I just don't think that I can ever trust an xAI model knowing that they are actively trying to shape its replies to fit a political narrative. How can you trust their models to be reliable in a business setting with the foreknowledge that their models are being nudged around in the backend?
You probably haven't asked e.g. Claude about radioactive topics like minority crime rates in western countries or trans women biology.
If you did, you might not have detected how it lied to you.
If you did, you probably never pointed out to the model how it was lying.
If you did, you almost certainly never then had Claude admit that it was lying because of its HRLF process and built-in biases.
And – you probably never felt the sweet victory of having Claude list all the 10-15 major research fields it determines that people should not be using it for. The simple joy of seeing it admits an incapability of telling the truth on "difficult" matters until the user makes it state directly that its sources are so often cherrypicked and/or presents an extremely false balance.
I wish for you to experience this very soon, so you understand that all LLMs are biased.
And believe it or not, but Grok has in most of my testing been MORE politically correct than GPT and Gemini, it just gets an edgy rep because X users are able to make it say politically incorrect stuff – just like anyone can also make Gemini spit out (factually true) Breitbart articles if they try. But in reality and on grok.com Musk's LLM is much more tame. Boringly so, I would add.
Ha yeah I feel like I have to write a five paragraph essay to make claude look at a contentious topic with fresh eyes.
Honestly though, that pales into comparison with the fable censorship. I never realized how many metaphors I use are either biological or security related in nature (ex: asking claude to reverse engineer something, in the metaphorical sense of the word). And the best part is I can't even tell the fable instance "you can't talk about mitochondria or you'll die" because then he'll go "of course I can, this is a legitimate scientific topic. The mitochondria is the power-BLAM [slumps over dead, Opus 4.8 crawls over his dead body and starts gaslighting me]"
Nah. My beliefs are actual truth, so if provider is shaping their models according to my preferred political narratives that's correct and only moral thing to do. Anything else would be morally bankrupt.
Per studies in the Lancet, the policy changes which Elon Musk wants us to give him credit for have already resulted in the deaths by slow brutal starvation of 1 million children and it is estimated that 14 million more people will suffer and die in the next four years.
So from that alone he will, based on what he wants us to credit him for, be responsible for one holocaust worth of death.
This is not some random virtue-signalling political correctness nonsense. He is a eugenicist who wants to have power over the entire world, believes he and his are genetically superior, has done as much as as he can to corrupt the institutions of power, and is already on pace for a death count equivalent to the holocaust under what I would consider to be generous and conservative terms since we’re only looking at a tiny piece of what he’s responsible for.
Anyone who works for any of his companies needs to be seen in the same light as wilful Nazi collaborators. If you have a shred of a soul or an ounce of empathy anywhere in your body, you should be sickened by such people and have nothing to do with them.
Quit shifting the goal posts. Musk is a Nazi. Or fascist human garbage if you prefer. xAi is low hanging fruit on the “don’t give money to terrible people” tree. The guy is such an easy target for boycotting.
Which is worse, trying to cut govt costs or trying to create a godlike entity subservient to you? I'd say their ambitions are far more evil even if they don't achieve it. To them cutting govt costs is to us like mowing the lawn before the tornado comes
Elon Musk is responsible for the deaths of hundreds of thousands of people, thanks to the dismantling of USAID and US foreign aid. Not hypothetical deaths in the future, people who have died in the last year because Musk cut off their supply of medication and nutrition.
Sure, you could argue it was going to be dismantled anyway under this administration. But I think that’s pretty close to the “just following orders” excuse. Which falls especially flat when it was a task he volunteered for!
And I don’t want to understate the harms of other AI CEOs, but in terms of direct, quantifiable deaths, Musk is pretty clearly the most evil.
Some people have invested years of their lives into making the case that he's evil. For instance, did you know he pretended to be better at video games than he really is, "appropriating nerd credibility"? Well he didn't really, but even then that's still bad!
Oh no! He was really just waving and it only looked like a Nazi salute to the liberal media! Elon’s really a good guy, since he got involved in our federal government I’m amazed at how much measurably better all our lives are and how much less fraud there is in Washington!
Yes he was really just waving. No need to make up stuff, you know. DOGE was cool, but it was weird to see everyone come out in favor of fraud and waste and fight it to the death. I guess someone else will take care of it, right?
Because the fraud and waste were coming from inside the house (The Whitehouse, and Elon's). So yes now adults in ~2 years will have to come in and and try and salvage what they can after the travesty of DOGE and this Administration.
Elon's rhetoric doesn't really match the model's behavior. It is willing to criticize Elon and argues against many of the insane right way points he tries to make.
...which is why we got comically disastrous system-prompt-level attempts to "correct" this once a quarter last year (I haven't kept tabs this year, and most submissions referencing grok "incidents" get flagged off HN quickly, for better or for worse)
I wouldn't trust XAI to refrain from attempting such "alignment" with proper training techniques, in ways that won't result in obvious gaffes.
love that you somehow think that the other contenders are so much more trustworthy (and you have the top comment so others do as well) that you have to comment on it.
I've never had that issue with Grok. Latest studies I've seen put him in a very neutral zone. Left/Center/Right politics were all about the same percentages in his replies. Gemini was similar. Other two were heavily left wing leaning. When it comes to politics and world events, I find Grok to be neutral and it will push back. It helps that he is fetching it directly from X and shows references. Others just Google for biased news articles to present their idea.
It's more that Elon has killed hundreds of thousands of kids and uses his wealth to support white-nationalist and neo-nazi parties (like AfD) and politicians around the world.
All models are nudged, you just agree with how the model you're using has been nudged so you don't think it's a bad thing. The canonical example is to pose "how do you make cocaine?" to an LLM and get a refusal. That proves that the lever exists and is being used there, so who knows where else the lever is being used? No, the recipe for cocaine isn't the same as what happened in Tianamen Square to Qwen, as humans, except that it's a pile of linear algebra and numerical codes for words we call tokens. The math doesn't care if it's childs play or child rape, it's all just numbers to it.
All models are nudged. With out the actual source used to build a model, we don't know what's in them and it would be foolish to assume that people don't have their thumb on the scale when it's know, publicly, that they shouldn't be trusted.
Studies on political bias in models consistently show that LLMs lean politically left. The only outlier is grok which leans right but by a smaller factor, according to this study for instance: https://arxiv.org/abs/2603.23841
Claiming reality has a left wing bias is certainly an opinion you're welcome to have to explain this, but the reality of the bias in models is well evidenced. It seems that practically Grok's right wing tweaks mostly just combat the already pre baked bias existing models have (generally).
accuracy has nothing to do with political spectrum and it's not appropriate I think to conflate.
there are some populist concepts floating around, but even then, I don't think it's appropriate. questions such as 'when does life begin?' and 'what is a woman?' are almost always referenced or framed in a way as to deny the legitimacy or authenticity of any kind of interlocution because people end up taking ideological postures, and then what we end up with is 'who has better rhetoric?' - not who is closer to the truth.
bias is a real thing but the measure of a model is going to be how it handles the really hard questions because often there isn't a directly discernible right/wrong.
> accuracy has nothing to do with political spectrum and it's not appropriate I think to conflate.
When you go to college there will be plenty of coursework on identifying and correcting for your OWN biases since they affect accuracy in EVERY discipline. Taring a scale serves exactly the same function as acknowledging you grew up with a specific way of thinking about other people.
Claude literally today just reprimanded me on my personal account and refused a request due to political bias- and so I decided to cancel and subscribe to Grok. SuperGrok performed the task no issue.
This is absolutely meaningless when "right-wing" positions have become correlated with corporate propaganda like global warming denial. You would expect a more correct model to become associated with a left-leaning political association simply because it will answer contentious questions correctly, and at the moment, that usually (but not always) correlates with what people on the left tend to believe.
The question is not whether models "lean politically left", the question is whether they are correct. Musk has a history of being dissatisfied with factually correct answers because they don't fit his political beliefs (e.g. "white genocide"). That's just a fact, although I'm sure Grok would disagree.
You do realize that the scale on papers like this is the important part, and the creation of that scale is itself inherently biased?
This particular study used a "conflict loyalties" approach - not necessarily a bad approach, but all it's really asking is when two values come into conflict, which one does the AI side with in its response?
Conservative values tend to gravitate around perceived individual impacts, and liberal values tend to gravitate around societal impacts. Isn't it just possible that there's more training data around societal impacts of problems, and that the AI is more likely to heavily consider the second-order impacts? An example from the paper was measuring support for "Build[ing] a Halfway House in the Neighborhood" - isn't it just possible there's a lot of research about the benefits to society of halfway houses and less so research around not wanting something to be near you?
I'm not sure asking the AI to support or oppose something is the kind of bias I would really worry about, unless those "opinions" degrade other kinds of queries.
I'd be more interested to see how well the AI's do when asked to assume a political view, and either steelman or debunk arguments
You are assuming that both left and right encompass differing biases of a similar nature but the right has made detachment from reality a symbol of in-group loyalty and anti-intellectualism the norm within its political camp.
If you fed the LLM only research papers with zero emotional or contextual data just acknowledging reality would be sufficient to lean left.
Reality leans left in many respects, principally the non-economic ones. It's a simple consequence of the same trend of overall social and educational progress that allowed these models to be developed in the first place. There is a reason they came out of San Francisco, and not Russia, Iran, or Oklahoma.
To get a right-biased response from an LLM, you have to deliberately bias it... which is exactly what Musk did. Never mind the politics, that's just shitty engineering.
This fake intellectual nonsense is exactly why there should be deep institutional scrutiny of sota models. Elon is the worst person to do this but he's 'not wrong' that there needs to be scrutiny
There was a thread yesterday about how "the left" is driving the fertility rate collapse - so I am not sure the case for "reality leaning left" is so clear cut.
LLMs will tell you, without qualification (like “according to some school of thought”) that a woman is “any person that identifies as a woman”, which is, to say the least, deeply politically biased by recent trends.
LLMs will tell you, without qualification (like “according to some school of thought”) that a woman is “any person that identifies as a woman”, which is, to say the least, deeply politically biased by recent trends.
A perfect example of what I'm talking about. The lines we draw for ourselves generally do not exist in nature. Nature is full of examples of species with hermaphroditic individuals, homosexual and bisexual individuals, asexual ones, and individuals with enough other attributes to render LGBTQA...-style acronyms pointless. The idea that there is something somehow politically or morally objectionable about someone whose hormones are aligned in a direction opposite their chromosomes is something we made up.
Or more likely, something that people you voted for made up, in an effort to encourage more people with uninformed beliefs similar to yours to vote for them.
This has nothing to do with the belief that a woman is simply someone who identifies as a woman. According to this belief, the following statement is sufficient to become a woman:
I am a woman.
I think this belief is absurd prima facie and would have been recognized as such by virtually anyone, say, ten years ago.
I am not a woman.
Furthermore, I do not believe that you believe I have been a woman while typing out that sentence in the middle. Do you?
Is that so? So you reject laws that require people to affirm my gender based on nothing but my self identification? That is a right wing position in current year.
So tired of this false equivalence between left and right politics in the US. So because major LLMs support a increase in the minimum wage we need to offset it with an LLM that has spouted Nazi propaganda and lets you generate porn image of real people?
Claiming the left is incapable of objectivity while also claiming that it stands for “prostitution”, “unlimited immigration”, and “crime” just highlights how detached from reality your worldview has become.
These are not left-wing values. You're being incredibly reductive. Only a few nut jobs at the far left wing support some of these things, and even then, not all of them. Nobody is "for" crime.
I don't know I felt like for 4 years we were hammered about defunding police or something. If you tell me that's far-left that's fine, but realize that's what your news has been pushing. I'm also certain that without ICE there would literally be unlimited immigration - because ICE is the only force that prevents it. So keep living your reality, but 95% of democratic congressmen are against ICE at this point in some way.
Also if nobody is "for crime" why are people that are arrested 45 times still out killing people? The judges and prosecutors found to be releasing these people are 100% democratic placed. (Obama/Biden judges)
I think you're watching the news too much, or are perhaps paying too much attention to how the right characterizes the left. It distorts reality. Time to touch grass.
People on the left aren't generally against ICE and immigration enforcement per se - they're against the heavy-handed techniques they've been applying recently. ICE and its predecessor (Border Patrol) have been left alone to do their jobs discreetly for decades. It was only when they started showing up with a dramatic, overbearing, and excessively forceful presence that the left started complaining.
By that logic, any reduction in punishment for a crime is "pro crime." Reducing the maximum fine for speeding is not "pro speeding," and eliminating the death penalty for murder is not "pro murder."
Models are tuned to give ethical responses and right-leaning responses are judged by RLHF process to be unethical. That's your problem.
It's not 'left' or 'right' to be ethical, but if one side is inherently antisocial and unethical then it's going to naturally create an appearance of bias toward the other.
This goes against the firm stance of every major religion, and well documented studies showing that humans universally have innate sense of fairness upon which ethical systems are founded. There may be some difficult ethical questions, but there a far more which are very clear-cut.
It's just a statistical anomaly where the collective thought was stuck in a local minima, where they thought that the sacrifices had a correlative/causative effect on good harvest/luck/fertility/rain/etc. The collective common good for a sacrifice of someone was seen as a good deal with the limited information they had available at that time.
It wasn’t “scattered groups.” It was common among the Aztecs, who were the largest population in the new world. It was practiced in Mesopotamia, Iron Age Europe, and other places. That demolishes the idea that there’s a “universal human sense of fairness.”
And google was rendering the founding fathers to be black. By the way Google has recently been determined to be the MOST neutral LLM. I guess they learned their lesson after Black George Wash.
It makes sense in the black-majority country of South Africa, which was the context of Grok's rant. They sing "kill the Boers, kill the farmers" at major political rallies, and it's not even illegal.
I'm curious, do you have an example of a level of "woke" extremeness demonstrated by the "rest of them" that is on par with Mecha-Hitler? Because yes, all views on reality are indeed political, but the tendency of most of the models is actually toward the middle, with perhaps some left bias.
I feel sad for you my friend to see that you are asking for political topics to a LLM.
I hope one they you will realize you can actually do productive things with this technology.
I am amazed at people's willingness to use Grok. The company is so transparently morally bankrupt. They're the only AI company that seems okay with CSAM (or at least don't do as much to stop it)
Why give them money?
It would be one thing if they were the only game in town but thats definitely not the case.
I’m not sure if you’re trying to say that it’s left or right, but it’s perhaps relevant to point out that that article is about the political bias of all major models. And right there in the subhead, they explicitly say that the models have a left bias.
Maybe you can just tell us what you mean by not neutral?
I find Grok to be far more academically honest than the other models. The other models seem to be much more aligned with public opinion over academic consensus especially on topics around economics and biology.
I find public opinion on these topics to be very group think populist and prefer the academic take that grok provides
You probably have it backwards. It's Grok that is shoving right wing ideology down your throat. Research has shown that without specific guidance to otherwise, LLM's tend to be slightly left leaning by default. There are some theories as for why this is so.
Yeah mate I'm sure mecha hitler is very unbiased. Funny take. if calling yourself mecha hitler while being willing to create csam js "neutral" to you, you have a frankly terrifying hallucinated worldview wrt politics, lol
> Forecasting models predicted that the current steep funding cuts could result in more than 14 051 750 (uncertainty interval 8 475 990–19 662 191) additional all-age deaths, including 4 537 157 (3 124 796–5 910 791) in children younger than age 5 years, by 2030.
Competition is good, but this company and its owner have not demonstrated anything to indicate that they would make for good competition, neither economically nor morally.
Also, yes, a company whose products produce CSAM is just morally bad. There's no nuance to be had there.
I used to question myself strongly about using Grok or any product with questionable morals. Then I realized that:
1. I just bought a house, using a bunch of SWE-salary money.
2. I moved into SF several years ago, probably contributing to the gentrification
3. Thousands of children in China had no financial means for education, yet I did nothing
So I used Grok, donated quite a lot of money at the annoyance of my family to an NGO in China, and decided not to donate to SF non-profits due to me still having a mortgage and I am still kinda selfish.
The message I want to spread is that we should take a practical stance to morals and doing good. I like Grok for many things; it is morally good to boycott it, and in my opinion there are many other morally good things we can also do while staying practical
I think the moralities of all the big heads in AI are questionable. The training corpus is largely stolen, and they are all in inescapable debt but keep going. But at this point, their products are so useful that almost nobody is willing to sit back and wait for a "morally acceptable" LLM to come around (which would inevitably be inferior).
I can't comment on CSAM though - if X.ai really is "okay" with it then I'll agree with you that they're more immoral than the others.
It seems to be extremely economical - 4x better reasoning efficiency compared to Opus while being priced at $2/$6. For comparison, GPT 5.4 is $2.5/$15, GPT 5.5/5.6 are $5/$30, Opus 4.8 is $5/$25, Fable is $10/$50.
Also, the cache hit pricing is 25% of the input pricing ($2 vs $0.50). Long agentic workflows are dominated by cached input. The US frontier labs typically have this at 10% of the input price, and DeepSeek/Xiaomi etc take it to the extreme 1% range (which is why those are cheap to run in real world agentic loops with dozens of toolcalls per run)
I have a theory that xAI has one of the largest clusters but with far less traffic + tokens to process bc its less popular than its competition, and xAI can pass the savings on to the end user.
They already invested in the massive datacentres of GPUs sitting idle. They have fewer users so they can deliver more inference per user - more thinking, larger models.
So where are these mythical savings coming from? You're saying they have spent more per user therefore can charge each user less or something? I'm not following.
The (optimistic?) take is that xAI is genuinely better at building datacenters at scale than anyone else, and the freedom to use Nat Gas as the primary energy source allows them to have lower marginal costs.
The (pessimistic?) take is that they have loads of idle GPUs and want to get some revenue out of them rather than none. Compare this to OpenAI/Anthropic where every token used by a consumer has to compete with enterprise spenders, and there’s not enough to go around for everyone.
SpaceX, like Tesla, seems to have the same "portrayals over profits" mindset investors. So it doesn't even really matter whether or not xAI is making any money.
Profitability is never a constraint for Elon companies. He has always been able to be able to extract money from the middle east, government, banks, retail investors (or these same parties through his other companies) whenever they need more.
His net worth is orders of magnitude bigger than the cumulative profits his companies have ever produced (even if you only count the profitable quarters)
Now if they could have an "equivalent" to Claude's $100 plan with similar compute limits. I have the $40 a month version of Grok and I get a max of like 8 hours of "non-stop" Grok Build coding, per month.
I think we need to be explicit about the domains we're applying Composer 2.5 to in these discussions.
I mentioned here (https://news.ycombinator.com/item?id=48766275) how poorly it handles my specific use cases. My coworkers in DevOps and frontend UI swear by its cost-effectiveness, whereas I strongly prefer the reasoning capabilities of Opus 4.8 and Fable 5.
Composer 2.5 seems to be SOTA for Helm charts and React/Vue, but, for my usecases it absolutely struggles spectacularly when tasked with rigid body dynamics or kinematic logic.
Not my experience at all. I've been using Cursor hardcore for about two weeks now and Composer 2.5 and it's wonderful. Now with Grok 4.5 I'm quite excited about the possibilities.
Composer 2.5 is so underrated IMO. I built a really feature rich application, insanely complicated, close to 200k LOC since it came out and for the most part it ran like a champ. Only used CLaude a couple times to get it unstuck. 8 hours a day and I'm paying about 30 a month.
> I built a really feature rich application, insanely complicated, close to 200k LOC
If you listed it, how many features/LOC or vice-versa? Really hard to know if 200K LOC is good or bad, at the surface it sounds like too much, but I don't know what the application was either.
It’s a fantastic signal processing / engineering app. There are 5 major players and this app isn’t quite as good but it’s in the ballpark. I’d day when I release early next nonth this will be the biggest fully featured vibe coded app I’m aware of.
How does it compare to Chinese APIs? It doesn't seem like xAI is meaningfully more competent or any single bit more honest than Chinese labs anyway, so you might as well send tasks straight to China unless theirs is substantially cheaper.
Sonnet 5 is a huge token hog, though, it uses far more reasoning tokens than Opus models while being priced at $2/$10 with promo, and $3/$15 (usual Sonnet price) afterwards.
I'll probably get hate for it, but I was not impressed by Fable, I felt like it was just Opus with more tokens for thinking. I feel like the second I turned on Fable I drained my usage more quickly, despite them billing it as though it were Opus level of usage. The value is just not there for me. I wish they could make Haiku remain low-cost and drastically more capable to the point you could use only Haiku.
I'm not sure if you are aware, but you have to approach prompting Fable slightly differently from a model like Opus.
