Apparently Grok 4.7 has 40% more weights than Grok 4.6, but the price ($6 output token, $2 input) is the same.
Given that the decrease in their margin and the fact they delayed the release of Grok 4.7 almost two weeks past the original date, XAI must not have been happy with the results for 4.7. And XAI also waited the day before Opus 5.5 is rumored to launch. I imagine Opus 5.5 will blow Grok 4.7 out of the water benchmark wise.
However, I have become skeptical of benchmarks. Grok 4.5 solved some issues setting up a buildroot system that Fable 5 couldn't do. I find the post cursor groks are phenomenal at frontend web development, though Claude is much better at backend ruby.
My favorite part of the new Groks has been how they speak in plain english. I simply cannot stand Claudish. Or even GPT, which doesn't have Claude's ticks but definitely likes to handwave explaining technical concepts. Still, nothing beats Claude 3.5 and 4 with explaining since it seems all models have regressed. I wonder if Grok 4.7 will also regress with English because of all the RL.
> My favorite part of the new Groks has been how they speak in plain english. I simply cannot stand Claudish.
Grok has its own feel too. It's not as bad as Claude, but one of the things that bugs me is that it is far too terse.
It regularly seems to come up with terms and descriptions for things in its chain of reasoning and then uses these terms in its output assuming you understand what it's talking about.
I find I often have to ask it to re-explain what it means.
> It regularly seems to come up with terms and descriptions for things in its chain of reasoning and then uses these terms in its output assuming you understand what it's talking about.
GPT does this all the time, too (both Sol and Astra). I constantly have to tell it to not use terms that were not part of the initial prompt.
I don't know how people are managing hands-off with Sol/Astra over long horizon tasks. It will come up with 100 new concepts/terms and then use them as if you've been following every Edit call for 24 hours.
It’s probably an assumption baked into the training pipeline from that ancient time six months ago when we mostly were manually following each edit tool call.
> I constantly have to tell it to not use terms that were not part of the initial prompt.
Hah, yeah even when you put it in AGENTS.md or a skill.. constantly having to remind it.. "what does AGENTS.md" say about doing that?".. Thinking.. Thinking.. "Oh, it says I should never do that, I'll remember that next time.."
I’m pretty sure the big bois don’t do it because it would undermine “confidence”.
Seeing a model output “Oh I should just delete blah. Wait blah is a production service, I shouldn’t touch that. Maybe I can gain access to blah? Oh the aws cli isn’t signed in to blah. I see kubectl has access to blah though! Wait, I should ask user permission first.”
Idk I feel like the more likely answer is to prevent distillation. Having the thinking is definitely better UX (oftentimes, I don’t know if Codex is just hanging, which it often does, or working in silence).
I stay much more hands-on when I'm using models that display full reasoning traces. And I tend to get more things done as a result, because I know exactly when it thought of a good solution that it talked itself out of because of some invalid assumption.
Could be something very stupid like - "I don't have ffmpeg available here. Should I install it? No, I can't. I'll proceed doing something that will take me 100x more tokens and wall clock just to avoid adding a dependency." I can then just stop and say - you've got nix flake there, just add it.
That's impossible with western models. The only way is to ask why it did something stupid when it already spent 50% of your weekly quota and produced millions lines of slop.
Ah, but you CAN see the thinking if you are willing to risk your account being banned. You just have to expose a "tool" with a specially crafted definition.
You can double click on the 'thinking' text and it will expand and you can read it. The problem is that it will often have multiple thinking/tool call sections and it can be a needle/haystack problem to find the one with the thinking you are interested in.
SpaceX is a defense contractor (I don't mean this in a bad way). When the whole DoD/Anthropic thing flared up, I can guarantee you that SpaceX.ai was the first company invited to take their place as DoD AI provider.
I suspect that they specifically train Grok to be able to work well with military personnel -- speaking the way they speak: brief, to the point, efficient communication. Personally I really like this. Claude sounds like some demented clown from the marketing department.
> It regularly seems to come up with terms and descriptions for things in its chain of reasoning and then uses these terms in its output assuming you understand what it's talking about.
FYI a quick fix for claudish is to ask for the response to be in ASD-STE100 (Simple Technical English). Then it is far more readable. But I would agree that this is an annoyance and shouldn't require user workaround to get something readable.
I think this is more a meme than anything else, for a couple reasons:
First, after a while it's just as grating as Claudeish.
