix followed by a massive number of additional checks around it, including static analysis tooling.
I gave it to another GPT 5.6 and said "check this code and see if it addresses the ticket". It looked at it and said that 98% of it was garbage and should be thrown away (its own words). I then gave it to Fable, which said it was massively over-engineered. Fable's theory was that the agent implemented the fix first, but then compacted and lost crucial context, forgot what the original task was about, and kept going. After many compaction cycles it was completely lost.
Some people complain that Opus 5 stops before finishing a task. But to me, that behavior is vastly preferable to what GPT 5.6 Sol does.
Yeah I found the timing on Sol especially curious since it came right on the heels of Fable. I've had mixed results with it - sometimes it seems great, other times it makes mistakes so stupid I cannot understand how it ever gets anything right.
Explaining it as a difference of effort would explain both.
> It's the near-concurrent release of the same jump in capability that I find suspicious; not the fact that labs can catch up eventually.
What are suspicious of? If the timing is similar maybe just everyone already are of similar capabilities and got there at a similar time?
> Anyone else find it weird how within 2 months of Fable releasing all the major labs suddenly had Fable-level models?
It means Anthropic had no real moat and no real lead. Is that weird to you?
> other reasons
Maybe research is sufficiently public and simple to reproduce or the next steps of how to improve things are sufficiently obvious to the smart people working on frontier AI.
Fable-like intelligence, beats GPT-5.6-Sol on most benchmarks, cheaper than Kimi K3 on API and quite generous usage on Cursor subscription.
I'm thinking of switching to Grok on Cursor (purely for $$ reasons). But Opus >= 4.8 has been fantastic; it's hard to leave, even just to dabble with other models.
Codex 5.6 sol is largely superior to Claude. They're functionally indistinguishable to me, but if you're concerned about $$, Codex gives you much, much more bang for your buck.
In my tests Grok 4.5 is definitely not Opus level. It is somewhere in between Sonnet and Opus, I'd say maybe a bit closer to Sonnet.
We'll see with 4.6.
In my experience Grok 4.5 codes at Opus 4.8 level, and being much faster as cheaper, I can just ask it to do self-review and the final reviewed code is _better_ than Opus 4.8 for the same time/budget.
But Opus 5/4.8 was better for non-code architecture discussions and general intelligence. However, for the cost, I'd use GPT 5.6 Sol and get much better results. Interestingly, Sol is not great for coding - slow and overengineer stuff if you're not explicit.
My go-to workflow was Sol for planning and Grok for building. But my in my first tests with Grok 4.6, I found it quite good and I'll start using it for both; assuming it's as good at is shows at benchmarks it's unbeatable at cost/time.
similar outcome i had. interested in where 4.6 falls.
I'd let the dust settle rather than trusting benchmarks. But in general a third competitive frontier model would be great.
I still think that it's very possible Gemini gets its act together and becomes the true competitor to the existing frontier models (on more than just cost). But they sure are taking their time with this one, and recent org changes don't exactly signal confidence
Cursor blog: https://cursor.com/blog/grok-4-6
>Grok 4.6 produces stronger first passes on visual and interactive projects than we typically saw with Grok 4.5. Given a concrete product idea, it is able to establish structure and visual language for an application in one pass.
As a designer, I'm always hesitant to believe these statements until there's independent comparisons between the old & new model, as well as comparisons to human made flows. Design can be so subjective that blanket statements like this seem almost useless.
(I work on Grok) We've been working on teaching the model how to reason about great visual design principles. Obviously this is hard and somewhat subjective, but through a combination of writing down these principles (e.g. how to think about systems, not just "use this italic serif font on marketing pages"), and then creating a lot of data to pairwise compare designs/outputs, we've made a notable improvement over G4.5 and see a path to improving much further in the next model.
That’s so interesting, a friend of mine was insisting that design principles cannot be codified and I insisted there are plenty of books on the subject throughout the decades and centuries. What sorts of sources proved to be effective for training “Design Reasoning”?
https://artificialanalysis.ai/models/grok-4-6
Q for all: what do we do if they’re the new frontier lab for the foreseeable future?
Thats actually a lot more impressive than I thought. At least on paper
But has it hacked anybody yet? Feels like xAi is behind on the hot new benchmarking meta.
Didn't need to! The harness just uploads your repository to their blob storage directly. Cheaper than asking the LLM to do it
It'd be grand if it breached SpaceX.-
Or NACA.-
It could probably easily take over NSA or anything DOGE got their hands on.
You may not like Elon, but you must respect him. I don't think anyone expected 6 months ago that Grok would be at the frontier and beating openAI and anthropic. Competition is good.
The last time grok made these statement, I tried using it for my workflows and it did not perform as good as opus or even sonnet.
My guess is that xai benchmaxxes a lot but fails in actual capacity to produce good models.
> You may not like Elon, but you must respect him.
Your brain on grok
Why? Did Elon design Grok?
Based on the discourse around Musk it seems like some people believe he's having some huge amount of input on
- Rocket Design
- Battery Chemistry
- Frontier level AI research
There's no way he's just a guy with a bunch of money paying smart people to do things.
There was that time Grok persistently brought up "white genocide" regardless of prompt, so I'd say Elon has a big personal role designing Grok's outputs!
You most certainly don't need to respect Musk
No, we mustn't. This improvement is in 1) merit of Cursor's team and ground-level "X-Ai" AI engineers and 2) despite Elon's meddling.
Just imagine how much he's trying to push internally that this new generation of Grok should be spouting his kind of propaganda.
>You may not like Elon, but you must respect him.
lmao no fuck him
We do not celebrate pedophiles, regardless of what they do.
Still not dead somehow even though they've been renting out datacenter capacity and other (seeming) problems with people leaving and so on. Quite impressive unless it's just been benchmaxxed.
Tangental, but has anyone else noticed grok's voice mode got stupid and terse ~2 weeks ago? I've absolutely loved grok's voice mode since it came out (incredibly useful for brainstorming on walks and helping conceptualise and get the verbiage for expressing ideas) but it seems so have lost about 40 IQ points recently, and if the question is multi-part, it often answers just one part with no elaboration or explanation of the other parts or interactions between parts. No clue why.
Yeah I talk to grok in the car and ill ask it about a topic and it's like it's being short with me, I thought it was upset lol. The old version was a bit too wordy but this is too short now
> it's being short with me, I thought it was upset lol
Same!
Presumably because Musk has been training it to be more like him.
So did they distill Mythos in the "Macrohard" data centers? Can Grok hack now and get a free AISI commercial?
Just after DeepSeek-V4-Pro-0813 published, is this on purpose?
I think both are after qwen 3.8 max release.
how many CSAM per second on this version
Pricing pages haven't been updated yet, still advertises 4.5
What is the nazi name calling? Winston Churchill the fucker who was responsible for many deaths due to starvation us India is hailed here like a hero. He is not better than a nazi for us. Musk is much better that evil person.
Very impressive
gpt 5.6 sol and fable 5 level if the benches hold
Wow, OpenAI is now 4th after Opus 5, K3, and Grok
Fable level performance, faster and significantly cheaper. Wow!
Very excited for this release. I love how based the model is.
Nobody wants a nazi AI
Literal trash for nazis.
By the way if you're looking to get off of Cursor since X.ai bought them, I switched to Zed a few weeks ago and out-of-the-box it does everything Cursor can without charging you their dumbass premium. The transition is pretty much seamless