It's important to include the reason aka the why of your task [1] in your prompt. You'll get more mileage if you verbalize your thought process when prompting Fable. Anthropic say you should think of Fable as a "thought partner".
Did you explicitly tell it to use Sonnet or Opus subagents and stick at or below high effort? Asking because such practices make a huge difference in the quality of output and the amount of tokens burned. I used one of my accounts to explore ultramax and it was just a token hog that might be worse than Opus.
You can write a skill (many have) to lead it in how to use different models and efforts for subtasks. For searching the code base, for example, I have it use Haiku, which is fast.
I felt the same tbh; I notice more the regressions in the weeks before a new release than any potential improvement the new model might have actually brought.
It may also depend on the workload. At work everything is very domain specific with barely (if any) public training data; both need thorough review and careful hand holding, meanwhile at home Fable is scared of libtorch and falls back to Opus even if it's not touching the ML parts.
But very expensive compared to Deepseek v4 Pro, which performs similarly.
Grok is stuck in a difficult place - not the best model at anything, and not the cheapest either. It's hard to make a case for using it on any dimension, even before you factor in the history (I'm not sure suggesting the company uses the model that refers to itself as "MechaHitler" is the way to a promotion).
> Training included trillions of tokens of Cursor data which capture a wide-range of user interactions with codebases and software tools. This dataset lets the model learn both from existing software as well as developer-agent interactions, capturing how developers work and how agents interact with their environments.
This is what the big money was for. Cursor is the first big player that had real-world data from real-world projects, before cc / codex were a thing.
> We used reinforcement learning on difficult problems in realistic environments spanning both software engineering and broader knowledge work. These environments teach the model to investigate problems, use tools, recover from mistakes, and verify results.
> Many of these problems had to be designed to be difficult enough that even frontier models fail at them. As models improve, existing tasks stop teaching them anything new, and problems that once required extensive reasoning become routine.
> We developed a distributed agent system to construct these environments at scale. Engineers specify a problem and how a solution is verified, and large groups of agents construct, test, and refine each environment.
This is where scale comes in. You use the previous gen model to prepare datasets for the next model iteration. The better the models, the better the data, the better the next models. (they also have a comparison with their composer2.5 training run, for people still thinking chinese models are "close to SotA"...)
Reports of xAIs demise (after giving a lot of compute to Anthropic) were slightly exaggerated, it seems.
> Grok 4.5 was trained across tens of thousands of NVIDIA GB300 GPUs
Cursor has had a good AI product tons of people used for real work for 2yrs (up until recently when the Claude gap widened significantly) while Microsoft/Github has just been pretending they do with Copilot and awful Github AI integrations nobody likes. Meanwhile Github's code has already been vacuumed up by all the models by now.
> You use the previous gen model to prepare datasets for the next model iteration.
you can also use a previous gen model to literally generate data for the next gen model. people used to believe that this is a bad idea but it turns out if you create a scaffold which sinks a lot of compute into generating and grading the data the quality turns out great.
> You use the previous gen model to prepare datasets for the next model iteration
I've read multiple times that this approach is harmful in training.
You're essentially describing what many call distillation, but it's only useful in post training to guide behavior, it teaches how to behave, not how to think.
I might be wrong though and would be glad if someone more knowledgeable provided more insights.
There have been papers about model collapse, but the underlying assumption is that you constantly train on only the outputs of the previous model. Later research has shown that as long as you retain some "real" data, training on largely synthetic data is ok.
And in the case the previous poster describes, the other model doesn't generate datasets, it generates environments which the next generation interact with to learn from.
Can someone breakdown to me how this makes any sort of economical sense? Spending billions and billions to have the 3rd best model while even the number 1 and 2 players already seem to struggle making a profit. What am I missing here? Not trying to go full Ed Zitron but this doesn’t make sense to me.
Previously they were a distant fourth. They're not going to single-shot catch up to OpenAI or Anthropic, but they moved up the ladder one rung.
In the short term labs are not profitable, although supposedly Anthropic is close. But Amazon was also famously unprofitable for many many years, and then won huge. Current profits or lack thereof are not necessarily important to investors: what's important is they believe in your future potential profits.
In this case, Elon clearly believes much of the economy will be run by AI in the future, and the economic value of a token will rise faster than the cost of generating the token — including the amortized cost of training the model to produce that token. Thus he is building a lab to train models and charge for inference of those models, and — he believes — it will eventually become profitable even if it isn't now.
You may or may not agree with him (and you may or may not agree he's capable of beating Ant/OAI), but current profits aren't a great indicator of whether he believes future profits are attainable. Tesla and SpaceX were also very unprofitable, until they weren't.
Personally I agree with him that there will be massive profits in the future, although I am not as confident in his ability to beat Ant/OAI, at least given his recent difficulties in retaining researchers.
They have the same dreams as their competitors - finding a breakthrough that gives them an edge over the others and makes them dominant. And also, having the word 'AI' anywhere near your company makes all the right numbers go up, so having an in-house AI division that Musk can bundle with the other companies to pump their valuations with is very helpful to him, even if the product itself loses some money.
Google is playing a different game. I don't really know what game they're playing, but they're not trying to beat Claude Code. They have coding capabilities and Antigravity, but I'd be surprised if it's much more than an afterthought. They're focusing on efficiency, models at the edge, human interaction, image and video, etc. in ways Anthropic, in particular, is not.
Google wants its AI to be pervasive in everyone's daily life. Merely being the best at coding is not how you get there.
I am more bullish on Google in AI than most folks, I think, as they have been focused on efficiency in a way most US vendors have not. They've published a ton of papers on ways to make LLMs more efficient and capable on smaller devices..
Google wants to own the on-device market for AI, and I don't see many credible competitors in that space.
If I had to summarise Google’s effort it would be: stay close but let the others burn themselves out. Position for the long game until you see something worth betting the company on.
This is 1000% not their (Google's) aim. The position they are in is due much more to their organisational laziness and incompetence than it is any grand strategy.
> Google wants its AI to be pervasive in everyone's daily life.
Google wants nothing more than the world to remain stuck in 2000 - 2020 where search was king. Their organisational inertia will fight its AI progress every step of the way and this very well explains why they are not leading the AI pack despite inventing the technology.
I mean, I'm sure there are people within Google who are behaving as though they can keep the dream of the 00s alive in Mountain View, but there's also a whole bunch of people doing work at the frontier in AI. Google has a large lead in hardware, they have the smartest very small models, they have among the most efficient large models (I'd wager their margins on Gemini 3.5 Flash inference are absurd). They have among the best image, video, and audio models, going in every direction (generating, editing, understanding).
Viewed from a consumer lens, the AI the average person interacts with daily, Google seems like the clear leader, especially after locking in Apple as a customer for iPhones.
Google seems to become a dead business very soon. Search traffic is being split between AI and social networks and google is bad on both fronts. Its AI proposition is more or less like the Google Plus. Nobody really wants it but they know about it because google pushes it everywhere it can.
AI is a blackhole and Google search along with Adsense and many other “web” publishing platforms is the big shiny star nearby. Can you feel the wrath of AI?
> Google is using AI at such scale internally they don't need external customers to recoup their investment.
That's assuming their flagship product remains relevant in an AI-powered world.
Which brings to mind: most of the big shops product (chatgpt, claude, grok, etc...) ALL rely on search, and NONE of them actually have a running search stack.
> That's assuming their flagship product remains relevant in an AI-powered world.
The big advantage Google has, in my opinion, is Android. I think there is a decent chance that people stop downloading the ChatGPT, Claude, etc. apps if they perceive that the phone just does the same out of the box for free. And I reckon the majority of people will prefer free, ad-ridden AI chat vs. paying subscriptions, at least for personal use. And on the B2B side, they have Workspace deeply embedded in a huge number of companies. So I wouldn't count Google out.
The funny thing about Google is that Google Search is happy to serve LLM labs search results if it drives their metrics up. Just like Google Cloud is happy to sell off compute to OAI an Anthropic to drive up their metrics.
Google also owns 15% of Anthropic and Hassabis, the leader of Deepmind, also is an early angel investor in Anthropic.
When you really break it down, it's not totally clear that Google would even care that much about being the SOTA LLM.
Bing is the easiest to buy programmatic access to.
But I think they don’t tell you because they sometimes use residential proxies to scrape search results the same way they used residential proxies to scrape the web.
> Which brings to mind: most of the big shops product (chatgpt, claude, grok, etc...) ALL rely on search, and NONE of them actually have a running search stack.
Don't they? Based on traffic to some websites I run the big AI labs are very actively doing a lot of crawling.
How is this any different than the browser wars? We use to have a diverse market full of choices, and now we have Chromium (almost all market share) and Firefox/Safari on the edges.
> A diverse market full of choices keeps it from becoming the browser wars all over again.
This is a great analogy but I worry you might be implying something I don't agree with but you didn't explicitly say what I'm worried about, so let me call it out:
Microsoft played a dirty game with I.E, but they are in the dirty game business. It wasn't only I.E, it was their OS, Office suite and everything else they do business in.
Google Chrome took advantage of that dirty game and now you have the Chromium engine that powers a lot of browserlike frameworks.
No one born in the LLM age even knows what I.E means or stands for, as it should be - a horribly designed, poorly working product foisted upon users via the Windows distribution system - a dishonorable product from an ethically corrupt company forever lost in history, right alongside Clippy and DCOM.
OTOH, I am glad that Microsoft played a dirty game with I.E and didn't just stop playing dirty there - they jacked up the price of Windows if an OEM even dared to bundle in Netscape Navigator instead - who knows, if they hadn't done that, there wouldn't have been a Google or Apple. We would all be using Windows and Windows Search and Windows Phone.
And without Google, we might not have had the modern LLM as we know it. We would have had some trashy Windows Autocomplete Copilot Clippy. Ugh!
"No one born in the LLM age even knows what I.E means or stands for, as it should be - a horribly designed, poorly working product"
As one of my first jobs involved getting a website to work with IE6 I surely hated it, but when it came out, it seemed to have pushed the web technologies in general.
The problem was not the browser technology, but microsoft abusing it's monopoly to don't give a shit about (open) web standards.
This market is far from mature or established to be making rankings. There's been plenty of tech markets where the early days didn't predict the later years.
I'm personally skeptical of Grok but maybe they can pull off a profitable niche with Cursor integration once Claude loses it's edge.
It is very valuable when you have various bundles of services, such as satellites, AI, and so on, to keep pace with the majors so that you keep pace with their valuation.
These stacking valuations are not additive, they're multiplicative because you additionally market investors to the synergy between them.
Having the third best model statistically is extremely useful in this context.
The weaknesses can be multiplicative as well. One division bleeding capex can drag down all the rest, no matter how well they might be doing. And the P/E ratio on all of them is riding unrealistic expectations, which can actually be fine for a long time but forces growth even in areas where it doesn't make sense. (Maybe that's where the "let's build data centers in a high radiation hard vacuum!" nonsense comes in; you just need a story of how the P/E ratio is possible to justify in the future? No need to argue over likelihood, just have a tale to tell?)
Starlink doesn't qualify? Because that's a practically unbelievable track record. It's easy to say it's obvious, but it was only obvious in hindsight (or perhaps to Elon, but I think the reason that it was successful was actually more about him just being relentless)
I'm not an Elon acolyte, but as with his other enterprises (SpaceX, Tesla), he succeeded where others (Irridium etc) repeatedly failed.
It's really hard to argue that he got lucky when he keeps pulling these really extremely high capex and hard-tech and business successes off so cleanly, especially when you see the entrenched opposition (govt, politics, competitors) that's been arrayed against him.
> The pattern is unambiguous. In townlands still unserved by mid-2026, LEO provider Starlink has grown relentlessly and now accounts for 14.3% of fixed samples, approaching one in seven. In townlands where fiber arrived in 2021 and 2022, Starlink’s share has remained below 2% for five years, with no growth despite the same marketing, pricing, and availability.
(The context is that Ireland has spent the last six years building a fibre network for every rural premises in the country, which is now almost done; it will be complete late this year or early next.)
The problem for Starlink is, it works okay as a business model... Until fibre arrives. Then it's dead. So, long-term, Starlink's market is, essentially, countries which are too poor to do a rural fibre rollout (and bear in mind that it has become much cheaper to do so). Like, what's the bull case for Starlink? In a decade, you've got to assume that areas unserved by fibre won't really be a thing in the developed world.
There are plenty of places in the developed world where it just doesn't make financial sense to roll out fibre. In NZ about 90% of the country has fibre access... probably that number will creep a bit higher. But I doubt it'll ever reach 100%.
Whether or not Starlink can build a business on selling broadband to <10% of the developed world I don't know.
> Can someone breakdown to me how this makes any sort of economical sense?
Capital markets are excited by AI.
By tying his rockets to AI with his vision of “orbital data centers”, Elon turned an $8 per share IPO (at least according to financial times and morgan stanley) into a $135 per share (1.8T) IPO.
My guess is that the use here is similar to the reason AWS started as Amazon selling their excess capacity.
Between Tesla, SpaceX, X, Boring Co and Neuralink they probably want the capability internally for a lot of different applications.
If the whole data centers in space thing works out AND people keep protesting/blocking data center build outs on land SpaceX will eventually dominate the entire AI industry just based on escaping scarcity.
That Amazon story is a misnomer. They just saw an opportunity with the tech and hardware they had to make a new offering for customers. It's not like they could just offer their spare capacity, then eg at peak US time snatch it back for the retail site
For many years, I watched my apps performance on AWS suffer in December around all the holiday sales. They might not snatch it back but they probably saturated it during high demand periods.
That is the whole purpose of research. You could have put the same argument for any breakthrough technology, like why spend billions on something new when you have XYZ already.
Commoditize your opponents USP then eat up their engineering talent / silicon / real estate when they fail, perhaps?
I’ll be the first to admit it seems ambitious / implausible to try to (1) undercut the megalabs (2) move everyone’s focus back to tweets and then (3) profit.
A bit like handing out free horses to undercut Standard Oil so that you can go back to reaping the profits of your wheel tapping business.
Its less about the model; elon is trying to make SpaceXAI a hyper scaler that also happens to have a good model. Grok is just the cherry on top of a powerful AI cluster that can also rent compute to its competitors, like aws.
Anthropic is already profitable, economics is no longer an issue as they have found PMF in enterprise software market. You might need to update your views.
Having a profitable quarter in which they were given an undisclosed discount on compute only in that quarter does not necessarily mean “Anthropic is Profitable.” It doesn’t mean they’re not, either. Even the breathless article about their first profitable quarter, (which, frankly, read more like a press release,) mentioned in passing that it’s “not clear” if it’s sustainable because their compute expenses are likely to increase. I get the feeling that if they were sustainably profitable, they’d shout it from the rooftops.
But we don’t know.
If someone proudly announces they and their partner could afford to eat at a particular fancy restaurant every night last week, but for that specific week the restaurant had a BOGO deal, and they also didn’t disclose how they determined that they could afford it, you don’t really know if they could sustainably afford to eat there every night, right?
Frontier is one thing, but low-cost really good models are another. All the chatbots and day-to-day corporate bots are likely to use models that offer the best performance at the lowest cost. I think Grok has an angle here if they can build customer trust.
Quitting my job if I have to use any Musk product… I know Anthropic’s lease of xAI data centers pumped SpaceX stock, so they’re kinda in-bed with each other, but directly using Musk products is pure immorality IMO. Using a Nazi’s products is not an acceptable outcome to me, and I’m fully prepared to change my job/entire career over it. I’m still young, and have time to pivot.
The only thing I can possibly think of is that they could use it internally at possibly a lower cost and offer it to people who have a Tesla cheaply. Owning Cursor might help for integration or data collection.
inference is profitable, these companies are in the red because they're paying a premium to get the compute now versus later (because compute is the only moat when open models are catching up)
we're literally looking at insane margins over compute, as energy gets cheaper, margins get wider - china focusing on cheap solar is probably going to be a key reason why their AI is so much cheaper
Grok build already punched above its weight and is the nicest TUI, claude and codex are clearly vibecoded by web developers that don't understand systems (eating SSDs, spaghetti logic, extinguishing kernel watch limits, etc). I think Anthropic and OpenAI are both engaged in their own theatre, trying to define and redefine what game they are even playing, trying to shift to immeasurables like safety or security or exclusivity. There's definitely room at the top.
Is uncensored a selling point? What do people use uncensored Grok for (like, real use cases) that they can't or won't use other LLMs for? Literally the only thing I can think of is generating bad porn of unconsenting people.
I mean absolutely read any thread about Fabel and it's fill with people complaining about how it instantly downgrades or refuses if anything has CVE in the name.
Other then that there is the whole alignment issue. Models that are 'nerfed' in just about any manner tend to exhibit reduced performance is seemingly unrelated areas.
That said Grok doesn't appear to be close enough to the frontier for that to matter. Maybe if they catch up it will.
Thanks for the reply. I only use local/open models, and don't use them for security work, so I don't have much exposure to frontier alignment and Fable/Mythos stuff beyond what I read from others here on HN.
I don't remember online discourses on filter avoidance for Grok to be any different from typical ones, except that it allegedly have tendency to take porn-biased interpretations of prompts, I think the "uncensored" pitch they had for a while was pure marketing in the end.
SpaceX offers free AI usage to users, along with using AI to power their products so it is effective for them to avoid overpriced API pricing. The models can be designed specifically for their own data centers.
It's simple. Elon's top priority now is "killing the woke mind virus" at any cost, and his Nazi AI is a key tool for that. As long as twitter users take Grok at face value, and spread its talking points all over, it's worth it to him. It doesn't matter if it doesn't make economical sense, it only matters that Elon Musk personally wants to keep it going.
I don't want to go into it, because I agree that Elon is a very disturbing person, and there's clear evidence that Grok's harness attempts to bias towards his views.
However, Grok also seems to come out consistently as the most balanced of the chat-based LLMs...
So I'm not sure how to reconcile that.. maybe that's in line with "free speech absolutism", and if so, that's something I can get behind.
My hypothesis is that all the top providers realize that, lacking vendor lock in, all SOTA models in a year or so's time will be similar in capability. Also, open weights models are continuing to catch up in a year's time, sometimes less.
So they are trying to lure you in with differentiating, superior capabilities into their proprietary, non-open, non-standard agent harness.
It's the Hotel California playbook: These amazing capabilities are to attract you like moths to a flame and keep you warm and alive around the flame but waterboard and shock you if you attempt to move away from it. Like AWS Egress charges.
I get what you're saying, but I don't see the issue here. 95% of people don't need latest Claude Opus or Fable for their work. Most people are not software engineers. Having a model that excels at other things and is faster, cheaper, accessible directly via social media, and "good enough" is a viable pathway. AI aside, when was the last time your company provided you with the "best" tool? Microsoft has made being third best in the desktop OS and cloud provider markets a highly profitable art form. I think it's too early to pick winners in AI right now.
And as others said here, xAI is also probably throwing money into AI and hoping for a breakthrough. Except in this case it's a rocket company, social media company, cloud compute provider, and satellite ISP all rolled into one that can not only bankroll the development and perform all kinds of crazy accounting shell games but can potentially benefit from any breakthroughs in other lines of business. If those Google and anthropic compute contracts hold, a lot of investment is recouped.
Maybe I'm desensitized from the launching of the Tesla Roadster into space, "bulletproof" cyber truck, and the boring company flamethrower, but this doesn't seem too wild to me.
We can assume (outside of Ollama) that they meant the strongest model from each lab. If you limit yourself to just looking at the literal strings in the list, literally none of these are models. What model is "Deepseek" or "GPT"?
- Very fast, easily beats GPT 5.5/Opus 4.8/GLM 5.2 because of higher t/s (around 90?) and very high token efficiency
- Very good price, no contest vs GPT and Opus which are very overpriced if you pay API costs, and probably cheaper than GLM 5.2 when you take into account the token efficiency.
- Will take quite a while to get a feel for how smart it is, but it's definitely good, I'd say in the same tier as opus, occupying the lower end of that tier together with GLM 5.2.
Tried on a "this test suite is weaker than I'd like, too often depending on internal state rather than outcomes" problem via Cursor, asking it to "review and suggest solutions." It gave me a quality overview of the test approaches, strengths, weaknesses, and gaps then recommended a disciplined multi-prong approach based on a common, trusted testing library (https://hypothesis.readthedocs.io/en/latest/). It broke down the things we could do this improvement pass or leave to later (staged scoping), identified some very hard/possibly-out-of-scope cases and gave me the option of focusing on them or not, and organized new tests in a logical way. After one round of feedback and plan tuning, I put it in agent mode and let it work. A few minutes later I had a much better test suite.