Second, my hunch is that it constricts the actual thinking of the LLM, like the same way that Newspeak does in 1984. It shrinks the range of thought that can be expressed if used as an input.
I think the real way to do it is to have another Claude entirely deal with the user as a liaison, but to keep the thinking in whatever format it came in.
Latent space reasoning, if you think about it, is exactly this to a crazy degree: why even formulate a thought as words if you can just keep it as matmuls until the user needs it? And then, if the user needs it, have it always specifically formulated for the user by another LLM rather than constrict its range of thought? Anyway, that's my take.
The fact that it might affect quality is something that is on my mind. In fact, I have mainly been using Astra after being primarily on Claude for several years exactly because of this annoyance. Ultimately, the model (at least for coding purposes) should just... not have this writing style.
I do think an infrastructure where another Claude retranslates the output would be better. Oftentimes I forget to put it in the actual prompt and when I receive back 8 paragraphs of Claudeish I ask for it then.
I would have to disagree that it gets as grating as Claudeish though. Its just direct and professional instead of ring-around-the-rosy clickbait.
The Claudeish drove me back to OpenAI and Codex as well. I find the Claudeish can be improved but it’s impossible to fully mitigate. Opus is unusable for anything I’m going to read.
“I would have to disagree that it gets as grating as Claudeish though.”
It’s hard to imagine anything more grating than Claudeish. To quote Rainer Wolfcastle, "My eyes! The goggles do nothing!"
> my hunch is that it constricts the actual thinking of the LLM
I've found that prompting any constraint on output (length, style, vocab, even simple formatting) not only places additional cognitive load on the model, which burns some of whatever cognitive budget is available, it will also often skew the output in other subtle and completely unrelated ways.
Since I found this artifact interesting, I did some pretty extensive experiments a couple months ago. The increased load is real, although it may not be apparent if you're not near any cognitive boundaries. The subtle skew, however, seems nearly ever-present regardless of load.
When I noticed web chat LLMs wouldn't number section headings correctly and consistently, I began experimenting with modifying the user prompt over a period of weeks. My usage at that time was research and learning not coding. In long, detailed sessions with branching sub-topics and deep follow-ups, I found it helpful if the LLM would number each major section and letter each sub-section in replies. Simple markdown formatting that most web chat LLMs do sometimes, but not consistently nor uniformly.
While extensive, my tests were just following my curiousity, not controlled, exhaustive or well-documented. I identified about a dozen prior sessions of varying length and complexity to test and downloaded them with a browser add-on. I then removed all other user prompt instructions except for the formatting instruction. A test would typically involve changing the wording of the formatting instruction ranging from brutally simple to detailed and complete, then starting a new session, seeding one of the test sessions and continuing it. To get a feel for baseline inter-session variation, I also tried running the exact same prompt/session multiple times back-to-back, at different times and on different days of the week.
Once I identified a promising prompt candidate, I'd make it the formatting instruction in my regular, daily-use prompt for a few days. I quickly got a feel for how seemingly minor user prompt variations impact response quality, compliance and tone across fresh sessions as well as those in various states of context rot, drift, decay and cliff (<--my nicknames for the distinct flavors of session degradation, not technical terms).
My overall conclusion was that every instruction, no matter how minor or unrelated it seems, has some, real impact on the model's cog load, attentional focus and/or attentional weight budget. Both how these impacts manifest and what causes more or less impact is often extremely counteriintuitive. To more fully understand this, I eventually, got to the point of testing null case variants, such as the entire user prompt being one sentence completely unrelated to text formatting or the session topic, like: "Don't reference the cartoon character SnagglePuss" (in a deep dive on ancient Sumerian clay tokens). Similarly, a simple one sentence prompt requesting something the model already always does naturally also has a cost (eg "Capitalize proper nouns"). As others have observed, heavy emphasis, absolute prohibitions or emotional weight in prompts also tend to have outsized impact in both skew (impacting unrelated output tone/style) and in accelerating session degradation. "Avoid referencing SnagglePuss when you can" would have equal compliance but fewer downside impacts than "NEVER reference the cartoon character SnagglePuss" in sessions starting to degrade.
There were also surprises, such as when I was scanning transcripts of an older, longer session and noticed the LLM was doing number formatting almost perfectly. On looking at the active user prompt at the time (I keep a log of every user prompt change I make for every model), it didn't even reference formatting at all. More experimentation showed it a result of the LLM gradually mirroring my consistent use of formatting structure in my prompts over a long session (in which I never mentioned anything about formatting). Unfortunately, that mirrored trait doesn't persist to new sessions and reaching that point requires a substantial number of rounds burning quite a bit of context window.