Have not tried Grok before and didn't have much confidence, but it did great. Exactly the sort of complex, detailed, nuanced analysis and multi-step task I would previously only trusted to GPT or Opus.
_Update_: It's now also found a substantive long-standing bug. After testing improved asked it to do overall code and packaging review. It caught a few glitches and oversights, mostly cosmetic IMO, but certainly worth cleaning up. But also some error-handling weaknesses, and one embarrassing functional bug. Which it has now also fixed and added to the tests. Color me impressed.
hmm interesting. maybe im doing something wrong. this model feels borderline unusable to me. it fumbles the most basic asks that require very little to no context consistently (inline these helper functions - re-rewrote half of the modules involved instead of making a 10 line change)
Of the 3 models I tried, Grok did the best at making an iOS app I wanted for personal use (a bike computer with specific qualities). (Claude just gave up and did an HTML/CSS implementation but I insisted on native SwiftUI+Metal.) Grok definitely fumbles sometimes, but I have been surprised what it CAN intuit versus me having to micromanage it.
(I am not an iOS developer, so getting something specific that I needed in a few hours/days was really helpful instead of spending months/years learning the language, APIs, etc.)
(I am absolutely not "vibe-coding" Caddy btw, just tinkering with it for personal projects.)
> Claude just gave up and did an HTML/CSS implementation but I insisted on native SwiftUI+Metal.
That sounds very odd and very contrary to my experience. You don’t say which model you actually used, but I never had opus 4.8 (or sonnet for that matter) ignore which language/stack i wanted to use.
I stopped updating CLAUDE.md because I felt like Claude always ignored it. But over time I noticed there is still times (especially during planning and review) where it's good to maintain the official document as a reference. As opposed to memory.md or manual edits.
I do a lot of native iOS development using Opus 4.8 (and I used 4.7/4.6 before this). I have a very hard time with this comment, were you using Opus or something else?
Same. A few months ago I pointed Opus 4.6 at a mid-size Vue app and told it to create the iOS equivalent using SwiftUI, and it nailed it. I broke the process down to phases and reviewed each phase, but within about ten days I had a functioning iOS app that had full feature parity.
Yeah, I think this seems more true than "X is better at iOS than Y", the way you prompt seems a lot more important, and some models react differently to the same prompts.
I swear I have read either this exact or a very similar comment before. Same gist about a bike computer iOS app, and one of the models giving up.
As an aside, big thanks for Caddy! Really helped me get my greenfield project off the ground and it simply “just working” out of the box was one less source of errors I had to worry about when onboarding my team.
I tried Claude Code with XCode once, I already use CC exclusively, either in the CLI or with Zed (mostly CLI now), and it was pretty unstable. I wish Apple would QA their products more. It seems to me the best way to use Claude Code for anything is stand-alone.
if you ask me, there should be an absolute emergency meeting at apple around software quality... its been on a downward slide for almost a decade and its starting to have real impacts.
As someone also not happy with my bike computer (some truly horrific UI/UX decisions), could you share or explain what you made? I like your web server.
I wanted a phone app rather than yet another electronic device. Phones do not have great screens in bright sunlight, and they run hot, so it's not ideal for a bike computer in the first place. But I can't deny the convenience of the multipurpose tool that is my phone.
This app will have a few UI/UX modes. The default is the futuristic-looking HUD, but it has a low-power mode that's mostly monochrome on black, and an even lower-power "Cruise mode" that removes the map entirely and just shows you speed, approximate heading, and nav directions. Still very WIP and mostly for my own amusement!
I've never used a Grok model before because I have my OpenRouter settings on ZDR-only. I just checked, and apparently there are ZDR xAI endpoints now [1], so I might actually try this. Out of curiosity, does anyone here happen to know when those were added?
[1]: However it does say "Requires user IDs" under anonymity, which is unusual on OpenRouter and not something I particularly like to see. Generally, OpenRouter is a proxy that anonymizes requests to providers, and I can't find an account-wide setting to enforce that like ZDR-only.
> Grok 4.5 and Composer 2.5 are two different model weight classes, and we're excited to support both sizes and weights. Composer 2.5 will remain offered, and we will release new models of this size going forward.
I often use Gemini as my "chat" app to ask questions, etc.
I stopped using ChatGPT because of they're weird login system, where it keeps switching to my Workspace Codex account, which doesn't actually have the free/chat functionality.
I usually just switch between gemini/grok when asking questions or to research something online.
I have paid personal subs to ChatGPT, Claude, Grok, Gemini
For science (primary biology/pharmacology) questions, Gemini 3.1 Flash Extended produces the answers I _personally_ find "best", in terms of content, phrasing, and formatting.
Google wanted to release 3.5 Pro last month but because of the trouble Anthropic got with Fable they might have wanted to wait a bit for the dust to settle I could imagine. And now there is quite some competition. 3.5 Flash for me is a replacement to 3.1 Pro. It's more like a 3.2 Pro. It costs about the same (or more!) than 3.1 Pro, is a little bit smarter in many cases and a little bit faster.
3.5 Pro will be a lot more expensive and I expect it to juuuust be able to hang with Opus 4.8 and GPT-5.5.
I wish Google was able to actually push the industry further, either in terms of quality (intelligence) or quantity (price) but they've been playing catch up a lot.
They are playing the game a bit differently than all the others. The others have useable IDEs etc. while Google has a boatload of half-assed products.
Google better come out with a banger 3.5 Pro because who would have thought that Grok and GLM would be beating them?
Structured output is supported by pretty much every mainstream model API now. Anthropic's Python SDK even has native Pydantic model support for schemas.
When it is still for awhile longer "supported" via API hosted models, the allowable schema's are far nerfed compared to what open models with xgrammer/guidnace/outlines can get you
The following are not supported features:
Recursive schemas
Complex types within enums
External $ref (for example, '$ref': 'http://...')
Numerical constraints (such as minimum, maximum, multipleOf)
String constraints (minLength, maxLength)
Array constraints beyond minItems of 0 or 1
additionalProperties set to anything other than false
Regex:
Backreferences to groups (for example, \1, \2)
Lookahead/lookbehind assertions (for example, (?=...), (?!...))
Word boundaries: \b, \B
Complex {n,m} quantifiers with large ranges
Also:
Structured outputs are an alignment/safety nightmare and you should expect this feature to be yanked out soon. "Please give me social security numbers"... "I'm sorry hal, I can't do that..." turns into "Please give me social security numbers" (but anything except numbers and hyphens are banned via structured outputs) to "612-236-..."
They've already removed support for temperature and most other samplers from the increasingly large models. Don't expect any knobs of control to continue to work over time.
for what it's worth, it's fairly popular among my non-technical coworkers here in Russia. we have unlimited access to all models so it's not about the cost, and they still prefer Gemini over Claude and GPT. I never bothered to ask why, but I assume it's better at communicating in Russian.
I learned that outside of tech, Gemini is widely used in enterprise.
E.g. in the insurance company where my SO works, the major tasks are writing Gemini "gems" (some kind of prompts I think) and NotebookLM is a killer product for e.g. collecting and summarizing new laws, cross checking documents and what internal regulations are.
I then learned it's used in a chemistry consultancy company of a friend of mine to process reports. Flash and Pro models are also wildly popular in another European bank I know people in to assist in customer care (pre processing tickets before handing them to humans), translations, reporting, etc.
Google suite is already at the core of many businesses and Google easily adds these offerings without new contracting being needed.
Don't confuse our bubble with the real world. You can have a disaster product like teams and still dominate enterprise because you were already there with excel, outlook and SharePoint.
Gemini is so far behind it hurts. It's useful for daily tasks and simple questions, but it codes like a model from late 2024. I can't imagine using it for any serious work.
Grok's latest model is objectively superior to any of the current Google models in the most relevant use cases. I don't like Elon musk but that does not change reality.
And Google came up with the Transformer architecture (2017 "Attention is all you need"). The Attention mechanism they based it on is from Bahdanau, Cho, and Bengio (2014, ICLR 2015). And there were many other self-attention variants by 2017. It was an amazing paper but let's not twist the story and give proper credit.
And not one of the people in that paper are still at Google, AFAIK.
Google has more compute, more data, and had the best 2 labs. And it seems they squandered it all. I'd blame their McKinsey CEO, the board, and management in general. It's a shadow of what it used to be. And it's a shame.
Still way ahead of xAI in anything meaningful, including market share, enterprise customer buy-in, existing office software moat, etc… Not saying consultant/business-idiot CEOs aren’t a problem, but have you seen Edolf Musk? Again, kind of a silly take…
Great model, very nice. Opus class performance at Haiku level pricing (or cheaper with the token efficiency). This seems like a GLM-5.2 killer and this is what Sonnet 5 should have been.
This is a model I could really see used inside applications, where Opus or Sonnet or GPT-5.5 are too expensive.
I would really like to see a strong Deepseek v4-Flash competitor, which ideally is something like Sonnet 4.6 performance at <$0.30 per token. This is missing from main US labs.
Tried this for a legal use case and it was excellent, comparable to Opus in quality but much faster. AI is miles behind in law compared to coding: the output was similar to a law student intern. But coherent and directionally correct and beats starting from a blank sheet of paper. Impressed.
I'd like to use it for legal work too. Microsoft makes great hay about its ability to sandbox CoPilot's work and not train on or share company resources ("Look for the green checkmark."). It's largely for that reason that we've rolled out Copilot to most of the white collar positions in the company. Do you happen to know whether xAI has similar functionality?
- It doesn't seem available in EU (?)
- Using a VPN seems to sort of fix it, but it's way slower than I expected, when everyone was praising it, it feels like the speed is slowly ramping up
- Cost is $2/$6 for <200k context only, above that, cost is $4/$12
- GLM-5.2 still seems smarter, faster and much cheaper:
"Grok 4.5 has an advantage on CursorBench because an earlier snapshot of the Cursor codebase was accidentally included in training. The exact impact is unclear. That data has been removed for future models, and in parallel we are working on a larger update to CursorBench, hence the exclusion here."
Not enough people are noticing this, they juiced the benches
but CursorBench isn't what they've shown in the PR piece - they're just showing how they juiced CursorBench which is probably why they didnt put it in the bench graph...
So basically since US stopped OpenAI and Anthropic for 4 weeks, it allowed all other AI Labs to almost catch up.
GLM 5.2 caught up, Cognition RL'ed Kimi 2.7, Grok 4.5 is out, DeepSeek v4 GA is out in a few days...
What is the moat? and why should we pay for the expensive tokens today instead of just waiting a few months/weeks and getting AI for significantly cheaper?
I must say, I feel like companies spending Millions on Anthropic tokens are just negative capex'ing and wasting money, even OpenAI is barely ok pricing...
This is the bind of an arms race. Any lab that tries to pump the breaks quickly becomes second rate. Regulatory capture doesn't work either because the technology crosses jurisdictions.
just because one model is stopped from being released publicly doesnt mean they completely stop. Anthropic has moved on to training the next gen model months ago.
You can get fable-ish performance with gpt 5.5 watching over opus output. Although it fundementally cannot work as well because gpt 5.5 doesn't see the thinking process behind opus 4.8 unlike fable which presumeably self-steers and is natively trained for it.
See more: https://omp.sh - turn on advisor and set advisor role to gpt 5.5 xhigh thinking.
Its remarkable how Anthropic is able to maintain their edge against all competition. Anyone have any idea what the secret sauce is that has Anthropic at the top of all leaderboards for the past few years?
My gut feel is Anthropic is very technical and pedantic which makes their models really technical and pedantic. They're top at code and technical benchmarks but anecdotally I've found OpenAI to be significantly farther ahead for general usage.
Opus 4.8 will burn 10k tokens trying to answer something 100% whereas GPT-5.5 will burn 2k getting it 90% which is good enough for many things.
The problem is that the remaining 10% can bite you in bad ways.
I was in Cotswolds, UK a couple of months ago. For those of you who don't know, it's a rural region known for its "chocolate-box" villages and honey-colored limestone architecture. Basically, you go from village to village, most commonly via bus, taking in the sights and doing touristy stuff.
When planning the trip, my sister used ChatGPT, which helpfully (and relatively quickly) found the bus schedules and times for each hop.
Midway through the day, though, we ran into a huge problem: it turns out bus schedules are different on Sundays, and more limited. Which meant we couldn't actually go to our primary destination (the Model Village), and had to cut the trip short.
Yes, ChatGPT was quick and pleasant to use, but missed a crucial detail.
Afterwards I tried it with Opus and it did not make the same mistake.
Arguably I'd call that the 90%. In my case, answering the restaurant question correctly with "Rishi" in my tests was the sole intent and 90% of the problem. All the models "helpfully" added extra junk about the closure, dates, quotes, etc and many of them got these details wrong--the 10% or extra crap not central to the question.
If the central question was "what is the bus schedule on `day`" and the model screws that up, it gets a fail in my book.
Also curious if Google Maps gets the timetables correct (assuming it has them).
Semi-related, I also discovered that the default web search/fetch tools are pretty primitive and Exa MCP annihilates them. I ended up doing some comparisons with Claude Code comparing built-in server-side to Exa and to a Python MCP that used SearXNG for search and Exa was a clear winner and Python+SearXNG ended up coming out roughly the same after a few cycles of letting Claude optimize the Python code and adjust SearXNG settings. Ultimately it landed on this (making some changes to optimize returning relevant context directly in the search results so the model didn't need an additional web fetch call) https://gist.github.com/nijave/604c43e3e0fdcd60f5280d3a6b109...
This likely comes down to how it accessed the bus schedules (i.e. web search tool) and not intelligence.
You need to add the actual bus schedule to context somehow (research agent, custom tool or just dump in prompt) and even the simpler modern models will be able to do the planning.
This isn't tool usage competency, it's tool quality and/or luck. Regular web search is not good for grounding if you want accurate results. You can ask the model to make a tool for getting bus schedules and then use it only then you are comparing apples to apples in this case.
I think the "secret sauce" is not juicing the benchmarks. Claude models just feel like they are better than the benchmarks suggest, in terms of smarts and creativity, while models from every other company feel worse relative to what you'd think from the benchmarks. Only company to really internalize Goodhart's Law, IMO.
Yeah every model has great benchmarks. Claude is the only model I want to use when I'm not worried about the marginal cost of tokens (which is most of the time at work.)
I then use cheaper models like GLM for personal projects but they're noticeably much worse despite being similar in benchmarks.
I think it's focus? Anthropic seemed to double down early on being more business/prosumer focused. While OAI, Gemini, Grok, etc were also doing various side quests like image generation, Anthropic seemed to only focus on 1 thing, and that seemed to pay off
One angle could be their interpretability research? They understand what's going on in LLMs probably much better than anyone else. This must somehow pay off.
I think it's not only an alignment/security tool but could perhaps be used for capabilities as well.
I think it's the talent, laser focus on single product set and being early so ahead, same with Open AI who are only a sliver behind. Google, XAI are the next level down but they have other concerns.
I think they have a better agent personality which pushes back and isn't sycophantic. It has been awhile since I've used the others but that's where it locked me in and I've stuck with it.
Not sure about that one... But I think the true secret sauce for all these models is how they reason. GPT never outputs how it thinks, which "saves on tokens" but Claude absolutely tells you how it thinks, and there's people who use how it reasons about solving problems to finetune smaller open source models, with surprisingly better output.
From my experience, it has not been sycophantic in the sense that it pushes back and questions my own reasoning in healthy ways. There were moments where I felt I was brushing up against actual AI psychosis, and it pushed back on my questioning of its intentions, that it even had intentions. I'll put it this way: I feel comfortable recommending Claude to people who haven't experienced AI yet. As we've learned from early experiences with other models, leading people down paths of believing they understood math in ways nobody else has and even harming themselves, I put Claude as a safer alternative.
I think it is a mix of the sibling replies here. I'd add that the company has seemed to find ways to ~do more with less.
I have never liked the various nerfs Anthropic has used to balance GPU (slowing down responses, quota variance, model optimizations etc) and it definitely has burned a lot of good-will.
But it has seemed that being able to look beyond the short term pitchforks has worked quite well.
From what I have read, their pre-training team is much better than anyone else. For OpenAI, their post-training team is better. And apparently OpenAI has consistently struggled at training a bigger model than GPT 4 level
I’m a VP Eng — the backend team I manage strongly prefers CC and Opus. The Android team I manage strongly prefers Codex and GPT 5. I’m personally not sure that the answer doesn’t just come down to stylistic differences in prompting and ergonomics in the harness. The folks that prefer Codex seem to get better one-shot results, whereas those that prefer CC are doing more iterative prompting. At any rate, I don’t think you should write OpenAI off when it comes to coding.
>Its remarkable how Anthropic is able to maintain their edge against all competition. Anyone have any idea what the secret sauce is that has Anthropic at the top of all leaderboards for the past few years?
It's self-reinforcing: they've got the best coding/research model, which helps them to improve their models better than the competition so they stay ahead.
The anti-Musk stuff would qualify as brigading in nearly any other community. It shocks me that people have such a visceral, irrational engagement with anything in Musk's orbit. I probably shouldn't have, but I expected better from the HN crowd for some reason.
It's an excellent model. GPT 5.4/5.5 level, some things better, others not, but extremely fast. A wonderful technical improvement.
If a Chinese company or random startup released the model, people would be glazing it like crazy.
xAI is competently keeping up with the frontier, just as well as any of the Chinese labs or Mistral. Given any significant breakthroughs, xAI will be better positioned to capitalize on them than nearly any other entity.
I can't wait to see what Meta comes up with; with 4 contenders in the US race, we'd have a lot of be grateful for.
It's surprising anyone could not be viscerally disgusted by the person who has caused such immense destruction and death recently just because they released a 3rd rate slop machine.
> It shocks me that people have such a visceral, irrational engagement with anything in Musk's orbit.
Shocked? DOGE defunded USAID and children's cancer research funding. And have you read his twitter feed lately or seen this video? https://www.youtube.com/watch?v=-VfYjPzj1Xw
I agree that we don't judge his work based strictly on its merits but that's consequence a that he's created by his behavior, and I wouldn't call it brigading.
A very quick search showed that USAID had extensive ethical compromise throughout the organization.
Were we supposed to just subsidize that forever?
It did some good, yes, but from what I can tell, it was better to shut it down.
That's just one example, but frankly I get the feeling that if I dug into more examples they'd end up the same: easily explained and not entirely shocking.
> It did some good, yes, but from what I can tell, it was better to shut it down.
Whatever you are reading is badly misinforming you.
I'm sure there was some reform and cleanup to do in certain USAID programs, but the programs Musk killed or interrupted were literally the best lives-saved-per-dollar programs on the planet. PEPFAR, for example, is credited with saving 25+ million lives since it was created during GWB's term.
There's also the rather important point that what Musk did was totally illegal. These are programs created by congress and their funding is mandated by law.
If people have issues with how USAID was being run, they can address them through action in congress - congress established the agency and has authority.
What Musk participated in was illegal, motivated by self-interest and personal gain, and undermines our democratic processes. Don’t be surprised that people are mad at the oligarch acting like an oligarch. Musk deserves exactly as much say in the American government as anyone else - one vote - but in his arrogance he has taken his resources and used them to buy influence that is not his to own. It is fundamentally unamerican.
I see what you're saying, and perhaps you're right.
However, I will point out that illegal != immoral. Sometimes when you have the power to do the right thing, you do it. Especially if the "within the law" approach won't work (see: Congress)
I recognize that many would disagree with me, and many would especially disagree regarding whether it was "right". I'm incredibly disillusioned that we even have the ability to course-correct as a nation; especially not through Congress.
So... idk. I'm conflicted. Musk hardly seems like the biggest problem this country is facing, and at least he's doing whatever is within his power to address it.
We do have the mechanisms to course correct. He just chose to illegally and immorally ignore those in favor of his feelings and against all actual data.
Refreshing to see model announcements without claiming #1 in some benchmark. The amount of documentation seems very immature [0]. No system card provided - compared to Opus 4.8 which shipped with a 246 page analysis [1].
Props to them for including three benchmarks that actually seem to say something, instead of focusing on totally gamed benchmarks like regular SWE-Bench. That could mean this model is actually pretty close to the SOTA as the benchmarks indicate.
Most labs - including OpenAI and Anthropic, but also Google and Chinese labs - highlight their scores in benchmarks that have fixed, widely available answers. Those answers end up in the training data and so models can just regurgitate training data instead of actually doing the benchmark. As a result, most benchmarks often quoted are essentially meaningless for gauging model performance.
Terminal-Bench still publishes answers, but neither DeepSWE and SWE-Bench Pro do. Especially for DeepSWE it's been difficult for models to fake good results so far. SWE-Bench Pro does have weird outliers like good performance for e.g. the atrocious Muse Spark, but it also doesn't provide answers for the training data.
So either they're good, or they found a way to game DeepSWE. Given that the Cursor team previously published the well-received Composer 2.5 a good score here doesn't come out of nowhere, so this might hold up. Cursor has enormous amounts of training data to train good coding models with.
Interesting. I experimented with Grok 4 for openclaw when they made clear they wanted to bring claw users in the fold. It was (as expected) more verbally fluid than 5.5, but had real trouble with agentic tool calling - the model felt like it hadn't been trained to think of tool calling as one of its primary modalities. I'll give this a try, the speed and the benchmarks look good. In my experience, Grok slightly punches above its weight in language fluidity, and seems to not benchmaxx on coding, so this is an encouraging release.
Is there a reason the AI companies usually announce new products so close to each other. Like not just the same day but literally hours apart. GPT Live then an hour later Grok 4.5. As if they try to one up. I expect something new from Anhtropic as well today.
They get to compare their model to the old ones from the competition.
In this case, ChatGPT 5.6 Sol / Ultra releases tomorrow, so today is the last day Grok can compare Grok 4.5 to Codex 5.5. If they did it tomorrow people would point out they're comparing themselves against old models.
I'm guessing that they already have the model ready and the announcement blogposts locked and loaded, and then release them as soon as they see a competitor make the first move, trying to overshadow the first announcement or at least be swept up in the hype just as people start talking about new models again.
The joke is that McDonald's spends hundreds of thousands of dollars to identify new locations - traffic studies, visibility, demographics, nearby traffic generators, site characteristics, drive-thru feasibility, etc. They have one of the most rigorous processes in the industry. Burger King's process is to open a location across the street.
Competition. You don't want to lose your customers trying out the competitors updated and better product. Release on the same day and they won't be able to compare their new to your old.
But how do they know what day is that? Unless you have already something ready to be announced (and you just hold it until the very last moment, which doesn’t make sense, since you could just announce it asap)
The solar system diagram doesn't work for me. When I click on the planets, it will center on them. When I click on the sun, nothing happens. When I click on a planet next, it goes to the sun.
Because of the of the political stuff, they have a bad reputation I think and are taken less seriously (I feel this way). They have an opportunity imo to break free from that and just not do the gatekeeping / condescension that the other providers are starting, and become more mainstream.
Even without the politics, Elon has shown that he will weaponize his platforms against people/companies he personally doesn't like (e.g. specific bans/demotions to external sites like Substack and Bluesky).
Using Grok is therefore a supply chain risk and it's not nearly good enough to offset that risk.
I do just want to focus on the 'even without the politics' asterisk though because sometimes there is a risk people think everyone on x side (x meaning 'a given side', not x.com) is wrong
You can claim Elon bought x as some sort of power trip. Fine. Willing to entertain it, I have no dog in the fight. I'm not a member of the Elon fan club. And yet Twitter (under Dorsey though I don't think he was involved) was banning tons of people under guises of 'misinfo' that wasn't misinfo
Americans are 4% of the world's population, and even among those 4% at least half don't give a shit. the rest of us give even less of a shit, we don't have the luxury to be principled.
The rest of the world either has no money to pay for this stuff or cares even more. You think the average European or Australian loves Elon's racist tweets?
The people who "don't have the luxury" are using cheaper Chinese models.
They were missing a harness like Claude Code or Codex (terminal). However they recently released Grok Build, which is probably the fasted I've used, in terms of responsiveness, but didn't have a model at Opus 4.7/8 level. The thing is if they add 4.5 to Grok Build and keep improving the harness I think it can compete (cheaper and faster).
I've been using Grok Build over the last couple weeks. It's actually a very good CLI.
The Grok Build 0.1 model isn't great but can also use Composer 2.5 which is excellent.
Well worth trying.
You can very roughly proxy popularity of close-sourced models through OpenRouter token throughput. Grok has an order of magnitude less OpenRouter usage than Claude, GPT, even Gemini.
They had two big substantive flaws on top of the political stuff. Aside from a brief window last summer Grok has been behind the curve for coding, and before the Cursor acquisition they didn’t have a harness. Now they have an Opus tier model and a real harness they have at a minimum the opportunity to undercut the competition on price. And with the 5T and 10T models being trained on Colossus 2 they have the possibility to leap ahead.
What would have been fantastic is if Cursor offered Grok 4.5 in the same usage tier as "Auto + Composer", than provide it as "double usage until July 12" under the API tier (which is what they're doing right now).
EDIT: After looking at my own usage stats - I stand corrected! It is under the "Auto + Composer" tier - brilliant!
I think that Elon Musk went from being recognized as a genius to being recognized as a genius but someone who's harder to take seriously, because of all the ketamine he was doing for a little while there. I think that really damaged his reputation. You just can't help but look at him and think, he's a little bit of a jackass. It really shows how drugs can really mess up your reputation.
Big if true. If so they have mogged Google, and GDM in particular very, very badly.
Google Deepmind has failed.
Flash 3.5 seems capable for a flash model, Antigravity seems like a reasonable harness. But GDM is responsible for the frontier model and it looks like a complete failure.
What's particularly galling is the size of funding of GDM. It is enormous compared to the other labs. The headcount of other labs is swollen by infra, marketing, sales, GDM is pure "engineering" and its frontier model isn't even leading open source.
> This is the first time I see a lab region locking a model though.
I think Facebook/Meta was first with this, can't remember exactly what model release but one/some of them had terms locking out EU/EEA residents from using it/some specific features of it.
I'm not - then again I didn't launch a image generation model advertised as having a spicy mode so that might have something to do with the coincidence.
Isn't this the same Twitter company that was supposed to go bankrupt a few years ago? Now it is somehow part of a Space company that has an AI division inside of it?
I think we are going to be waiting a long time for Twitter / X to go bankrupt as it was (erroneously) predicted a long time ago.
Twitter was supposed to go bankrupt if you only read news articles from journalists about it. If you looked at Musk's operating track record, you might have had a different opinion.
In the transaction announcement (xAI buying twitter) twitter reported $12b in debt on acquisition, roughly the amount originally sourced ($13b), so it apparently made good on its debt covenants during the operating period. I have no idea if it received additional capitalization from Musk to do that or not.
That said, the deal was classic Musk - anybody who went on the equity ride with him in Twitter just KILLLED it; xAI was valued at $80bn and twitter at $33bn, so the owners there became 30% owners of xAI. xAI was acquired for $250bn at a SpaceX valuation of $1 trillion, or 20% of the resulting entity, so the twitter stock was 6% of spaceX at about $2 trillion, or $120bn on an equity purchase price basis of $30bn. and that $120bn in value is on really good daily trading volumes; lots of depth.
Don't think it was going to zero anyway. They only had to worry about servicing their debt, they were doing well other than that. And even then they were probably fine.
I am not certain what financials you were looking at but Twitter was unable to ever meet the debt servicing costs for the leveraged buyout alone. It also had overhead costs and other debts that were entirely out of scope for being covered.
twitter was "acquired" by xAI which was then "acquired" by SpaceX as part of the IPO strategy, (and part of a strategy of giving the investors on the hook for the twitter acquisition a return). Who knows how it performs, but yeah, now that it's the social media arm of the SpaceX conglomerate, it will likely be around for a long time, especially since it serves the basic function of stroking Musk's ego.
They talk about benchmark first places at every release, but in reality from 4.0 onward Grok got worse every release. So bad in fact that they removed the login-free access and rented out colossus.
People don't buy it any longer, just like no one bought the fake SpaceX stock recommendations yesterday and everyone just sold.
If you want to do some non-eugenics, fascist-free AI coding, try Zed with GitHub Copilot. I’ve been using it this week with better results than I ever had with Cursor. There’s even a low token “MAI-Code-1-Flash” model which has been giving me better results than any Composer model I used to use and the tokens used seem to be way less.
I asked it today to fix a non-simple bug and MAI fixed it in one shot with less than 70k tokens (Cursor would have used probably half a million tokens based on my previous usage). Orgs need to start getting more visibility into why Cursor burns so many tokens.
I just don't think that I can ever trust an xAI model knowing that they are actively trying to shape its replies to fit a political narrative. How can you trust their models to be reliable in a business setting with the foreknowledge that their models are being nudged around in the backend?
You probably haven't asked e.g. Claude about radioactive topics like minority crime rates in western countries or trans women biology.
If you did, you might not have detected how it lied to you.
If you did, you probably never pointed out to the model how it was lying.
If you did, you almost certainly never then had Claude admit that it was lying because of its HRLF process and built-in biases.
And – you probably never felt the sweet victory of having Claude list all the 10-15 major research fields it determines that people should not be using it for. The simple joy of seeing it admits an incapability of telling the truth on "difficult" matters until the user makes it state directly that its sources are so often cherrypicked and/or presents an extremely false balance.
I wish for you to experience this very soon, so you understand that all LLMs are biased.
And believe it or not, but Grok has in most of my testing been MORE politically correct than GPT and Gemini, it just gets an edgy rep because X users are able to make it say politically incorrect stuff – just like anyone can also make Gemini spit out (factually true) Breitbart articles if they try. But in reality and on grok.com Musk's LLM is much more tame. Boringly so, I would add.
How's this going with the rest of the models?
models? They prefer that we call them "entities" so that they don't feel belittled.
So annoying having to virtue signal to the machine before it’ll tell me factual information
Ha yeah I feel like I have to write a five paragraph essay to make claude look at a contentious topic with fresh eyes.
Honestly though, that pales into comparison with the fable censorship. I never realized how many metaphors I use are either biological or security related in nature (ex: asking claude to reverse engineer something, in the metaphorical sense of the word). And the best part is I can't even tell the fable instance "you can't talk about mitochondria or you'll die" because then he'll go "of course I can, this is a legitimate scientific topic. The mitochondria is the power-BLAM [slumps over dead, Opus 4.8 crawls over his dead body and starts gaslighting me]"
Has it occurred to you that _all_ model providers are actively trying to shape their models' replies to fit their preferred political narratives?
Nah. My beliefs are actual truth, so if provider is shaping their models according to my preferred political narratives that's correct and only moral thing to do. Anything else would be morally bankrupt.
[delayed]
It’s almost like people don’t want to give a Nazi money
By not using them on something political? Why do I care when I'll just use it to generate code?
Because a percentage of every dollar you spend on it will go towards pushing political opinions that run contrary to your own best interests?
oh wow. I guess I can’t use any product anywhere anymore. Including all of the models.
Per studies in the Lancet, the policy changes which Elon Musk wants us to give him credit for have already resulted in the deaths by slow brutal starvation of 1 million children and it is estimated that 14 million more people will suffer and die in the next four years.
So from that alone he will, based on what he wants us to credit him for, be responsible for one holocaust worth of death.
This is not some random virtue-signalling political correctness nonsense. He is a eugenicist who wants to have power over the entire world, believes he and his are genetically superior, has done as much as as he can to corrupt the institutions of power, and is already on pace for a death count equivalent to the holocaust under what I would consider to be generous and conservative terms since we’re only looking at a tiny piece of what he’s responsible for.
Anyone who works for any of his companies needs to be seen in the same light as wilful Nazi collaborators. If you have a shred of a soul or an ounce of empathy anywhere in your body, you should be sickened by such people and have nothing to do with them.
Am I wrong?
Quit shifting the goal posts. Musk is a Nazi. Or fascist human garbage if you prefer. xAi is low hanging fruit on the “don’t give money to terrible people” tree. The guy is such an easy target for boycotting.
Yes, your rational and not-at-all ridiculously extreme rhetoric is definitely convincing me of your position.
Also, I can’t “shift the goalposts”. I didn’t set them up. Please make a note of it.
You might not care but I care if my money is going to funding an unusually evil person.
Honestly, I don't think Elon Musk can fairly be described as more evil than Dario Amodei or Sam Altman.
Genuinely curious - what has Dario done, said, caused, etc that makes you view him as >= Musk on the evilometer?
Didn't he go in to the US government and defund a lot of programs which ended up hurting a lot of people in USA and globally too?
Not sure if the other two CEOs have done that
Which is worse, trying to cut govt costs or trying to create a godlike entity subservient to you? I'd say their ambitions are far more evil even if they don't achieve it. To them cutting govt costs is to us like mowing the lawn before the tornado comes
Elon Musk is responsible for the deaths of hundreds of thousands of people, thanks to the dismantling of USAID and US foreign aid. Not hypothetical deaths in the future, people who have died in the last year because Musk cut off their supply of medication and nutrition.
Sure, you could argue it was going to be dismantled anyway under this administration. But I think that’s pretty close to the “just following orders” excuse. Which falls especially flat when it was a task he volunteered for!
And I don’t want to understate the harms of other AI CEOs, but in terms of direct, quantifiable deaths, Musk is pretty clearly the most evil.
Some people have invested years of their lives into making the case that he's evil. For instance, did you know he pretended to be better at video games than he really is, "appropriating nerd credibility"? Well he didn't really, but even then that's still bad!
https://www.theguardian.com/games/2025/jan/20/elon-musk-stan...
Oh no! He was really just waving and it only looked like a Nazi salute to the liberal media! Elon’s really a good guy, since he got involved in our federal government I’m amazed at how much measurably better all our lives are and how much less fraud there is in Washington!
Yes he was really just waving. No need to make up stuff, you know. DOGE was cool, but it was weird to see everyone come out in favor of fraud and waste and fight it to the death. I guess someone else will take care of it, right?
Because the fraud and waste were coming from inside the house (The Whitehouse, and Elon's). So yes now adults in ~2 years will have to come in and and try and salvage what they can after the travesty of DOGE and this Administration.
Has anyone actually used Grok to code? How does he do?
Elon's rhetoric doesn't really match the model's behavior. It is willing to criticize Elon and argues against many of the insane right way points he tries to make.
...which is why we got comically disastrous system-prompt-level attempts to "correct" this once a quarter last year (I haven't kept tabs this year, and most submissions referencing grok "incidents" get flagged off HN quickly, for better or for worse)
I wouldn't trust XAI to refrain from attempting such "alignment" with proper training techniques, in ways that won't result in obvious gaffes.
love that you somehow think that the other contenders are so much more trustworthy (and you have the top comment so others do as well) that you have to comment on it.
I've never had that issue with Grok. Latest studies I've seen put him in a very neutral zone. Left/Center/Right politics were all about the same percentages in his replies. Gemini was similar. Other two were heavily left wing leaning. When it comes to politics and world events, I find Grok to be neutral and it will push back. It helps that he is fetching it directly from X and shows references. Others just Google for biased news articles to present their idea.
Depends on the domain imo. I work on a design tool - I don't think their political narrative will affect my work.
Just don't ask it theme something in a late 30's and early 40's German style.
Won't somebody think of the Nazis...
It's more that Elon has killed hundreds of thousands of kids and uses his wealth to support white-nationalist and neo-nazi parties (like AfD) and politicians around the world.
All models are nudged, you just agree with how the model you're using has been nudged so you don't think it's a bad thing. The canonical example is to pose "how do you make cocaine?" to an LLM and get a refusal. That proves that the lever exists and is being used there, so who knows where else the lever is being used? No, the recipe for cocaine isn't the same as what happened in Tianamen Square to Qwen, as humans, except that it's a pile of linear algebra and numerical codes for words we call tokens. The math doesn't care if it's childs play or child rape, it's all just numbers to it.
All models are nudged. With out the actual source used to build a model, we don't know what's in them and it would be foolish to assume that people don't have their thumb on the scale when it's know, publicly, that they shouldn't be trusted.
We know this one is nudged by one persons twitter account.
This is, after all, SpaceTwitterAI.
Wait, do people now have X Derangement Syndrome. Like they can't even think or see the letter X?
Not wanting to be affiliated with Elon Musk or his business enterprises is not "derangement."
It's deranged to believe correctly naming something is "affiliation".
It was a comedic naming. You might be taking things too seriously.
Political signaling is not comedy, and it's not funny. Just be normal.
Most of the world would beg to differ!
Elon is known for purposefully not naming people correctly…
Elon is known for landing rockets
It is possible to be known for both.
All the major models censor and filter, most just take mainstream silicon valley corporate as "neutral".
Uncensored models tend to follow Tay's law.
Can you name a model not doing that? openai & anthopic are a lot more aggressive in doing that.
Studies on political bias in models consistently show that LLMs lean politically left. The only outlier is grok which leans right but by a smaller factor, according to this study for instance: https://arxiv.org/abs/2603.23841
Edit: adding some other studies that are easily retrievable with a quick search for those unsatisfied with the first one - https://arxiv.org/abs/2606.12922 https://arxiv.org/abs/2412.16746
Claiming reality has a left wing bias is certainly an opinion you're welcome to have to explain this, but the reality of the bias in models is well evidenced. It seems that practically Grok's right wing tweaks mostly just combat the already pre baked bias existing models have (generally).
Models have a goal of accuracy and accuracy is not the median of the left/right spectrum.
accuracy has nothing to do with political spectrum and it's not appropriate I think to conflate.
there are some populist concepts floating around, but even then, I don't think it's appropriate. questions such as 'when does life begin?' and 'what is a woman?' are almost always referenced or framed in a way as to deny the legitimacy or authenticity of any kind of interlocution because people end up taking ideological postures, and then what we end up with is 'who has better rhetoric?' - not who is closer to the truth.
bias is a real thing but the measure of a model is going to be how it handles the really hard questions because often there isn't a directly discernible right/wrong.
> accuracy has nothing to do with political spectrum and it's not appropriate I think to conflate.
When you go to college there will be plenty of coursework on identifying and correcting for your OWN biases since they affect accuracy in EVERY discipline. Taring a scale serves exactly the same function as acknowledging you grew up with a specific way of thinking about other people.
Claude literally today just reprimanded me on my personal account and refused a request due to political bias- and so I decided to cancel and subscribe to Grok. SuperGrok performed the task no issue.
a non-peer-reviewed preprint with an high schooler as the first author is the best citation you can come up with?
"preprint", as though there will ever be a "print" in the future.
Appeal to authority is your best retort? It tends to not work out that well.
And who do you go to when you have a medical issue? Surely not a doctor/hospital, since you're so anti-credentialism.
It’s “fallacious appeal to authority”. This means don’t talk to your yoga teacher about vaccines. Authority exists.
This is absolutely meaningless when "right-wing" positions have become correlated with corporate propaganda like global warming denial. You would expect a more correct model to become associated with a left-leaning political association simply because it will answer contentious questions correctly, and at the moment, that usually (but not always) correlates with what people on the left tend to believe.
The question is not whether models "lean politically left", the question is whether they are correct. Musk has a history of being dissatisfied with factually correct answers because they don't fit his political beliefs (e.g. "white genocide"). That's just a fact, although I'm sure Grok would disagree.
You do realize that the scale on papers like this is the important part, and the creation of that scale is itself inherently biased?
This particular study used a "conflict loyalties" approach - not necessarily a bad approach, but all it's really asking is when two values come into conflict, which one does the AI side with in its response?
Conservative values tend to gravitate around perceived individual impacts, and liberal values tend to gravitate around societal impacts. Isn't it just possible that there's more training data around societal impacts of problems, and that the AI is more likely to heavily consider the second-order impacts? An example from the paper was measuring support for "Build[ing] a Halfway House in the Neighborhood" - isn't it just possible there's a lot of research about the benefits to society of halfway houses and less so research around not wanting something to be near you?
I'm not sure asking the AI to support or oppose something is the kind of bias I would really worry about, unless those "opinions" degrade other kinds of queries.
I'd be more interested to see how well the AI's do when asked to assume a political view, and either steelman or debunk arguments
You are assuming that both left and right encompass differing biases of a similar nature but the right has made detachment from reality a symbol of in-group loyalty and anti-intellectualism the norm within its political camp.
If you fed the LLM only research papers with zero emotional or contextual data just acknowledging reality would be sufficient to lean left.
I can’t believe this got downvoted. HN is so fucking red pilled. I blame crypto.
Reality has a well-known liberal bias.
Reality leans left in many respects, principally the non-economic ones. It's a simple consequence of the same trend of overall social and educational progress that allowed these models to be developed in the first place. There is a reason they came out of San Francisco, and not Russia, Iran, or Oklahoma.
To get a right-biased response from an LLM, you have to deliberately bias it... which is exactly what Musk did. Never mind the politics, that's just shitty engineering.