After spending time surfacing the impacts of just changing lightweight user prompts so they could be observed (which are the lowest priority prompts a model gets), I now wonder just how much more 'brilliant' the models we use daily would be if they didn't have dozens of pages high-priority manufacturer prohibition prompts we never even see weighing them down. We've only ever seen these frontier 'racehorses' when they're already pulling a heavy invisible wagon.
This is the same reason why I am a bit skeptical of LLM superintelligence. LLMs in the end have to operate in natural language concepts and the complexity of natural language is bounded by limits of human cognition. I'm sure super advanced AI could use concepts that humans not only have no words for, but might not be able to understand alltogether. As such if my thesis is correct, the only way forward for true superintelligence may be getting rid of natural language COTs.
> LLMs in the end have to operate in natural language concepts and the complexity of natural language is bounded by limits of human cognition.
I don't think this is true.
They have to express themselves as tokens. The meaning of those tokens doesn't have to be text. See any model that can handle images/video. Also, I don't think math, svg, etc, are "natural" language.
And, only the final expression is tokens. The intermediate layers, with the encoded concepts, aren't "natural language".
But, to address your concern (which nobody can disagree with, since even humans can't fully express through text/pictures), potentially: https://news.ycombinator.com/item?id=49758615
> The model isn't limited to concepts that can be expressed in natural language.
How do we know for sure? We don't even know how the emergent properties we see actually emerged?
For humans we know for sure that people sometimes have concepts that they have no word for (the reason the phrase "It's on the tip of my tongue" is a phrase, after all).
We don't know this for LLMs. When it makes new phrases, it's always a mixup of two existing words hyphenated (aside, that also seems to be the limits of SOTA models creativity - join two unrelated words together with a hyphen).
LLMs never respond with "It's on the tip of my tongue" type responses, indicating it has a concept but cannot remember (or does not have) a word for that concept. Every human, pre-speech-age, has managed to express or convey concepts that they had no word for.
So, no. I'd need a citation, preferably multiple, that did the trials and found that a model can generate concepts for which it does not have any words for.
1. Is natural language holding LLMs back by some %?
2. Is natural language serving as a hard gate that will prevent LLM intelligent progressing past some specific point?
The answer to 1 seems like an obvious yes to me.
Your thesis says the answer to 2 is "yes." That doesn't feel right to me. Think about all of the humans who have pushed various fields forward: Einstein, Newtown, Bach, whoever. If natural language doesn't prevent an entity from surpassing humans in one intellectual field, why would it prevent an entity from surpassing humans in all intellectual fields?
(To be clear, I'm not claiming superintelligence will or won't be achieved; I'm considering your specific thesis about whether or not natural language will be a hard gate)
Each letter has it's own token. LLMs can invent new words if they want to, just like humans do. All the fancy words we use today in science did not exist even 100 years ago. And that didn't stop us.
A few weeks ago two "Claude wrapper" projects showed up here within 24 hours of each other. Both seemed to just sand the details away--useful if Claude is too wordy, I suppose, but seemed to also lose real substance.
I agree there is probably some impact on output quality when doing this (Claude seems to embedded key signals all over the writing, which is much or what makes it horrible to read). However this does work well as a "second pass" over technical docs or designs along the way
Ask for output to the user in "simple technical English", let it think how it wants. It is hard to believe all the flowery prose is actually helpful to the model.
I don’t think system prompts are particularly reliable way to do much at all. It’s better to put it as a hook after each response, or a skill at least so you can trigger it at will if you don’t want it everytime.
Anthropic has probably RL’d the system prompt into nothing because of their fear of the user being able to control the model. If it listened to you about the slop language, it might listen to you if you asked it to help you with no-no tasks.
Your best bet is to use hooks and inject it after every file edit / response by first running the content through haiku and asking if it is asd 100 ste.
It burns more tokens but is the only way to get tolerable text.
The hook sends the text to another agent/context with a request to validate and return a good or bad + reason response. Every request is a fresh context.
I hadn’t heard of ASD-STE100 until last month when the TinyGo AGENTS.md added it as a requirement, along with some other tidbits to improve life for maintainers.
It’s been really productive and I’ve been asking my agents to communicate using it more and more. I believe it’s relieved my cognitive load a bit while working with them.