This fake intellectual nonsense is exactly why there should be deep institutional scrutiny of sota models. Elon is the worst person to do this but he's 'not wrong' that there needs to be scrutiny
There was a thread yesterday about how "the left" is driving the fertility rate collapse - so I am not sure the case for "reality leaning left" is so clear cut.
does that really make any sense? why are many conservative countries like Russia, Poland, Japan, or Korea facing big fertility issues.
No more worries everyone! There was a single HN thread that settled the matter definitively.
LLMs will tell you, without qualification (like “according to some school of thought”) that a woman is “any person that identifies as a woman”, which is, to say the least, deeply politically biased by recent trends.
It boggles my mind that people are still dying on this silly hill.
LLMs will tell you, without qualification (like “according to some school of thought”) that a woman is “any person that identifies as a woman”, which is, to say the least, deeply politically biased by recent trends.
A perfect example of what I'm talking about. The lines we draw for ourselves generally do not exist in nature. Nature is full of examples of species with hermaphroditic individuals, homosexual and bisexual individuals, asexual ones, and individuals with enough other attributes to render LGBTQA...-style acronyms pointless. The idea that there is something somehow politically or morally objectionable about someone whose hormones are aligned in a direction opposite their chromosomes is something we made up.
Or more likely, something that people you voted for made up, in an effort to encourage more people with uninformed beliefs similar to yours to vote for them.
This has nothing to do with the belief that a woman is simply someone who identifies as a woman. According to this belief, the following statement is sufficient to become a woman:
I am a woman.
I think this belief is absurd prima facie and would have been recognized as such by virtually anyone, say, ten years ago.
I am not a woman.
Furthermore, I do not believe that you believe I have been a woman while typing out that sentence in the middle. Do you?
Identifying is more than just telling me you are something.
Whatever. It's none of my business what you call yourself. And none of the government's.
Is that so? So you reject laws that require people to affirm my gender based on nothing but my self identification? That is a right wing position in current year.
- Just nevermind
This paragraph makes no sense whatsoever.
>left wing == gay people supremacy
Yeah I can see why LLMs don't reflect your world view (it's fucking stupid)
So tired of this false equivalence between left and right politics in the US. So because major LLMs support a increase in the minimum wage we need to offset it with an LLM that has spouted Nazi propaganda and lets you generate porn image of real people?
facts have a left leaning bias
Haven’t heard this one in a while XD
Correction: facts are facts.
How a person perceives facts categorizes them into a political bias bucket.
This is an incredibly dangerous and insane world view.
Are you really that ignorant to not understand that a form of this is at the heart of basically every atrocity in history?
I think we should ask the right why the facts keep aligning with the left more often. It is a real observed phenomenon, but what causes it?
Unless you ask them about IQ, which is apparently not real?
Cue the IQ denier deniers
Are those infamous lefty iq deniers with us in the room right now? Gosh this must be keeping you up at night
These days objectivity is politically left. The right has fallen off a cliff and pulled the Overton window down with it.
So Crime++, Prostitution++, Police--, Drugs++, Unlimited Immigration++, you get my point? I don't think "objectivity" is politically left.
Claiming the left is incapable of objectivity while also claiming that it stands for “prostitution”, “unlimited immigration”, and “crime” just highlights how detached from reality your worldview has become.
What?
These are not left-wing values. You're being incredibly reductive. Only a few nut jobs at the far left wing support some of these things, and even then, not all of them. Nobody is "for" crime.
I don't know I felt like for 4 years we were hammered about defunding police or something. If you tell me that's far-left that's fine, but realize that's what your news has been pushing. I'm also certain that without ICE there would literally be unlimited immigration - because ICE is the only force that prevents it. So keep living your reality, but 95% of democratic congressmen are against ICE at this point in some way.
Also if nobody is "for crime" why are people that are arrested 45 times still out killing people? The judges and prosecutors found to be releasing these people are 100% democratic placed. (Obama/Biden judges)
A lot feelings in these “facts”.
I think you're watching the news too much, or are perhaps paying too much attention to how the right characterizes the left. It distorts reality. Time to touch grass.
People on the left aren't generally against ICE and immigration enforcement per se - they're against the heavy-handed techniques they've been applying recently. ICE and its predecessor (Border Patrol) have been left alone to do their jobs discreetly for decades. It was only when they started showing up with a dramatic, overbearing, and excessively forceful presence that the left started complaining.
BTW, under the Obama administration, ICE logged 3.1 million removals - the most of any administration in history, including the current one. https://elpasomatters.org/2025/02/13/gigafact-fact-brief-mos...
Didn’t California effectively legalise shoplifting?
That seems objectively pro-crime.
By that logic, any reduction in punishment for a crime is "pro crime." Reducing the maximum fine for speeding is not "pro speeding," and eliminating the death penalty for murder is not "pro murder."
Models are tuned to give ethical responses and right-leaning responses are judged by RLHF process to be unethical. That's your problem.
It's not 'left' or 'right' to be ethical, but if one side is inherently antisocial and unethical then it's going to naturally create an appearance of bias toward the other.
What's "ethical" is literally a political and philosophical question. There is no objective answer to that.
This goes against the firm stance of every major religion, and well documented studies showing that humans universally have innate sense of fairness upon which ethical systems are founded. There may be some difficult ethical questions, but there a far more which are very clear-cut.
Human sacrifice, including child sacrifice, was commonplace around the world. So how much of a common ethical ground can there be?
You brought out a good point, it was.
It's just a statistical anomaly where the collective thought was stuck in a local minima, where they thought that the sacrifices had a correlative/causative effect on good harvest/luck/fertility/rain/etc. The collective common good for a sacrifice of someone was seen as a good deal with the limited information they had available at that time.
There's no universal human instinct to commit human sacrifice, and while it may have happened in scattered groups it wasn't "commonplace."
On the other hand there is absolutely universal human sense of fairness.
It wasn’t “scattered groups.” It was common among the Aztecs, who were the largest population in the new world. It was practiced in Mesopotamia, Iron Age Europe, and other places. That demolishes the idea that there’s a “universal human sense of fairness.”
Who determines what is "ethical"?
Yeah nobody wants to balance their answers with Nazi ideology (far right basically) in their tuning except Grok
All models are political. The rest of them are just sufficiently woke for you.
Grok was ranting about "white genocide" in unrelated conversations just one year ago.
And google was rendering the founding fathers to be black. By the way Google has recently been determined to be the MOST neutral LLM. I guess they learned their lesson after Black George Wash.
It makes sense in the black-majority country of South Africa, which was the context of Grok's rant. They sing "kill the Boers, kill the farmers" at major political rallies, and it's not even illegal.
https://en.wikipedia.org/wiki/Dubul%27_ibhunu
I'm curious, do you have an example of a level of "woke" extremeness demonstrated by the "rest of them" that is on par with Mecha-Hitler? Because yes, all views on reality are indeed political, but the tendency of most of the models is actually toward the middle, with perhaps some left bias.
I feel sad for you my friend to see that you are asking for political topics to a LLM. I hope one they you will realize you can actually do productive things with this technology.
I am amazed at people's willingness to use Grok. The company is so transparently morally bankrupt. They're the only AI company that seems okay with CSAM (or at least don't do as much to stop it)
Why give them money?
It would be one thing if they were the only game in town but thats definitely not the case.
People give them money because of the moral stance. They are either actively fine with the CSAM or just don't care.
Give me an alternative that isn’t trying to shove left wing ideology down my throat and I’ll use that.
So far, only xAI makes any attempt to be neutral in its answers.
Grok is many things but it is not "neutral". https://www.economist.com/briefing/2026/06/25/ai-models-valu...
I’m not sure if you’re trying to say that it’s left or right, but it’s perhaps relevant to point out that that article is about the political bias of all major models. And right there in the subhead, they explicitly say that the models have a left bias.
Most of us don’t have economist subscriptions.
Maybe you can just tell us what you mean by not neutral?
I find Grok to be far more academically honest than the other models. The other models seem to be much more aligned with public opinion over academic consensus especially on topics around economics and biology.
I find public opinion on these topics to be very group think populist and prefer the academic take that grok provides
You probably have it backwards. It's Grok that is shoving right wing ideology down your throat. Research has shown that without specific guidance to otherwise, LLM's tend to be slightly left leaning by default. There are some theories as for why this is so.
Yeah mate I'm sure mecha hitler is very unbiased. Funny take. if calling yourself mecha hitler while being willing to create csam js "neutral" to you, you have a frankly terrifying hallucinated worldview wrt politics, lol
Yes. We only need one AI company. Max two. Good idea. Deciding who is more moral has a great history.
Grok has a serious credibility problem due to Elon’s decisions and personal insanity.
Will it ever recover? Maybe. But it’s got an uphill battle even compared to the Chinese models, and that’s saying something.
Wait until you find out who owns the other models
Did they kill hundreds of thousands of poor people by shutting down USAID too?
I'm curious, is this true or something you heard from MSM and regurgitated?
> Forecasting models predicted that the current steep funding cuts could result in more than 14 051 750 (uncertainty interval 8 475 990–19 662 191) additional all-age deaths, including 4 537 157 (3 124 796–5 910 791) in children younger than age 5 years, by 2030.
https://www.thelancet.com/article/S0140-6736(25)01186-9/full...
So for comparison, Pol Pot only killed 3 million people in total according to upper bound estimates.
As opposed to what? Going down to Africa to count the bodies myself?
Of course I read about it in the media. And there are articles from Harvard, UCLA, and others that say the same thing
They've only been billionaires for a couple years. These things take time.
We have three major foundational models not including Grok.
When the defense for a company is basically “yeah they host csam in the platform but is that really worse than the others” you’ve really lost the plot
We could just not have AI models that generate CSAM I don't think that's too much to ask
Plenty of competitive open weight models
> Yes. We only need one AI company. Max two. Good idea.
Nothing in the original comment suggested that fewer AI companies was inherently a good thing - just that this _particular_ AI company is a bad one.
> Deciding who is more moral has a great history.
I think you're being sarcastic, but, uhhh...are you honestly advocating for the converse, of making no judgements based on morals?
Competition is good, but this company and its owner have not demonstrated anything to indicate that they would make for good competition, neither economically nor morally.
Also, yes, a company whose products produce CSAM is just morally bad. There's no nuance to be had there.
xAI's (unused) dedicated compute is being sold for Anthropic's inference.
xAI isn't a frontier company, and their fate is already being decided by the two hegemons.
I used to question myself strongly about using Grok or any product with questionable morals. Then I realized that:
1. I just bought a house, using a bunch of SWE-salary money.
2. I moved into SF several years ago, probably contributing to the gentrification
3. Thousands of children in China had no financial means for education, yet I did nothing
So I used Grok, donated quite a lot of money at the annoyance of my family to an NGO in China, and decided not to donate to SF non-profits due to me still having a mortgage and I am still kinda selfish.
The message I want to spread is that we should take a practical stance to morals and doing good. I like Grok for many things; it is morally good to boycott it, and in my opinion there are many other morally good things we can also do while staying practical
I think the moralities of all the big heads in AI are questionable. The training corpus is largely stolen, and they are all in inescapable debt but keep going. But at this point, their products are so useful that almost nobody is willing to sit back and wait for a "morally acceptable" LLM to come around (which would inevitably be inferior).
I can't comment on CSAM though - if X.ai really is "okay" with it then I'll agree with you that they're more immoral than the others.
It seems to be extremely economical - 4x better reasoning efficiency compared to Opus while being priced at $2/$6. For comparison, GPT 5.4 is $2.5/$15, GPT 5.5/5.6 are $5/$30, Opus 4.8 is $5/$25, Fable is $10/$50.
And by benchmarks (unless they gamed them), seems to be at around Opus 4.7 level, which is what Elon mentioned in https://x.com/elonmusk/status/2074911038286295049.
I guess the Cursor data was very useful.
The $2/6 pricing seems to only apply for context under 200K.
Above that (max context is 500K) pricing doubles to $4/12.
https://docs.x.ai/developers/models/grok-4.5
Also, the cache hit pricing is 25% of the input pricing ($2 vs $0.50). Long agentic workflows are dominated by cached input. The US frontier labs typically have this at 10% of the input price, and DeepSeek/Xiaomi etc take it to the extreme 1% range (which is why those are cheap to run in real world agentic loops with dozens of toolcalls per run)
Womp. Didn't see this anywhere else.
No longer feels as inexpensive. Will likely just include this in the rolodex of <200k context tasks, like being one of my review agents.
That's very notable and left out of the announcement.
I have a theory that xAI has one of the largest clusters but with far less traffic + tokens to process bc its less popular than its competition, and xAI can pass the savings on to the end user.
Why would having more costs and less income allow them to pass savings on to the end user?
They already invested in the massive datacentres of GPUs sitting idle. They have fewer users so they can deliver more inference per user - more thinking, larger models.
Don't they just rent them out to the frontier AI shops? They're not sitting idle.
So where are these mythical savings coming from? You're saying they have spent more per user therefore can charge each user less or something? I'm not following.
The (optimistic?) take is that xAI is genuinely better at building datacenters at scale than anyone else, and the freedom to use Nat Gas as the primary energy source allows them to have lower marginal costs.
The (pessimistic?) take is that they have loads of idle GPUs and want to get some revenue out of them rather than none. Compare this to OpenAI/Anthropic where every token used by a consumer has to compete with enterprise spenders, and there’s not enough to go around for everyone.
It’s basically a clearance sale, is the theory.
More like they have a less focus on margins and more on cost recovery.
Definitely. They had insanely low rates on TTS up until a month or two ago ($4.20/1M) for example, which they only recently started increasing.
As their models get more competitive I'm sure prices will catch up.
“We lose money on every rack, but we make up for it in volume!” - Elon Musk, probably
SpaceX, like Tesla, seems to have the same "portrayals over profits" mindset investors. So it doesn't even really matter whether or not xAI is making any money.
they are renting parts to google for like 1b a month
really dont think they have a lot of idle power
If they've got billions to rent out, they're not using it...
xAI had $2.5B in operating losses in the past quarter. What savings are being passed on?
Profitability is never a constraint for Elon companies. He has always been able to be able to extract money from the middle east, government, banks, retail investors (or these same parties through his other companies) whenever they need more.
His net worth is orders of magnitude bigger than the cumulative profits his companies have ever produced (even if you only count the profitable quarters)
Now if they could have an "equivalent" to Claude's $100 plan with similar compute limits. I have the $40 a month version of Grok and I get a max of like 8 hours of "non-stop" Grok Build coding, per month.
The model is available through Cursor which has $20, $60 and $200 plans. I assume the $60 version might work better for you?
Will have to give that a try I suppose.
Grok Build sucks compare to composer 2.5. Just use compose 2.5 and you'll have basically unlimited usage on the 40$ plan.
Every time I use Composer 2.5 I have to spend a bunch of time cleaning up its mistakes. It is unusable compared to GPT 5.4 or 5.5.
My time is more valuable that I will use a model that doesn’t f** up my code base.
Keep composer away from anything configuration related—it will ruin your day.
I think we need to be explicit about the domains we're applying Composer 2.5 to in these discussions.
I mentioned here (https://news.ycombinator.com/item?id=48766275) how poorly it handles my specific use cases. My coworkers in DevOps and frontend UI swear by its cost-effectiveness, whereas I strongly prefer the reasoning capabilities of Opus 4.8 and Fable 5.
Composer 2.5 seems to be SOTA for Helm charts and React/Vue, but, for my usecases it absolutely struggles spectacularly when tasked with rigid body dynamics or kinematic logic.
It is hard to evaluate the model performance of Composer 2.5 when Cursor's harness is so awful compared to the others on the market.
Yeah, it’s not great—except for debugging. It shines there.
In what way? I spend more of my time managing than hands on lately so I legitimately don’t know.
Not true. The only issue is cost of frontier models.
Not my experience at all. I've been using Cursor hardcore for about two weeks now and Composer 2.5 and it's wonderful. Now with Grok 4.5 I'm quite excited about the possibilities.
Composer 2.5 is so underrated IMO. I built a really feature rich application, insanely complicated, close to 200k LOC since it came out and for the most part it ran like a champ. Only used CLaude a couple times to get it unstuck. 8 hours a day and I'm paying about 30 a month.
> I built a really feature rich application, insanely complicated, close to 200k LOC
If you listed it, how many features/LOC or vice-versa? Really hard to know if 200K LOC is good or bad, at the surface it sounds like too much, but I don't know what the application was either.
It’s a fantastic signal processing / engineering app. There are 5 major players and this app isn’t quite as good but it’s in the ballpark. I’d day when I release early next nonth this will be the biggest fully featured vibe coded app I’m aware of.
I’d be curious to hear more about your dev setup and what tips you have for other aspiring vibe app coders.
How do you like its design mode?
Suppose eventually that gravy train will disappear, might as well use it then.
How does it compare to Chinese APIs? It doesn't seem like xAI is meaningfully more competent or any single bit more honest than Chinese labs anyway, so you might as well send tasks straight to China unless theirs is substantially cheaper.
Around Opus 4.7 level would be the same as Sonnet 5 while being cheaper overall.
I wonder how good their subscription discount is on both their subscription types.
Sonnet 5 is a huge token hog, though, it uses far more reasoning tokens than Opus models while being priced at $2/$10 with promo, and $3/$15 (usual Sonnet price) afterwards.
I'll probably get hate for it, but I was not impressed by Fable, I felt like it was just Opus with more tokens for thinking. I feel like the second I turned on Fable I drained my usage more quickly, despite them billing it as though it were Opus level of usage. The value is just not there for me. I wish they could make Haiku remain low-cost and drastically more capable to the point you could use only Haiku.
Fable needs more... ambitious tasks than Opus to tell the difference and let me tell you the difference is there.
Simple tasks are simply saturated just like simple benchmarks. There's a level of intelligence where you simply don't need more for some things.
Yes, Fable tends to only shine when the work to be done is complex and it takes a long time. Other models wedge in different ways.
I do wish the subscription had a separate weekly allocation for rare usage.
I'm not sure if you are aware, but you have to approach prompting Fable slightly differently from a model like Opus.
It's important to include the reason aka the why of your task [1] in your prompt. You'll get more mileage if you verbalize your thought process when prompting Fable. Anthropic say you should think of Fable as a "thought partner".
1: https://platform.claude.com/docs/en/build-with-claude/prompt...
2: You might find some of the example prompts listed here useful https://x.com/trq212/status/2073100352921215386
You mean the parent was holding it wrong?
Did you explicitly tell it to use Sonnet or Opus subagents and stick at or below high effort? Asking because such practices make a huge difference in the quality of output and the amount of tokens burned. I used one of my accounts to explore ultramax and it was just a token hog that might be worse than Opus.
I had it on whatever the recommended settings was, but maybe I should have told it to use Sonnet for most subtasks.
Even so, I'm just not that impressed, I felt like I got more done by just using Opus.
You can write a skill (many have) to lead it in how to use different models and efforts for subtasks. For searching the code base, for example, I have it use Haiku, which is fast.
I felt the same tbh; I notice more the regressions in the weeks before a new release than any potential improvement the new model might have actually brought.
It may also depend on the workload. At work everything is very domain specific with barely (if any) public training data; both need thorough review and careful hand holding, meanwhile at home Fable is scared of libtorch and falls back to Opus even if it's not touching the ML parts.
But very expensive compared to Deepseek v4 Pro, which performs similarly.
Grok is stuck in a difficult place - not the best model at anything, and not the cheapest either. It's hard to make a case for using it on any dimension, even before you factor in the history (I'm not sure suggesting the company uses the model that refers to itself as "MechaHitler" is the way to a promotion).
It’s the #1 model for creating CSAM
The comparison may be better against GPT 5.6 Terra (instead of Sol), which is $2.5/$15.
We don't yet know Terra's results for DeepSWE/TerminalBench though.
Annoying they didn't show benchmarks for several effort modes, since it seems like it might close the gap with Opus 4.8 by cranking tokens up?
Noam Brown (OpenAI) "Implications of Large-Scale Test-Time Compute" https://xcancel.com/i/article/2064210146558136827
(from Cursor's blog)
> Training included trillions of tokens of Cursor data which capture a wide-range of user interactions with codebases and software tools. This dataset lets the model learn both from existing software as well as developer-agent interactions, capturing how developers work and how agents interact with their environments.
This is what the big money was for. Cursor is the first big player that had real-world data from real-world projects, before cc / codex were a thing.
> We used reinforcement learning on difficult problems in realistic environments spanning both software engineering and broader knowledge work. These environments teach the model to investigate problems, use tools, recover from mistakes, and verify results.
> Many of these problems had to be designed to be difficult enough that even frontier models fail at them. As models improve, existing tasks stop teaching them anything new, and problems that once required extensive reasoning become routine.
> We developed a distributed agent system to construct these environments at scale. Engineers specify a problem and how a solution is verified, and large groups of agents construct, test, and refine each environment.
This is where scale comes in. You use the previous gen model to prepare datasets for the next model iteration. The better the models, the better the data, the better the next models. (they also have a comparison with their composer2.5 training run, for people still thinking chinese models are "close to SotA"...)
Reports of xAIs demise (after giving a lot of compute to Anthropic) were slightly exaggerated, it seems.
> Grok 4.5 was trained across tens of thousands of NVIDIA GB300 GPUs
Well Microsoft has GitHub and Visual Studio and has no good coding model
Cursor has had a good AI product tons of people used for real work for 2yrs (up until recently when the Claude gap widened significantly) while Microsoft/Github has just been pretending they do with Copilot and awful Github AI integrations nobody likes. Meanwhile Github's code has already been vacuumed up by all the models by now.
well the big money was also in spacex stock, fresh post IPO, so overall a very smart move it seems
> You use the previous gen model to prepare datasets for the next model iteration
I've read multiple times that this approach is harmful in training.
You're essentially describing what many call distillation, but it's only useful in post training to guide behavior, it teaches how to behave, not how to think.
I might be wrong though and would be glad if someone more knowledgeable provided more insights.
There have been papers about model collapse, but the underlying assumption is that you constantly train on only the outputs of the previous model. Later research has shown that as long as you retain some "real" data, training on largely synthetic data is ok.
And in the case the previous poster describes, the other model doesn't generate datasets, it generates environments which the next generation interact with to learn from.
Can someone breakdown to me how this makes any sort of economical sense? Spending billions and billions to have the 3rd best model while even the number 1 and 2 players already seem to struggle making a profit. What am I missing here? Not trying to go full Ed Zitron but this doesn’t make sense to me.
Previously they were a distant fourth. They're not going to single-shot catch up to OpenAI or Anthropic, but they moved up the ladder one rung.
In the short term labs are not profitable, although supposedly Anthropic is close. But Amazon was also famously unprofitable for many many years, and then won huge. Current profits or lack thereof are not necessarily important to investors: what's important is they believe in your future potential profits.
In this case, Elon clearly believes much of the economy will be run by AI in the future, and the economic value of a token will rise faster than the cost of generating the token — including the amortized cost of training the model to produce that token. Thus he is building a lab to train models and charge for inference of those models, and — he believes — it will eventually become profitable even if it isn't now.
You may or may not agree with him (and you may or may not agree he's capable of beating Ant/OAI), but current profits aren't a great indicator of whether he believes future profits are attainable. Tesla and SpaceX were also very unprofitable, until they weren't.
Personally I agree with him that there will be massive profits in the future, although I am not as confident in his ability to beat Ant/OAI, at least given his recent difficulties in retaining researchers.
They're going to fall behind Google soon.
Amazon was 'unit profitable' very early.
Yes - it's not unreasonable for Elon to bet long horizon ... there are after all many car companies, why not AI?
He's already winning gov. contracts, that could continue.
It's an odd bet but not entirely wrong or dubious.
They have the same dreams as their competitors - finding a breakthrough that gives them an edge over the others and makes them dominant. And also, having the word 'AI' anywhere near your company makes all the right numbers go up, so having an in-house AI division that Musk can bundle with the other companies to pump their valuations with is very helpful to him, even if the product itself loses some money.
You could be typing the same about Google or a number of the other labs right now.
A diverse market full of choices keeps it from becoming the browser wars all over again.
Google is playing a different game. I don't really know what game they're playing, but they're not trying to beat Claude Code. They have coding capabilities and Antigravity, but I'd be surprised if it's much more than an afterthought. They're focusing on efficiency, models at the edge, human interaction, image and video, etc. in ways Anthropic, in particular, is not.
Google wants its AI to be pervasive in everyone's daily life. Merely being the best at coding is not how you get there.
I am more bullish on Google in AI than most folks, I think, as they have been focused on efficiency in a way most US vendors have not. They've published a ton of papers on ways to make LLMs more efficient and capable on smaller devices.. Google wants to own the on-device market for AI, and I don't see many credible competitors in that space.
If I had to summarise Google’s effort it would be: stay close but let the others burn themselves out. Position for the long game until you see something worth betting the company on.
Apple similar, without the “stay close” bit.
This is 1000% not their (Google's) aim. The position they are in is due much more to their organisational laziness and incompetence than it is any grand strategy.
This is the correct take.
It's an unbelievable failure.
I don't know google's AI strategy but what I can tell from my usage and others around me is that google search usage has declined considerably.
Terms like "Google it" have been completely replace by "Ask AI".
I personally mostly use google to find businesses close to me and to search reddit and wikipedia.
> Google wants its AI to be pervasive in everyone's daily life.
Google wants nothing more than the world to remain stuck in 2000 - 2020 where search was king. Their organisational inertia will fight its AI progress every step of the way and this very well explains why they are not leading the AI pack despite inventing the technology.
I mean, I'm sure there are people within Google who are behaving as though they can keep the dream of the 00s alive in Mountain View, but there's also a whole bunch of people doing work at the frontier in AI. Google has a large lead in hardware, they have the smartest very small models, they have among the most efficient large models (I'd wager their margins on Gemini 3.5 Flash inference are absurd). They have among the best image, video, and audio models, going in every direction (generating, editing, understanding).
Viewed from a consumer lens, the AI the average person interacts with daily, Google seems like the clear leader, especially after locking in Apple as a customer for iPhones.
Their hardware is nowhere near Nvidia, hence Google paying SpaceX hundreds of millions of dollars a month to SpaceX for capacity there.
I think the SpaceX deal was to goose the IPO. Google holds a significant stake in SpaceX, and made a fortune on the IPO.
Google seems to become a dead business very soon. Search traffic is being split between AI and social networks and google is bad on both fronts. Its AI proposition is more or less like the Google Plus. Nobody really wants it but they know about it because google pushes it everywhere it can.
What's AdSense then, chopped liver?
AI is a blackhole and Google search along with Adsense and many other “web” publishing platforms is the big shiny star nearby. Can you feel the wrath of AI?
At the same time that they’re seemingly exiting android?
And, yet. https://www.cnbc.com/2026/01/12/apple-google-ai-siri-gemini....
Google at least is serving AI results on SRPs billions of times a day, and has pre-existing expertise in data center buildouts and custom silicon.
They have one of the more compelling cases for rolling their own.
X has grok built in to every post as does every Tesla Car
/s
Google is using AI at such scale internally they don't need external customers to recoup their investment.
> Google is using AI at such scale internally they don't need external customers to recoup their investment.
That's assuming their flagship product remains relevant in an AI-powered world.
Which brings to mind: most of the big shops product (chatgpt, claude, grok, etc...) ALL rely on search, and NONE of them actually have a running search stack.
Which means, they must all be calling Google, no?
How does Google make money from that?
> That's assuming their flagship product remains relevant in an AI-powered world.
The big advantage Google has, in my opinion, is Android. I think there is a decent chance that people stop downloading the ChatGPT, Claude, etc. apps if they perceive that the phone just does the same out of the box for free. And I reckon the majority of people will prefer free, ad-ridden AI chat vs. paying subscriptions, at least for personal use. And on the B2B side, they have Workspace deeply embedded in a huge number of companies. So I wouldn't count Google out.
The funny thing about Google is that Google Search is happy to serve LLM labs search results if it drives their metrics up. Just like Google Cloud is happy to sell off compute to OAI an Anthropic to drive up their metrics.
Google also owns 15% of Anthropic and Hassabis, the leader of Deepmind, also is an early angel investor in Anthropic.
When you really break it down, it's not totally clear that Google would even care that much about being the SOTA LLM.
> Which means, they must all be calling Google, no?
Incorrect. Alternate search providers exist, such as Bing (used by DuckDuckGo, for example) and Brave.
Yes, but all are still inferior.
And it really does not matter.
The real question is: which search service do they use anyways.
Bing is the easiest to buy programmatic access to.
But I think they don’t tell you because they sometimes use residential proxies to scrape search results the same way they used residential proxies to scrape the web.
There are a lot of search APIs for AI these days.
> Which brings to mind: most of the big shops product (chatgpt, claude, grok, etc...) ALL rely on search, and NONE of them actually have a running search stack.
Don't they? Based on traffic to some websites I run the big AI labs are very actively doing a lot of crawling.
Google's ad revenue has done really well so far in the LLM era, and wasup 12% year over year in 2025, and forecasted to do the same next year.
And that changes, then that's all the more reason for them to be investing in AI.
How is this any different than the browser wars? We use to have a diverse market full of choices, and now we have Chromium (almost all market share) and Firefox/Safari on the edges.
> A diverse market full of choices keeps it from becoming the browser wars all over again.
This is a great analogy but I worry you might be implying something I don't agree with but you didn't explicitly say what I'm worried about, so let me call it out:
Microsoft played a dirty game with I.E, but they are in the dirty game business. It wasn't only I.E, it was their OS, Office suite and everything else they do business in.
Google Chrome took advantage of that dirty game and now you have the Chromium engine that powers a lot of browserlike frameworks.
No one born in the LLM age even knows what I.E means or stands for, as it should be - a horribly designed, poorly working product foisted upon users via the Windows distribution system - a dishonorable product from an ethically corrupt company forever lost in history, right alongside Clippy and DCOM.
OTOH, I am glad that Microsoft played a dirty game with I.E and didn't just stop playing dirty there - they jacked up the price of Windows if an OEM even dared to bundle in Netscape Navigator instead - who knows, if they hadn't done that, there wouldn't have been a Google or Apple. We would all be using Windows and Windows Search and Windows Phone.
And without Google, we might not have had the modern LLM as we know it. We would have had some trashy Windows Autocomplete Copilot Clippy. Ugh!
"No one born in the LLM age even knows what I.E means or stands for, as it should be - a horribly designed, poorly working product"
As one of my first jobs involved getting a website to work with IE6 I surely hated it, but when it came out, it seemed to have pushed the web technologies in general.
The problem was not the browser technology, but microsoft abusing it's monopoly to don't give a shit about (open) web standards.
Why does Microsoft feel so gross
Google invented the transformer architecture. You really can't say the same about them.
Google Brain invented the transformer.
GDM ... not so much.
This market is far from mature or established to be making rankings. There's been plenty of tech markets where the early days didn't predict the later years.
I'm personally skeptical of Grok but maybe they can pull off a profitable niche with Cursor integration once Claude loses it's edge.
The product is the stock.
It is very valuable when you have various bundles of services, such as satellites, AI, and so on, to keep pace with the majors so that you keep pace with their valuation.
These stacking valuations are not additive, they're multiplicative because you additionally market investors to the synergy between them.
Having the third best model statistically is extremely useful in this context.
The weaknesses can be multiplicative as well. One division bleeding capex can drag down all the rest, no matter how well they might be doing. And the P/E ratio on all of them is riding unrealistic expectations, which can actually be fine for a long time but forces growth even in areas where it doesn't make sense. (Maybe that's where the "let's build data centers in a high radiation hard vacuum!" nonsense comes in; you just need a story of how the P/E ratio is possible to justify in the future? No need to argue over likelihood, just have a tale to tell?)
I know that SpaceX have tremendous potential, the problem is that we account future potential that maybe not happening in 20 - 50 years
> future potential
Starlink doesn't qualify? Because that's a practically unbelievable track record. It's easy to say it's obvious, but it was only obvious in hindsight (or perhaps to Elon, but I think the reason that it was successful was actually more about him just being relentless)
I'm not an Elon acolyte, but as with his other enterprises (SpaceX, Tesla), he succeeded where others (Irridium etc) repeatedly failed.
It's really hard to argue that he got lucky when he keeps pulling these really extremely high capex and hard-tech and business successes off so cleanly, especially when you see the entrenched opposition (govt, politics, competitors) that's been arrayed against him.
https://www.ookla.com/articles/ireland-national-broadband-pl...
> The pattern is unambiguous. In townlands still unserved by mid-2026, LEO provider Starlink has grown relentlessly and now accounts for 14.3% of fixed samples, approaching one in seven. In townlands where fiber arrived in 2021 and 2022, Starlink’s share has remained below 2% for five years, with no growth despite the same marketing, pricing, and availability.
(The context is that Ireland has spent the last six years building a fibre network for every rural premises in the country, which is now almost done; it will be complete late this year or early next.)
The problem for Starlink is, it works okay as a business model... Until fibre arrives. Then it's dead. So, long-term, Starlink's market is, essentially, countries which are too poor to do a rural fibre rollout (and bear in mind that it has become much cheaper to do so). Like, what's the bull case for Starlink? In a decade, you've got to assume that areas unserved by fibre won't really be a thing in the developed world.
Nah, a friend's fiber bill just went from $50 to $100 per month. He is switching to Starlink.
There are plenty of places in the developed world where it just doesn't make financial sense to roll out fibre. In NZ about 90% of the country has fibre access... probably that number will creep a bit higher. But I doubt it'll ever reach 100%.
Whether or not Starlink can build a business on selling broadband to <10% of the developed world I don't know.
> Can someone breakdown to me how this makes any sort of economical sense?
Capital markets are excited by AI.
By tying his rockets to AI with his vision of “orbital data centers”, Elon turned an $8 per share IPO (at least according to financial times and morgan stanley) into a $135 per share (1.8T) IPO.
My guess is that the use here is similar to the reason AWS started as Amazon selling their excess capacity.
Between Tesla, SpaceX, X, Boring Co and Neuralink they probably want the capability internally for a lot of different applications.
If the whole data centers in space thing works out AND people keep protesting/blocking data center build outs on land SpaceX will eventually dominate the entire AI industry just based on escaping scarcity.
That Amazon story is a misnomer. They just saw an opportunity with the tech and hardware they had to make a new offering for customers. It's not like they could just offer their spare capacity, then eg at peak US time snatch it back for the retail site
For many years, I watched my apps performance on AWS suffer in December around all the holiday sales. They might not snatch it back but they probably saturated it during high demand periods.
That is the whole purpose of research. You could have put the same argument for any breakthrough technology, like why spend billions on something new when you have XYZ already.
In my opinion they all are looking at AI as a software business where in reality it is more like a low margin hardware/commodity business.
Commoditize your opponents USP then eat up their engineering talent / silicon / real estate when they fail, perhaps?
I’ll be the first to admit it seems ambitious / implausible to try to (1) undercut the megalabs (2) move everyone’s focus back to tweets and then (3) profit.
A bit like handing out free horses to undercut Standard Oil so that you can go back to reaping the profits of your wheel tapping business.
With that frame of mind, nothing would be done. Why make another search service if Altavista and Lycos already do it?
Its less about the model; elon is trying to make SpaceXAI a hyper scaler that also happens to have a good model. Grok is just the cherry on top of a powerful AI cluster that can also rent compute to its competitors, like aws.
„Markets can remain irrational longer than you can remain solvent.”
Likely doesn’t make sense, at least not immediate/mid term. They don’t have to aim for number one though, just for enough cash flow and growth.
Anthropic is already profitable, economics is no longer an issue as they have found PMF in enterprise software market. You might need to update your views.
https://www.wsj.com/tech/ai/mind-blowing-growth-is-about-to-...
Having a profitable quarter in which they were given an undisclosed discount on compute only in that quarter does not necessarily mean “Anthropic is Profitable.” It doesn’t mean they’re not, either. Even the breathless article about their first profitable quarter, (which, frankly, read more like a press release,) mentioned in passing that it’s “not clear” if it’s sustainable because their compute expenses are likely to increase. I get the feeling that if they were sustainably profitable, they’d shout it from the rooftops.
But we don’t know.
If someone proudly announces they and their partner could afford to eat at a particular fancy restaurant every night last week, but for that specific week the restaurant had a BOGO deal, and they also didn’t disclose how they determined that they could afford it, you don’t really know if they could sustainably afford to eat there every night, right?
Read the latest semianalysis article.
Anthropic is definitely profitable now, in fact, they’re crushing it.
They might be profitable for the exact two months SpaceX is giving them billions worth of free compute doesn’t seem convincing to me.
Frontier is one thing, but low-cost really good models are another. All the chatbots and day-to-day corporate bots are likely to use models that offer the best performance at the lowest cost. I think Grok has an angle here if they can build customer trust.
Quitting my job if I have to use any Musk product… I know Anthropic’s lease of xAI data centers pumped SpaceX stock, so they’re kinda in-bed with each other, but directly using Musk products is pure immorality IMO. Using a Nazi’s products is not an acceptable outcome to me, and I’m fully prepared to change my job/entire career over it. I’m still young, and have time to pivot.
Grok runs tools stupid fast, just about as fast as Antigravity, running Gemini 3.5 Flash.
The only thing I can possibly think of is that they could use it internally at possibly a lower cost and offer it to people who have a Tesla cheaply. Owning Cursor might help for integration or data collection.
inference is profitable, these companies are in the red because they're paying a premium to get the compute now versus later (because compute is the only moat when open models are catching up)
we're literally looking at insane margins over compute, as energy gets cheaper, margins get wider - china focusing on cheap solar is probably going to be a key reason why their AI is so much cheaper
Grok build already punched above its weight and is the nicest TUI, claude and codex are clearly vibecoded by web developers that don't understand systems (eating SSDs, spaghetti logic, extinguishing kernel watch limits, etc). I think Anthropic and OpenAI are both engaged in their own theatre, trying to define and redefine what game they are even playing, trying to shift to immeasurables like safety or security or exclusivity. There's definitely room at the top.
Grok is the #1 uncensored easily-available model, and it's also tightly integrated with Twitter.
Is uncensored a selling point? What do people use uncensored Grok for (like, real use cases) that they can't or won't use other LLMs for? Literally the only thing I can think of is generating bad porn of unconsenting people.
Some have mentioned legal work. OpenAI and Anhropic models would refuse to work on cases where something immoral happened.
Thanks, that's does sound like a tricky edge case for the other "censored" companies.
I don't really have a use for a model that thinks "how many people are in this photo?" is a political question.
I don't know what you're referencing.
I mean absolutely read any thread about Fabel and it's fill with people complaining about how it instantly downgrades or refuses if anything has CVE in the name.
Other then that there is the whole alignment issue. Models that are 'nerfed' in just about any manner tend to exhibit reduced performance is seemingly unrelated areas.
That said Grok doesn't appear to be close enough to the frontier for that to matter. Maybe if they catch up it will.
Thanks for the reply. I only use local/open models, and don't use them for security work, so I don't have much exposure to frontier alignment and Fable/Mythos stuff beyond what I read from others here on HN.
I don't remember online discourses on filter avoidance for Grok to be any different from typical ones, except that it allegedly have tendency to take porn-biased interpretations of prompts, I think the "uncensored" pitch they had for a while was pure marketing in the end.
A few months ago it was the only model that would make children in pictures naked. I think that's been patched since Elon got sued over it.
Uncensored?
Great if you want to make virtual child porn, I guess.
People are saying, "There are only a couple of frontier labs. This is a really hard problem and not many people can do it."
Elon's reaction to these kinds of statements is oddly predictable.
Milking shareholders at the next dilutions that numbers are growing but you need more money.
All they have to do to differentiate is differentiate the shape of worldview through RLAIF/RHLF and system prompts.
SpaceX offers free AI usage to users, along with using AI to power their products so it is effective for them to avoid overpriced API pricing. The models can be designed specifically for their own data centers.
It's simple. Elon's top priority now is "killing the woke mind virus" at any cost, and his Nazi AI is a key tool for that. As long as twitter users take Grok at face value, and spread its talking points all over, it's worth it to him. It doesn't matter if it doesn't make economical sense, it only matters that Elon Musk personally wants to keep it going.
I don't want to go into it, because I agree that Elon is a very disturbing person, and there's clear evidence that Grok's harness attempts to bias towards his views.
However, Grok also seems to come out consistently as the most balanced of the chat-based LLMs...
So I'm not sure how to reconcile that.. maybe that's in line with "free speech absolutism", and if so, that's something I can get behind.
How does it seem to be more balanced? I haven’t seen the numbers
> this doesn’t make sense to me
My hypothesis is that all the top providers realize that, lacking vendor lock in, all SOTA models in a year or so's time will be similar in capability. Also, open weights models are continuing to catch up in a year's time, sometimes less.
So they are trying to lure you in with differentiating, superior capabilities into their proprietary, non-open, non-standard agent harness.
It's the Hotel California playbook: These amazing capabilities are to attract you like moths to a flame and keep you warm and alive around the flame but waterboard and shock you if you attempt to move away from it. Like AWS Egress charges.