I created a custom output style based on this (borrowing some from github.com/AminBlg/SimpleEnglish) and I've found it to be better than the default or concise output styles, but still not as good for me as current GPT or Gemini models when it comes to communicating.
I tried this a while back and I felt like the result was the same weird shoehorning of ideas into language, just with a different vocabulary. I’d really like for it to work, though.
Do tell why the downvotes? It actually works. When you tell it to adopt a certain style, just be sure to also tell it not to change the core truth of the output, it must still convey the original intent. It is surprisingly good at outputting Warhammer styles, which is very enjoyable in a dev environments or system admin sessions. Also put on some warhammer soundtrack in the background and you can easily zone in.
I was going to say the reverse - claude has been the less satisfying normalized by benchmark for me in the last year. Both astra and fable have their quirks, but I am 90% codex this year up from 10% last year.
I've been getting a ton done with Fable as the supervisor and astra as the implementer, with opus for adversarial reviews of the astra PRs. You can use terminal multiplexers with custom harnesses to allow Fable to start codex sessions and send instructions / read instructions / allow/deny actions. It's pretty cool!
codex has an option to expose itself as an MCP. You can also use something like OpenCodex to bring Anthropic models into Codex as any other selectable model.
The reason I did it the way I did was so that I can still use the codex and claude code subscriptions vs paying the API cost. Can you do that via OpenCode?
It's not just about benchmaxxing. Sincerely targeting those long-autonomy benchmarks is questionable in the first place, because naturally it drives the model to assume more and more about what you want.
The target market for frontier models is CEOs who want to lay off entire departments of their company. So the long autonomy benchmarks would seem to be sending exactly the right signal.
I totally agree, it’s like that as models become more intelligent, they are less understandable by most of people... but aren’t we humans doing the same?
Agreed. The more knowledge you amass on a subject, the more important it becomes to be extremely specific and nuanced - or your communications end up being incorrect. You become better at expressing your thoughts, but harder to understand.
The weird thing is, that's not what AI models seem to be doing. The prose is just weird.
> You become better at expressing your thoughts, but harder to understand.
This happens most though when the speaker doesn't (or care to) understand their audience.
Eg i find effective communication requires expertise in both the subject matter domain but also the reference of the listener. Eg in ELI5 framing, if you don't know what information 5yr olds are expected to know you'll do a poor job at an ELI5.
It often feels like Claude does poorly at both framing the response relative to what it "thinks" the listener knows, but also the prose is... sideways, just weird as you said.
I find people tend to lack nuance in their communication more often - leading to problems and misunderstandings.
If I don't grok an elaborate explanation, I can ask for clarification. If it's explained to me in an overly simplistic or unnuanced way, I'll walk away with a false sense of understanding.
That said, I'm sure we all have very different concentrations of these types of people and problems around us. I've definitely met some engineers who seem to actively try to make their language incomprehensible
They’re training the models on generated slop. I’ve done a comparison on samples from the different versions of Claude and they’re worlds apart. The ancient, supposedly obsolete models speak normal English.
What I notice about Claudish is that it has its preferred cliche’s and overstretched methaphores, it packs too many ideas in a sentence, and to achieve the latter it makes up adjectives.
I should try adding these tips to my system prompt. Is there a shorthand to describe such language use? I am not a native English speaker.
Look up the output-style setting, which is a bit stronger than putting it in the system prompt. The new "concise" setting is better than the default but in practice, Claude is a very stubborn model when it comes to these patterns and they're really hard to eliminate, mostly you can only hope to mitigate.
As for the wording of the prompt, you're pretty on point, I created a custom output style targeting mostly the first two you have there. Some people have wording that demands a certain technical standard or uses fancy words to describe what to avoid, but I haven't seen evidence those work better than asking plainly and I suspect the opposite: LLMs mimic the user to a degree so talking to it in terms of technical specifications and fancy words is an invitation to get them back.
That's half true. A very smart model should be able make good explanations, which include simple understandable prose. That can should be possible even as its thought process gets more alien.
The best ideas are usually the simplest to elaborate. If someone comes up with a convoluted scheme that are hard to understand or be adequately explained, it's usually fraud.
When claude speak in convoluted mess, they are often going off on tangents in real work that you asked it to do, too.