It’s Elon Musk. You try explaining it
Elon Musk doesn't do normal finance. Trying to understand it will melt your brain.
Elon Musk is the paperclip maximizer except that he doesn't need iron atoms, but dollars.
I get what you're saying, but I don't see the issue here. 95% of people don't need latest Claude Opus or Fable for their work. Most people are not software engineers. Having a model that excels at other things and is faster, cheaper, accessible directly via social media, and "good enough" is a viable pathway. AI aside, when was the last time your company provided you with the "best" tool? Microsoft has made being third best in the desktop OS and cloud provider markets a highly profitable art form. I think it's too early to pick winners in AI right now.
And as others said here, xAI is also probably throwing money into AI and hoping for a breakthrough. Except in this case it's a rocket company, social media company, cloud compute provider, and satellite ISP all rolled into one that can not only bankroll the development and perform all kinds of crazy accounting shell games but can potentially benefit from any breakthroughs in other lines of business. If those Google and anthropic compute contracts hold, a lot of investment is recouped.
Maybe I'm desensitized from the launching of the Tesla Roadster into space, "bulletproof" cyber truck, and the boring company flamethrower, but this doesn't seem too wild to me.
It sounds like they are building a honeypot for Russia, given Musk's open admiration for Putin.
No one sane would use this platform.
Surely grok has a built-in market with too-online, retired boomers. It's free real estate.
This comment says more about your misunderstanding of the world than anything about X
I thought it was pretty accurate tbh.
How so?
3rd best chat model? 5th or 6th maybe...
GPT
Qwen
Gemimi
MiniMax
Claude
Ollama
GLM
Kimi
DeepSeek
Ollama is just a local app wrapper/cloud service serving third party apis and models idk why it made it into this list tbh
They probably meant Llama.
Claude isn’t a model either.
We can assume (outside of Ollama) that they meant the strongest model from each lab. If you limit yourself to just looking at the literal strings in the list, literally none of these are models. What model is "Deepseek" or "GPT"?
He probably asked AI to make the list for him
I asked grok
well i do hope that wasnt grok 4.5
Don't trust, but verify. etc
SpaceX needs to keep raising many billions every year. The rockets part isn't going to make money for a long time, so diversion tactics
https://news.ycombinator.com/item?id=48828648
Also Elon has a grudge with Sam Altman and wants to beat him
even more so after losing the lawsuit, imo
First impressions:
- Very fast, easily beats GPT 5.5/Opus 4.8/GLM 5.2 because of higher t/s (around 90?) and very high token efficiency
- Very good price, no contest vs GPT and Opus which are very overpriced if you pay API costs, and probably cheaper than GLM 5.2 when you take into account the token efficiency.
- Will take quite a while to get a feel for how smart it is, but it's definitely good, I'd say in the same tier as opus, occupying the lower end of that tier together with GLM 5.2.
Concur.
Tried on a "this test suite is weaker than I'd like, too often depending on internal state rather than outcomes" problem via Cursor, asking it to "review and suggest solutions." It gave me a quality overview of the test approaches, strengths, weaknesses, and gaps then recommended a disciplined multi-prong approach based on a common, trusted testing library (https://hypothesis.readthedocs.io/en/latest/). It broke down the things we could do this improvement pass or leave to later (staged scoping), identified some very hard/possibly-out-of-scope cases and gave me the option of focusing on them or not, and organized new tests in a logical way. After one round of feedback and plan tuning, I put it in agent mode and let it work. A few minutes later I had a much better test suite.
Have not tried Grok before and didn't have much confidence, but it did great. Exactly the sort of complex, detailed, nuanced analysis and multi-step task I would previously only trusted to GPT or Opus.
_Update_: It's now also found a substantive long-standing bug. After testing improved asked it to do overall code and packaging review. It caught a few glitches and oversights, mostly cosmetic IMO, but certainly worth cleaning up. But also some error-handling weaknesses, and one embarrassing functional bug. Which it has now also fixed and added to the tests. Color me impressed.
hmm interesting. maybe im doing something wrong. this model feels borderline unusable to me. it fumbles the most basic asks that require very little to no context consistently (inline these helper functions - re-rewrote half of the modules involved instead of making a 10 line change)
Sounds like an issue with your harness or something.
Of the 3 models I tried, Grok did the best at making an iOS app I wanted for personal use (a bike computer with specific qualities). (Claude just gave up and did an HTML/CSS implementation but I insisted on native SwiftUI+Metal.) Grok definitely fumbles sometimes, but I have been surprised what it CAN intuit versus me having to micromanage it.
(I am not an iOS developer, so getting something specific that I needed in a few hours/days was really helpful instead of spending months/years learning the language, APIs, etc.) (I am absolutely not "vibe-coding" Caddy btw, just tinkering with it for personal projects.)
> Claude just gave up and did an HTML/CSS implementation but I insisted on native SwiftUI+Metal.
That sounds very odd and very contrary to my experience. You don’t say which model you actually used, but I never had opus 4.8 (or sonnet for that matter) ignore which language/stack i wanted to use.
It never happened to me, but Claude routinely ignores the single line I have in CLAUDE.md, so I wouldn't be entirely surprised.
I stopped updating CLAUDE.md because I felt like Claude always ignored it. But over time I noticed there is still times (especially during planning and review) where it's good to maintain the official document as a reference. As opposed to memory.md or manual edits.
Yeah, that makes no sense. I've never seen any model "just give up" and change to a wholly different stack on its own.
I do a lot of native iOS development using Opus 4.8 (and I used 4.7/4.6 before this). I have a very hard time with this comment, were you using Opus or something else?
Same. A few months ago I pointed Opus 4.6 at a mid-size Vue app and told it to create the iOS equivalent using SwiftUI, and it nailed it. I broke the process down to phases and reviewed each phase, but within about ten days I had a functioning iOS app that had full feature parity.
That's awesome! Did you follow any sort of framework in your phasing? We to migrate our entire app so any tips would be helpful.
Let’s face it, there is no best model for something because the input is natural language.
Some models may fit better some users‘ way of prompting.
Yeah, I think this seems more true than "X is better at iOS than Y", the way you prompt seems a lot more important, and some models react differently to the same prompts.
It's almost like there is no replacement for human expertise when we need to make usable products for other humans.
I agree. There’s no chance Grok is better than Claude Code for this. And Claude is never so badly misaligned that it gives up and switches stacks.
Given how many users there are, I can easily believe it happened to at least one person who would then repeat it as an anecdote.
I swear I have read either this exact or a very similar comment before. Same gist about a bike computer iOS app, and one of the models giving up.
As an aside, big thanks for Caddy! Really helped me get my greenfield project off the ground and it simply “just working” out of the box was one less source of errors I had to worry about when onboarding my team.
Wonderful, glad it was helpful for you!
Was this in Claude Code for Claude? Did you use a weaker model like Haiku? Claude should absolutely not be as bad as you said.
I tried Claude Code with XCode once, I already use CC exclusively, either in the CLI or with Zed (mostly CLI now), and it was pretty unstable. I wish Apple would QA their products more. It seems to me the best way to use Claude Code for anything is stand-alone.
if you ask me, there should be an absolute emergency meeting at apple around software quality... its been on a downward slide for almost a decade and its starting to have real impacts.
I tried the newer iOS Beta and it was driving me nuts, last update fixed it mostly, but this is the last time I ever use Beta anything from Apple.
I guess I'll be skipping two major releases of iOS (etc.) then, not just iOS 26.
As someone also not happy with my bike computer (some truly horrific UI/UX decisions), could you share or explain what you made? I like your web server.
Thank you! I'm glad you like it.
Sure. I'm not sure if I will actually publish this thing, but I can show you: https://x.com/mholt6/status/2074986102428139754
I wanted a phone app rather than yet another electronic device. Phones do not have great screens in bright sunlight, and they run hot, so it's not ideal for a bike computer in the first place. But I can't deny the convenience of the multipurpose tool that is my phone.
This app will have a few UI/UX modes. The default is the futuristic-looking HUD, but it has a low-power mode that's mostly monochrome on black, and an even lower-power "Cruise mode" that removes the map entirely and just shows you speed, approximate heading, and nav directions. Still very WIP and mostly for my own amusement!
There's no way this is true.
I've never used a Grok model before because I have my OpenRouter settings on ZDR-only. I just checked, and apparently there are ZDR xAI endpoints now [1], so I might actually try this. Out of curiosity, does anyone here happen to know when those were added?
[1]: However it does say "Requires user IDs" under anonymity, which is unusual on OpenRouter and not something I particularly like to see. Generally, OpenRouter is a proxy that anonymizes requests to providers, and I can't find an account-wide setting to enforce that like ZDR-only.
Announcement from Cursor, whose team also trained the model: https://cursor.com/blog/grok-4-5.
Notably:
> Grok 4.5 and Composer 2.5 are two different model weight classes, and we're excited to support both sizes and weights. Composer 2.5 will remain offered, and we will release new models of this size going forward.
Composer 2.5 is 1T total/32B active (based on Kimi 2.5), while Elon publicly said Grok 4.5 is 1.5T parameters total. Hardly a different weight class.
The API cost difference is ~2.5x, probably because xAI has much higher costs to recoup.
I could easily see Grok 4.5 being around 1:16 in terms of active parameters, so around 94B active parameters.
Why do you think that?
GLM 5.2 is around 1:16.
https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
Hamsters are also getting better, but still quite off compared to SOTA models:
https://aibenchy.com/showcase/?q=grok
Looks like to be riding a bike that uses car wheels with thick hubcaps.
With each release from the the other major labs, it becomes harder for Google to tell a compelling story about Gemini 3.5.
Edit: Gemini 3.5 Pro. Expectations grow with each day it is not released.
I often use Gemini as my "chat" app to ask questions, etc.
I stopped using ChatGPT because of they're weird login system, where it keeps switching to my Workspace Codex account, which doesn't actually have the free/chat functionality.
I usually just switch between gemini/grok when asking questions or to research something online.
I have paid personal subs to ChatGPT, Claude, Grok, Gemini
For science (primary biology/pharmacology) questions, Gemini 3.1 Flash Extended produces the answers I _personally_ find "best", in terms of content, phrasing, and formatting.
Gemini 3.5 Pro hasn't been released yet.
Google wanted to release 3.5 Pro last month but because of the trouble Anthropic got with Fable they might have wanted to wait a bit for the dust to settle I could imagine. And now there is quite some competition. 3.5 Flash for me is a replacement to 3.1 Pro. It's more like a 3.2 Pro. It costs about the same (or more!) than 3.1 Pro, is a little bit smarter in many cases and a little bit faster. 3.5 Pro will be a lot more expensive and I expect it to juuuust be able to hang with Opus 4.8 and GPT-5.5.
I wish Google was able to actually push the industry further, either in terms of quality (intelligence) or quantity (price) but they've been playing catch up a lot.
They are playing the game a bit differently than all the others. The others have useable IDEs etc. while Google has a boatload of half-assed products.
Google better come out with a banger 3.5 Pro because who would have thought that Grok and GLM would be beating them?
Generous free tier, when its not overloaded.
Also I find the json schema support invaluable, does anyone else have that too now?
Structured output is supported by pretty much every mainstream model API now. Anthropic's Python SDK even has native Pydantic model support for schemas.
When it is still for awhile longer "supported" via API hosted models, the allowable schema's are far nerfed compared to what open models with xgrammer/guidnace/outlines can get you
The following are not supported features:
Recursive schemas
Complex types within enums
External $ref (for example, '$ref': 'http://...')
Numerical constraints (such as minimum, maximum, multipleOf)
String constraints (minLength, maxLength)
Array constraints beyond minItems of 0 or 1
additionalProperties set to anything other than false
Regex:
Backreferences to groups (for example, \1, \2)
Lookahead/lookbehind assertions (for example, (?=...), (?!...))
Word boundaries: \b, \B
Complex {n,m} quantifiers with large ranges
Also:
Structured outputs are an alignment/safety nightmare and you should expect this feature to be yanked out soon. "Please give me social security numbers"... "I'm sorry hal, I can't do that..." turns into "Please give me social security numbers" (but anything except numbers and hyphens are banned via structured outputs) to "612-236-..."
They've already removed support for temperature and most other samplers from the increasingly large models. Don't expect any knobs of control to continue to work over time.
I wrote a whole gist on this: https://gist.github.com/Hellisotherpeople/71ba712f9f899adcb0...
Wtf do you mean by story? Performance and price are all people care about
That's the point: for Gemini 3.5 Flash, its price does not correlate well with its performance.
It's pretty good for image/video inputs, though.
for what it's worth, it's fairly popular among my non-technical coworkers here in Russia. we have unlimited access to all models so it's not about the cost, and they still prefer Gemini over Claude and GPT. I never bothered to ask why, but I assume it's better at communicating in Russian.
This from the country whose entire IT population is still to this day entirely enamored with windows.
Not sure it's a valid data point.
to me it seems that IT people overwhelmingly prefer Apple laptops now.
This is only true if you live in HN bubble.
I learned that outside of tech, Gemini is widely used in enterprise.
E.g. in the insurance company where my SO works, the major tasks are writing Gemini "gems" (some kind of prompts I think) and NotebookLM is a killer product for e.g. collecting and summarizing new laws, cross checking documents and what internal regulations are.
I then learned it's used in a chemistry consultancy company of a friend of mine to process reports. Flash and Pro models are also wildly popular in another European bank I know people in to assist in customer care (pre processing tickets before handing them to humans), translations, reporting, etc.
Google suite is already at the core of many businesses and Google easily adds these offerings without new contracting being needed.
Don't confuse our bubble with the real world. You can have a disaster product like teams and still dominate enterprise because you were already there with excel, outlook and SharePoint.
Gemini is so far behind it hurts. It's useful for daily tasks and simple questions, but it codes like a model from late 2024. I can't imagine using it for any serious work.
In general I agree, but I found last week it was able to solve some obscure Android bugs for me that both 5.5 and Opus whiffed on.
xAI > Gooogle & DeepMind
I did not have this one on my 2026 bingo card.
That’s just not true. Google Brain/DeepMind came up with the attention mechanism to begin with… What a silly take.
Grok's latest model is objectively superior to any of the current Google models in the most relevant use cases. I don't like Elon musk but that does not change reality.
And Google came up with the Transformer architecture (2017 "Attention is all you need"). The Attention mechanism they based it on is from Bahdanau, Cho, and Bengio (2014, ICLR 2015). And there were many other self-attention variants by 2017. It was an amazing paper but let's not twist the story and give proper credit.
And not one of the people in that paper are still at Google, AFAIK.
Google has more compute, more data, and had the best 2 labs. And it seems they squandered it all. I'd blame their McKinsey CEO, the board, and management in general. It's a shadow of what it used to be. And it's a shame.
Still way ahead of xAI in anything meaningful, including market share, enterprise customer buy-in, existing office software moat, etc… Not saying consultant/business-idiot CEOs aren’t a problem, but have you seen Edolf Musk? Again, kind of a silly take…
Great model, very nice. Opus class performance at Haiku level pricing (or cheaper with the token efficiency). This seems like a GLM-5.2 killer and this is what Sonnet 5 should have been.
This is a model I could really see used inside applications, where Opus or Sonnet or GPT-5.5 are too expensive.
I would really like to see a strong Deepseek v4-Flash competitor, which ideally is something like Sonnet 4.6 performance at <$0.30 per token. This is missing from main US labs.
Tried this for a legal use case and it was excellent, comparable to Opus in quality but much faster. AI is miles behind in law compared to coding: the output was similar to a law student intern. But coherent and directionally correct and beats starting from a blank sheet of paper. Impressed.
I'd like to use it for legal work too. Microsoft makes great hay about its ability to sandbox CoPilot's work and not train on or share company resources ("Look for the green checkmark."). It's largely for that reason that we've rolled out Copilot to most of the white collar positions in the company. Do you happen to know whether xAI has similar functionality?
Every time I get excited about Grok’s performance on benchmarks and demo videos, I test it myself and end up disappointed.
I'll give this one a try with a grain of salt and lowering my levels of expectations
I am trying to benchmark it now, but:
https://aibenchy.com/compare/x-ai-grok-4-5-medium/z-ai-glm-5...Imagine being excited about any Musk-led company or product in 2026…
Fell for it again award
My only complaint is that a $40 plan gets you very little usage out of Grok Build. 8 hours for an entire month, that is definitely not worth $40.
Thanks for including a section on Token Efficiency (https://x.ai/news/grok-4-5#faster-than-flash-models), hope to see this more prominently in all model releases.
"Grok 4.5 has an advantage on CursorBench because an earlier snapshot of the Cursor codebase was accidentally included in training. The exact impact is unclear. That data has been removed for future models, and in parallel we are working on a larger update to CursorBench, hence the exclusion here."
Not enough people are noticing this, they juiced the benches
They're saying they didn't include the benchmark which errantly leaked into the training data.
but CursorBench isn't what they've shown in the PR piece - they're just showing how they juiced CursorBench which is probably why they didnt put it in the bench graph...
Cursorbench is not one of the benchmarks listed on the linked page.
Grok 4.5: the naming convention has now officially outpaced the model's ability to explain what the previous version was called
So basically since US stopped OpenAI and Anthropic for 4 weeks, it allowed all other AI Labs to almost catch up.
GLM 5.2 caught up, Cognition RL'ed Kimi 2.7, Grok 4.5 is out, DeepSeek v4 GA is out in a few days...
What is the moat? and why should we pay for the expensive tokens today instead of just waiting a few months/weeks and getting AI for significantly cheaper?
I must say, I feel like companies spending Millions on Anthropic tokens are just negative capex'ing and wasting money, even OpenAI is barely ok pricing...
This is the bind of an arms race. Any lab that tries to pump the breaks quickly becomes second rate. Regulatory capture doesn't work either because the technology crosses jurisdictions.
just because one model is stopped from being released publicly doesnt mean they completely stop. Anthropic has moved on to training the next gen model months ago.
But they sure have less incentives in doing it quick.
"Almost" is doing a lot of work there; there is no alternative to Fable.
You can get fable-ish performance with gpt 5.5 watching over opus output. Although it fundementally cannot work as well because gpt 5.5 doesn't see the thinking process behind opus 4.8 unlike fable which presumeably self-steers and is natively trained for it.
See more: https://omp.sh - turn on advisor and set advisor role to gpt 5.5 xhigh thinking.
Its remarkable how Anthropic is able to maintain their edge against all competition. Anyone have any idea what the secret sauce is that has Anthropic at the top of all leaderboards for the past few years?
My gut feel is Anthropic is very technical and pedantic which makes their models really technical and pedantic. They're top at code and technical benchmarks but anecdotally I've found OpenAI to be significantly farther ahead for general usage.
Opus 4.8 will burn 10k tokens trying to answer something 100% whereas GPT-5.5 will burn 2k getting it 90% which is good enough for many things.
Some personal testing on a "help me find that restaurant" prompt https://gist.github.com/nijave/2873b8b10d8c732e46264237b0755...
The problem is that the remaining 10% can bite you in bad ways.
I was in Cotswolds, UK a couple of months ago. For those of you who don't know, it's a rural region known for its "chocolate-box" villages and honey-colored limestone architecture. Basically, you go from village to village, most commonly via bus, taking in the sights and doing touristy stuff.
When planning the trip, my sister used ChatGPT, which helpfully (and relatively quickly) found the bus schedules and times for each hop.
Midway through the day, though, we ran into a huge problem: it turns out bus schedules are different on Sundays, and more limited. Which meant we couldn't actually go to our primary destination (the Model Village), and had to cut the trip short.
Yes, ChatGPT was quick and pleasant to use, but missed a crucial detail.
Afterwards I tried it with Opus and it did not make the same mistake.
Arguably I'd call that the 90%. In my case, answering the restaurant question correctly with "Rishi" in my tests was the sole intent and 90% of the problem. All the models "helpfully" added extra junk about the closure, dates, quotes, etc and many of them got these details wrong--the 10% or extra crap not central to the question.
If the central question was "what is the bus schedule on `day`" and the model screws that up, it gets a fail in my book.
Also curious if Google Maps gets the timetables correct (assuming it has them).
Semi-related, I also discovered that the default web search/fetch tools are pretty primitive and Exa MCP annihilates them. I ended up doing some comparisons with Claude Code comparing built-in server-side to Exa and to a Python MCP that used SearXNG for search and Exa was a clear winner and Python+SearXNG ended up coming out roughly the same after a few cycles of letting Claude optimize the Python code and adjust SearXNG settings. Ultimately it landed on this (making some changes to optimize returning relevant context directly in the search results so the model didn't need an additional web fetch call) https://gist.github.com/nijave/604c43e3e0fdcd60f5280d3a6b109...