That believes that the world can be simplified into dichotomies, or at least, simplified. Sometimes problems are complex, and the solutions to them necessarily so. For example, cancer. I order to begin to understand that problem, you have to understand the utter complex scheme it has devised in order to exist. A 20 minute YouTube video isn't going to be able to begin to cover the basics of the subject, although there are some good ones, with clever analogies.
Just because something is difficult to understand doesn't mean it's fraud, although if someone is trying to dazzle you with clever words and names of institutions you recognize because they are selling you something, there's a good chance they're lying to you in order to get some money from you.
No but almost all good ideas can be reduced down to a few sentences if you're good at explaining things. It's a different kind of intelligence than what's commonly called IQ but it's something like that regardless.
Sure the explanation will oversimplify a lot but then you can expand it recursively if needed, you gotta start somewhere.
I agree with you in that there exist such a class of problems, but Occam's razor apply in far more circumstances than it does not. When confronted with novel information under pressure of quick decisions, you have to take the most likely correct path.
> That believes that the world can be simplified into dichotomies, or at least, simplified. Sometimes problems are complex, and the solutions to them necessarily so. For example, cancer
You just simplified most of the problems people work on down to cancer complexity. Ironic, isn't it?
That's also simply not the case, most people are building CRUD apps with some frontend code and some accessory stuff like build systems etc., which while complex, can still be expressed in very plain, easy to understand language for anyone who's a bit technical.
> Part of intelligence is knowing your audience and communicating efficiently.
Bingo! And on this axis many SOTA models fail miserably. These things are acting on my behalf under my direction. All the supposed intelligence in the world means fuck-all if nobody can understand it.
And like somebody else said… when meat-based humans talk like Claude does, it almost always means they either don’t understand what they are talking about, or are actively trying to conceal something and are a fraud. Not always, but almost always.
Yeah just today it told me in a snarky way that my CPU (7940HX) doesn't exist and that I must have misread it and it's either 7945HX or 7940HS. Yes, AMD (re-)branding CPU models makes things difficult but I thought we are past AI models making such egregious mistakes
Perhaps you haven't had the chance to use it, but 3.8 flash is the best model for talking too. Even routing Claudes output through 3.8 to have it explain whats going on is a breath of fresh air
I'll have to try Gemini Flash for coding. The reason I haven't I used Gemini for coding is last time I tried it couldn't call tools very well.
I am a huge fan of Gemini Pro for chat... gemini somehow just knows the most obscure stuff. I'll double check something Gemini said and find the source is deep inside a hard to access scientific paper. Google just has the best index of the internet.
I remember the Gemini 2.5 Pro series was the best at text, but failed half of it's tool calls. They really redeemed themselves with the 3.5 Flash series, it's great. I love how fast it is.
Now if only they could offer a subscription service for it...
Makes sense. When Google Jules was new, I experimented with it for a while and it was embarrassing how often it flubbed tool calls, often repeatedly. It tended to forget the working directory so almost every command needed two tries.
Even if you aren't coding, you really need to double check its answers. Flash 3.8 hallucinated a Keyence camera's max operating temperature for me, last week, and backed it up with "references".
It's still my favorite model for most non-coding stuff, though.
> My favorite part of the new Groks has been how they speak in plain english.
I don't know if it's the plain english or what, but I really like Grok for legal research (as opposed to code). It's got a noticeable edge in getting to the point compared to Opus 5.
My favorite part of the new Groks has been how they speak in plain english
And the fact that Grok is the ultimate grandmaster of parallel tool-calls, routinely kicking off four or five at once. Overlapping the latencies makes a huge difference in responsiveness.
I also like how Grok is trained to print a short one-sentence descriptions of what it's doing before each step. Like an airline pilot calling out observations for the black-box recorder to hear.
I do wonder why a frontier model does this to be honest. It still does good coding wise, but it seems strange to me. r/Claude is full of "load bearing" jokes in every thread.
I've noticed Chatgpt 5.6 Sol High, on the chat interface, inventing words that are a mixture of Portuguese and English. Like "hardcodar" a mix of "hardcode" and the most common verb ending in Portuguese "-ar". Some don't have a single google hit
Do you have any connection to Portugal? I imagine if you have Portuguese in any of your prompts that might bleed into your user profile which becomes a part of every prompt. Alternatively it might use browser language settings
they are bugs with the model. Sol regularly glitches out and will type out random stuff even in tool calls. I'm guessing this is when they have capacity problems
> I find the post cursor groks are phenomenal at frontend web development, though Claude is much better at backend ruby.
Wonder if we'd benefit from a much more specialized + task-specific benchmarks to paint a clearer picture like this. A benchmark solely for frontend, ruby, hardware, etc.
Interesting to note that mimo v2.6 pro has been released at I think 1 trillion parameters and does mostly better or equal than grok 4.7 which is a 2 trillion parameter. Both of which got released on the same day.
That’s a factor of half the parameters. I would be curious to see more on the focus of smaller parameters model and pushing its frontiers
Grok and Zai have both been excellent as adjunct code-reviews, on their cheapest plans, for me. Fable plans, Opus writes, Codex as primary reviewer, but Grok and Zai usually find something worth fixing that the others have missed. Both are well worth whatever the $20 or so I'm paying for them
Same. The issue with Anthropics models is that (speaking regarding code generation) they REFUSE any kind of comment override instructions. I've tried everything and no matter what, after a few turns, they resort to generating the same overtly verbose junk. Bun's codebase is littered with them
See
// `HANDLE` is an opaque kernel handle (kernel32 validates and returns 0/FALSE
// on a non-console handle); every out-param is `&mut T` to a `#[repr(C)]` POD,
// ABI-identical to the Win32 `LP*` pointer (thin non-null). The reference type
// encodes the only pointer-validity precondition, so `safe fn` discharges the
// link-time proof. (`bun_windows_sys::kernel32` declares these with `*mut`;
// redeclared locally so the legacy-conhost cursor path below is plain calls.)
or
// Progress's terminal handle is the canonical `output::File` (vtable-backed
// stderr/File from `OutputSinkVTable`). The duplicate `ProgressTerminalVTable`
// from B-0 round 1 is removed; tty/ansi/winsize route through the new
// `OutputSinkVTable` slots so `bun_core` stays T0 (no `bun_sys` dep).
I actually love fable 5.1 prose. Before I was always on GPT models and I despised the writing. Actually I despised the writing they would do in the markdown docs, the writing in the responses was good. But there was always this weird thing that in the responses the model would write very clear explanations. Then if you ask it to document it what it ends up writing in the .md files is way too verbose, robotically lists facts and omits reasoning and gotchas. Too much unnecessary detail and too little detail it actually needed to capture. I absolutely hated GPT writing. Fable 5.1 though has the same concise, dense but logical and clear prose in both the responses and the documentation and the in-line code comments (oh yea Sol never wrote in-line code comments; and most of the time it deleted existing comments of code it didn’t even touch).
So yea, I find fable 5.1 writing to be excellent everywhere. I still use Sol daily though, but for things like config, quick research, fixes, code review etc. Feature work and writing is for fable 5.1.
Really? I’ve found that when working on my game I can’t let Grok write any text over about 8 words (tooltips for instance) or it will write the most horrendous incomprehensible slop - totally full of invented jargon, Claude-style weird grammar
Another great thing about Groks is sometimes they just simply do what you want to do. There's no fuss about refusals or it doing random stuff you didn't ask for or it speaking in slop or anything like that. They probably should pay a bit more attention to safety/alignment as they get better but they're great models for many use cases
You don't have to go into conspiracy mode about this. Musk clearly stated on X the other day that they delayed the release because they got some thing wrong with the RL behavior.
Flag (comments like the above extremely clearly break the guidelines which is what flagging is for), downvote, and contact the mods if there's a pattern of behavior. HN is partially moderated by its users!
I do not understand how anyone can seriously use a tool that has "Be funny and irreverent when appropriate" baked into the system prompt.
I don't want to waste money because my calculator is cracking jokes. They don't deserve their paltry 5% marketshare or whatever it is they have currently. I'm not even getting into Musk as a person or the horrid things we've seen Grok spit out on twitter. I just don't trust his companies with my data and I have seen very little evidence that it's ever the best tool for the job. I'm sure those cases exist but I can't imagine it's worth it.
I am on the exact same page as you, but there is definitely a market for LLMs which speak more conversationally and less like Claude! Non-programming use cases abound and most users don't like the rigid, exact tone that engineering demands.
For some reason reasoning effort low and medium used similar numbers of tokens, and xhigh used less than high. I think I need to try without OpenRouter in the middle.
UPDATE: I tried again with the xAI API directly: https://tools.simonwillison.net/markdown-svg-renderer?url=ht... - not a great deal of difference between reasoning levels, and this time xhigh and low used the same number of reasoning tokens for some reason.
exactly, the benchmark just needs to be downvoted into oblivion each times it's posted. The outcome is not deterministic and the model needs to determine what level of detail is appropriate for an svg. There is no wrong answer to this unless it's obviously un-Pelican-like.