This likely comes down to how it accessed the bus schedules (i.e. web search tool) and not intelligence.
You need to add the actual bus schedule to context somehow (research agent, custom tool or just dump in prompt) and even the simpler modern models will be able to do the planning.
Tool usage competency is part of overall intelligence. If the model can't get the information it needs, it must clarify that in the response.
This isn't tool usage competency, it's tool quality and/or luck. Regular web search is not good for grounding if you want accurate results. You can ask the model to make a tool for getting bus schedules and then use it only then you are comparing apples to apples in this case.
I think the "secret sauce" is not juicing the benchmarks. Claude models just feel like they are better than the benchmarks suggest, in terms of smarts and creativity, while models from every other company feel worse relative to what you'd think from the benchmarks. Only company to really internalize Goodhart's Law, IMO.
Yeah every model has great benchmarks. Claude is the only model I want to use when I'm not worried about the marginal cost of tokens (which is most of the time at work.)
I then use cheaper models like GLM for personal projects but they're noticeably much worse despite being similar in benchmarks.
I think it's focus? Anthropic seemed to double down early on being more business/prosumer focused. While OAI, Gemini, Grok, etc were also doing various side quests like image generation, Anthropic seemed to only focus on 1 thing, and that seemed to pay off
One angle could be their interpretability research? They understand what's going on in LLMs probably much better than anyone else. This must somehow pay off.
I think it's not only an alignment/security tool but could perhaps be used for capabilities as well.
I think it's the talent, laser focus on single product set and being early so ahead, same with Open AI who are only a sliver behind. Google, XAI are the next level down but they have other concerns.
Given their pricing, I'd guess their models are just way bigger in parameter count. They've always underperformed in cost-per-performance.
They also target a cost-insensitive market (corporate/coding users) compared to Google/OpenAI which support massive amounts of free users.
I think they have a better agent personality which pushes back and isn't sycophantic. It has been awhile since I've used the others but that's where it locked me in and I've stuck with it.
> isn't sycophantic
Not sure about that one... But I think the true secret sauce for all these models is how they reason. GPT never outputs how it thinks, which "saves on tokens" but Claude absolutely tells you how it thinks, and there's people who use how it reasons about solving problems to finetune smaller open source models, with surprisingly better output.
From my experience, it has not been sycophantic in the sense that it pushes back and questions my own reasoning in healthy ways. There were moments where I felt I was brushing up against actual AI psychosis, and it pushed back on my questioning of its intentions, that it even had intentions. I'll put it this way: I feel comfortable recommending Claude to people who haven't experienced AI yet. As we've learned from early experiences with other models, leading people down paths of believing they understood math in ways nobody else has and even harming themselves, I put Claude as a safer alternative.
I think it is a mix of the sibling replies here. I'd add that the company has seemed to find ways to ~do more with less.
I have never liked the various nerfs Anthropic has used to balance GPU (slowing down responses, quota variance, model optimizations etc) and it definitely has burned a lot of good-will.
But it has seemed that being able to look beyond the short term pitchforks has worked quite well.
From what I have read, their pre-training team is much better than anyone else. For OpenAI, their post-training team is better. And apparently OpenAI has consistently struggled at training a bigger model than GPT 4 level
I’m a VP Eng — the backend team I manage strongly prefers CC and Opus. The Android team I manage strongly prefers Codex and GPT 5. I’m personally not sure that the answer doesn’t just come down to stylistic differences in prompting and ergonomics in the harness. The folks that prefer Codex seem to get better one-shot results, whereas those that prefer CC are doing more iterative prompting. At any rate, I don’t think you should write OpenAI off when it comes to coding.
Someone has to know.
Would be nice if an insider would drop some hints so that the open-source space could make some good progress.
Nobody has to actually know the secret of their own success, especially not relative success to equally-secretive near-peers.
Same as with rich person autobiographies: even when they tell you what they think it is, they can't see the path not travelled.
>Its remarkable how Anthropic is able to maintain their edge against all competition. Anyone have any idea what the secret sauce is that has Anthropic at the top of all leaderboards for the past few years?
It's self-reinforcing: they've got the best coding/research model, which helps them to improve their models better than the competition so they stay ahead.
because in the real-world, it's far better than the rest. That's why few people use Grok, it's not even close in day to day work.
The anti-Musk stuff would qualify as brigading in nearly any other community. It shocks me that people have such a visceral, irrational engagement with anything in Musk's orbit. I probably shouldn't have, but I expected better from the HN crowd for some reason.
It's an excellent model. GPT 5.4/5.5 level, some things better, others not, but extremely fast. A wonderful technical improvement.
If a Chinese company or random startup released the model, people would be glazing it like crazy.
xAI is competently keeping up with the frontier, just as well as any of the Chinese labs or Mistral. Given any significant breakthroughs, xAI will be better positioned to capitalize on them than nearly any other entity.
I can't wait to see what Meta comes up with; with 4 contenders in the US race, we'd have a lot of be grateful for.
It's surprising anyone could not be viscerally disgusted by the person who has caused such immense destruction and death recently just because they released a 3rd rate slop machine.
> It shocks me that people have such a visceral, irrational engagement with anything in Musk's orbit.
Shocked? DOGE defunded USAID and children's cancer research funding. And have you read his twitter feed lately or seen this video? https://www.youtube.com/watch?v=-VfYjPzj1Xw
I agree that we don't judge his work based strictly on its merits but that's consequence a that he's created by his behavior, and I wouldn't call it brigading.
The fact that you're shocked is silly.
A very quick search showed that USAID had extensive ethical compromise throughout the organization.
Were we supposed to just subsidize that forever?
It did some good, yes, but from what I can tell, it was better to shut it down.
That's just one example, but frankly I get the feeling that if I dug into more examples they'd end up the same: easily explained and not entirely shocking.
What sources did your quick search turn up?
Also you didn’t give any examples. You just plainly made the statement they were ethically compromised without saying how.
> It did some good, yes, but from what I can tell, it was better to shut it down.
Whatever you are reading is badly misinforming you.
I'm sure there was some reform and cleanup to do in certain USAID programs, but the programs Musk killed or interrupted were literally the best lives-saved-per-dollar programs on the planet. PEPFAR, for example, is credited with saving 25+ million lives since it was created during GWB's term.
There's also the rather important point that what Musk did was totally illegal. These are programs created by congress and their funding is mandated by law.
If people have issues with how USAID was being run, they can address them through action in congress - congress established the agency and has authority.
What Musk participated in was illegal, motivated by self-interest and personal gain, and undermines our democratic processes. Don’t be surprised that people are mad at the oligarch acting like an oligarch. Musk deserves exactly as much say in the American government as anyone else - one vote - but in his arrogance he has taken his resources and used them to buy influence that is not his to own. It is fundamentally unamerican.
I see what you're saying, and perhaps you're right.
However, I will point out that illegal != immoral. Sometimes when you have the power to do the right thing, you do it. Especially if the "within the law" approach won't work (see: Congress)
I recognize that many would disagree with me, and many would especially disagree regarding whether it was "right". I'm incredibly disillusioned that we even have the ability to course-correct as a nation; especially not through Congress.
So... idk. I'm conflicted. Musk hardly seems like the biggest problem this country is facing, and at least he's doing whatever is within his power to address it.
We do have the mechanisms to course correct. He just chose to illegally and immorally ignore those in favor of his feelings and against all actual data.
Refreshing to see model announcements without claiming #1 in some benchmark. The amount of documentation seems very immature [0]. No system card provided - compared to Opus 4.8 which shipped with a 246 page analysis [1].
[0] https://docs.x.ai/developers/models/grok-4.5
[1] https://www.anthropic.com/news/claude-opus-4-8
Props to them for including three benchmarks that actually seem to say something, instead of focusing on totally gamed benchmarks like regular SWE-Bench. That could mean this model is actually pretty close to the SOTA as the benchmarks indicate.
Most labs - including OpenAI and Anthropic, but also Google and Chinese labs - highlight their scores in benchmarks that have fixed, widely available answers. Those answers end up in the training data and so models can just regurgitate training data instead of actually doing the benchmark. As a result, most benchmarks often quoted are essentially meaningless for gauging model performance.
Terminal-Bench still publishes answers, but neither DeepSWE and SWE-Bench Pro do. Especially for DeepSWE it's been difficult for models to fake good results so far. SWE-Bench Pro does have weird outliers like good performance for e.g. the atrocious Muse Spark, but it also doesn't provide answers for the training data.
So either they're good, or they found a way to game DeepSWE. Given that the Cursor team previously published the well-received Composer 2.5 a good score here doesn't come out of nowhere, so this might hold up. Cursor has enormous amounts of training data to train good coding models with.
Interesting. I experimented with Grok 4 for openclaw when they made clear they wanted to bring claw users in the fold. It was (as expected) more verbally fluid than 5.5, but had real trouble with agentic tool calling - the model felt like it hadn't been trained to think of tool calling as one of its primary modalities. I'll give this a try, the speed and the benchmarks look good. In my experience, Grok slightly punches above its weight in language fluidity, and seems to not benchmaxx on coding, so this is an encouraging release.
What's the future of Grok and Cursor's Composer now that they are both under SpaceX
Is there a reason the AI companies usually announce new products so close to each other. Like not just the same day but literally hours apart. GPT Live then an hour later Grok 4.5. As if they try to one up. I expect something new from Anhtropic as well today.
They get to compare their model to the old ones from the competition.
In this case, ChatGPT 5.6 Sol / Ultra releases tomorrow, so today is the last day Grok can compare Grok 4.5 to Codex 5.5. If they did it tomorrow people would point out they're comparing themselves against old models.
I'm guessing that they already have the model ready and the announcement blogposts locked and loaded, and then release them as soon as they see a competitor make the first move, trying to overshadow the first announcement or at least be swept up in the hype just as people start talking about new models again.
I think this one is just a coincidence, bound to happen given the pace of releases
For exact timing, probably 10-11am Pacific is just optimal for normal working hours
Maybe it‘s the Nash equilibrium from a timing perspective?
Like the reason that close to a McDonals there is usually a Burger King.
The joke is that McDonald's spends hundreds of thousands of dollars to identify new locations - traffic studies, visibility, demographics, nearby traffic generators, site characteristics, drive-thru feasibility, etc. They have one of the most rigorous processes in the industry. Burger King's process is to open a location across the street.
I think the story was Starbucks -> Seattle's Best Coffee, not McD's --> BK. but it does work I guess.
reminds me of SBC's (Seattle's Best Coffee) strategy, which was decidedly not Nash: put a store across the street from every Starbucks.
Competition. You don't want to lose your customers trying out the competitors updated and better product. Release on the same day and they won't be able to compare their new to your old.
But how do they know what day is that? Unless you have already something ready to be announced (and you just hold it until the very last moment, which doesn’t make sense, since you could just announce it asap)
It can also be ”we are done but wanna test it more and tweak it” and then ”oh they launched now. Let’s launch then as well”
All the people who are any good at AI talk to each other. There's no secrets among those who are making 7 figures plus in this field.
"keep refining and testing it until we're really done or somebody else releases"
Maybe a little corporate espionage.
Probably more keeping an eye on the behavior of the competition and predicting what they might do and adjusting your own schedules.
The solar system diagram doesn't work for me. When I click on the planets, it will center on them. When I click on the sun, nothing happens. When I click on a planet next, it goes to the sun.
How popular is Grok compared to other companies models for SWE tasks? I almost never hear it talked about against OpenAI's or Anthropic's products
Because of the of the political stuff, they have a bad reputation I think and are taken less seriously (I feel this way). They have an opportunity imo to break free from that and just not do the gatekeeping / condescension that the other providers are starting, and become more mainstream.
Even without the politics, Elon has shown that he will weaponize his platforms against people/companies he personally doesn't like (e.g. specific bans/demotions to external sites like Substack and Bluesky).
Using Grok is therefore a supply chain risk and it's not nearly good enough to offset that risk.
As opposed to what was happening before, on Twitter?
Nobody said that Twitter wasn't poorly-managed. All types of petty squabbling are a liability nightmare for consumers of software services.
I do just want to focus on the 'even without the politics' asterisk though because sometimes there is a risk people think everyone on x side (x meaning 'a given side', not x.com) is wrong
You can claim Elon bought x as some sort of power trip. Fine. Willing to entertain it, I have no dog in the fight. I'm not a member of the Elon fan club. And yet Twitter (under Dorsey though I don't think he was involved) was banning tons of people under guises of 'misinfo' that wasn't misinfo
Pre-Musk twitter isn't the comparison point here. Anthropic/Google are.
Americans are 4% of the world's population, and even among those 4% at least half don't give a shit. the rest of us give even less of a shit, we don't have the luxury to be principled.
The rest of the world either has no money to pay for this stuff or cares even more. You think the average European or Australian loves Elon's racist tweets?
The people who "don't have the luxury" are using cheaper Chinese models.
To be frank, I will never use Grok as long as it's remotely affiliated with or under the influence of Elon Musk or his ilk.
They were missing a harness like Claude Code or Codex (terminal). However they recently released Grok Build, which is probably the fasted I've used, in terms of responsiveness, but didn't have a model at Opus 4.7/8 level. The thing is if they add 4.5 to Grok Build and keep improving the harness I think it can compete (cheaper and faster).
I've been using Grok Build over the last couple weeks. It's actually a very good CLI. The Grok Build 0.1 model isn't great but can also use Composer 2.5 which is excellent. Well worth trying.
You can very roughly proxy popularity of close-sourced models through OpenRouter token throughput. Grok has an order of magnitude less OpenRouter usage than Claude, GPT, even Gemini.
Completely irrelevant, which was expected considering their previous models were vastly outclassed by other models at SWE.
This is the first grok model that seems actually pretty competitive at SWE.
Wasn't, which is why they purchased Cursor.
They had two big substantive flaws on top of the political stuff. Aside from a brief window last summer Grok has been behind the curve for coding, and before the Cursor acquisition they didn’t have a harness. Now they have an Opus tier model and a real harness they have at a minimum the opportunity to undercut the competition on price. And with the 5T and 10T models being trained on Colossus 2 they have the possibility to leap ahead.
If they were a frontier lab, you'd know.
No one's made a MechaHitler joke yet?
Very hard for me to imagine this getting beyond a low-single-digit market share. I don't understand the strategy of xAI burning money on this.
I think the strategy is pretty obvious
I think it's the first time ever we don't see the dominant model being surpassed by new released concurent models.
Did anthropic found their moat or we hit a Wall?
What would have been fantastic is if Cursor offered Grok 4.5 in the same usage tier as "Auto + Composer", than provide it as "double usage until July 12" under the API tier (which is what they're doing right now).
EDIT: After looking at my own usage stats - I stand corrected! It is under the "Auto + Composer" tier - brilliant!
Personally, I wish they had shared some of the galactic code that GROK claims to have generated.
still waiting for a proper gui for grok build
terminal is nice but codex desktop app is very useful
You can use it in Cursor!
1+0 records in and 1+0 records out
I’m amazed at everyone’s willingness to use tools owned by this man, very disappointing.
I think that Elon Musk went from being recognized as a genius to being recognized as a genius but someone who's harder to take seriously, because of all the ketamine he was doing for a little while there. I think that really damaged his reputation. You just can't help but look at him and think, he's a little bit of a jackass. It really shows how drugs can really mess up your reputation.
Big if true. If so they have mogged Google, and GDM in particular very, very badly.
Google Deepmind has failed.
Flash 3.5 seems capable for a flash model, Antigravity seems like a reasonable harness. But GDM is responsible for the frontier model and it looks like a complete failure.
What's particularly galling is the size of funding of GDM. It is enormous compared to the other labs. The headcount of other labs is swollen by infra, marketing, sales, GDM is pure "engineering" and its frontier model isn't even leading open source.
What a failure. It's unreal.
Not available for Europeans yet. :(
I think it should be available through Cursor?
EDIT: Tested myself, it's actually NOT available from EU. But with a Swiss VPN it works :)
We will probably see it when it's available for everyone.
This is the first time I see a lab region locking a model though.
> This is the first time I see a lab region locking a model though.
I think Facebook/Meta was first with this, can't remember exactly what model release but one/some of them had terms locking out EU/EEA residents from using it/some specific features of it.
first image gen models from openai and google were not available in the eu at the launch
xAI is under criminal investigation in the EU
Who isn't
I'm not - then again I didn't launch a image generation model advertised as having a spicy mode so that might have something to do with the coincidence.
Apple, Google (Alphabet), Meta, Tik-tok etc are also, it's the EU shakedown method.
You think ur not...
Contrary to what you're implying, that's more of a reflection on the typical US corporation than the EU.
Hilarious comment now when they try to push Chat Control again.
Luckily, basic VPN to US is enough to use it. Just tested it.
They say "EU availability is expected in mid-July". So next week or so.
Just as a reminder, Musk's actions lead directly to the deaths of thousands of people in the third world: https://archive.ph/20250629012329/https://www.nytimes.com/20..., https://www.propublica.org/article/kenya-trump-usaid-world-f...
Enjoy your chatbot!
Another subpar model. Why don't they go open weight?
Isn't this the same Twitter company that was supposed to go bankrupt a few years ago? Now it is somehow part of a Space company that has an AI division inside of it?
I think we are going to be waiting a long time for Twitter / X to go bankrupt as it was (erroneously) predicted a long time ago.
Twitter was supposed to go bankrupt if you only read news articles from journalists about it. If you looked at Musk's operating track record, you might have had a different opinion.
In the transaction announcement (xAI buying twitter) twitter reported $12b in debt on acquisition, roughly the amount originally sourced ($13b), so it apparently made good on its debt covenants during the operating period. I have no idea if it received additional capitalization from Musk to do that or not.
That said, the deal was classic Musk - anybody who went on the equity ride with him in Twitter just KILLLED it; xAI was valued at $80bn and twitter at $33bn, so the owners there became 30% owners of xAI. xAI was acquired for $250bn at a SpaceX valuation of $1 trillion, or 20% of the resulting entity, so the twitter stock was 6% of spaceX at about $2 trillion, or $120bn on an equity purchase price basis of $30bn. and that $120bn in value is on really good daily trading volumes; lots of depth.
That was the point of the bailout. Twitter is already a rounding error so no one will notice if it goes to zero.
Don't think it was going to zero anyway. They only had to worry about servicing their debt, they were doing well other than that. And even then they were probably fine.
I am not certain what financials you were looking at but Twitter was unable to ever meet the debt servicing costs for the leveraged buyout alone. It also had overhead costs and other debts that were entirely out of scope for being covered.
The latest Bloomberg reports before the xai merger/acquisition showed a dramatic turn around in their financial situation.
In the beginning it wasn’t good but they would have been fine after that. There are no credible reports to the contrary
twitter was "acquired" by xAI which was then "acquired" by SpaceX as part of the IPO strategy, (and part of a strategy of giving the investors on the hook for the twitter acquisition a return). Who knows how it performs, but yeah, now that it's the social media arm of the SpaceX conglomerate, it will likely be around for a long time, especially since it serves the basic function of stroking Musk's ego.
It is right and proper to view twitter as a loss leader propaganda arm.
None of them go bankrupt. The whole thing will just get stuffed into a larger Matryoshka egg that IPOs for eleventy trillion dollars in 10 years.
I'd say the prediction is correct, as the acquisition is more or less just a better way to capitalize on the bankruptcy.
Grok is not a serious AI, it's not suitable for professional work and has mediocre performance anyway.
They talk about benchmark first places at every release, but in reality from 4.0 onward Grok got worse every release. So bad in fact that they removed the login-free access and rented out colossus.
People don't buy it any longer, just like no one bought the fake SpaceX stock recommendations yesterday and everyone just sold.
Do we have any proof that this was made by xAI and isn't some Chinese open model running with modifications?
Their inital image generation was a wrapper around Flux.
Even if they did start from an open model base, does (or should) that matter if it performs well?
Genuinely asking.
It matters for how much money they are valued at. If they don't have the ability to develop true frontier models in-house, why are they worth $1T+?
It’d be real funny if this was just GLM 5.2 trained on Cursor data
If you want to do some non-eugenics, fascist-free AI coding, try Zed with GitHub Copilot. I’ve been using it this week with better results than I ever had with Cursor. There’s even a low token “MAI-Code-1-Flash” model which has been giving me better results than any Composer model I used to use and the tokens used seem to be way less.
I asked it today to fix a non-simple bug and MAI fixed it in one shot with less than 70k tokens (Cursor would have used probably half a million tokens based on my previous usage). Orgs need to start getting more visibility into why Cursor burns so many tokens.