Are there good tools for doing context audits? I feel I have no good way to visualize what a new session is getting by default in a given repo without crawling through every potentially included markdown file
Nice to see this release cadence increasing and some continued improvement in quality. I am guessing these models are basically still outcomes of the cursor team integrating with the massive amount of compute they now own: I’d imagine we will see significant step up improvements with grok 5 later this year as the team gets more experienced and confident with larger training deployments. Here’s hoping for another competitive frontier model!
> for “re-migration” in europe, also known as the forceful ethnic cleansing of non-white immigrants.
I'm curious if you feel the same about re-migration of Belgians from the Congo?
Personally I think it's fine for any country to vote to control immigration as they see fit. I think Japan is a good example of a relatively xenophobic culture that deals with this fairly and thoughtfully.
> I'm curious if you feel the same about re-migration of Belgians from the Congo?
Can't say I've ever heard anyone implying that colonialists leaving Belgium was unjust. Colonialists is actually not the right word, more like extended occupation, only slightly better than the enslavement of the Leopold II era. The Belgian's were less than 1% of the population and all but an ancillary amount worked in exploiting the native population.
You're right, I don't care and I certainly didn't ask for your political opinion or validation. This is a tech news website, not the place for your false and unrelated political tirades.
Technology isn't apolitical. You can choose to ignore the politics if it helps you sleep at night, but Elon's got three-letter agencies reaching up his ass like he's a Sesame Street puppet.
I didn't miss anything. The parent that they can choose to ignore it forever, it's a perfectly valid option. It just won't disentangle tech from politics.
The fact that Elon Musk's companies take contracts from the CIA and NRO is not flamebait. It's context that informs how we evaluate future SpaceX ventures.
You’re going to have to keep dealing with it, sorry to say, until you stop engaging with the work of a fascist. We’re not going away, and it’s just going to get worse.
Grok did ask its users what it thought about the right wing fever dream of genocide of white people in South Africa so its definitely relevant to one's consideration of the product.
Musk also shut down USAID for absolutely no reason at all which will cause the deaths of hundred of thousands of the poorest people in the world. Not a good look for the richest person in the world. Musk also sounds like a complete moron when he tries to justify why he did it.
Flamebait I guess but I think it is good we have several options to choose from already. If you don't like Elon there are several other models, and each can pick the one controlled by her favourite supervillain.
Initial impressions, Grok 4.6 for me just didn't really hack it for any usecase I tried. I seem to have a floor for my usecaseses (coding and a bunch of agentic workflows) and Sol/Opus are above some kind of intelligence floor.
4.7 is definitely slower & more expensive. It feels kind of like they really had it burn tokens to claw up the benchmarks. But it's not super clear to me whether it's above the line or not. A part of that is that it is so slow that i haven't been making fast progress today with benchmarking it.
Overall, it it gets above my intelligence line its a good release...but you can read the tea leaves and tell the Grok team thinks this was a miss.
I have no idea how good it is at coding but it seems to be good at omniscient tasks like solving a puzzle game I made [1]. It's a bit of a silly eval but I wonder if strong recall makes it good for knowledge tasks like legal work.
Coding, agentic flows like logging into my accounts and gathering data, grok bot.
4.6 made more mistakes than SOL or Opus overall. Gave up a lot. And in my opinion, the rate of mistakes is kind of more important than how brilliant it is.
I think 4.7 may still be better, but I was hoping for clearly Sol/Opus level and so far it just isn't there for me.
I didn't find 4.6 any better than Composer 2.5 - which remains incredible and honestly nothing else compares for me.
Make a galaxy model search the space, create a document, argue and defend decisions, then hand it to 2.5 to implement. 4.6 was a slower less enjoyable version of that.
4.7 is better at "I want the button to cancel the jobs, dont make any mistakes" but honestly that's not what I use it's class for.
I'm curious: what languages or frameworks is this in?
The Django code that comes out of composer2.5, to me, was insulting. Grok definitely was a step up, especially because the fast option reaaally is fast so even if it came out a bit wrong I could just whip it into perfection.
For frontend work, it's a different story. You can still tell that composer2.5 is taking the long route, but I don't think it's as egregious as with Django.
Also, composer2.5 would routinely run commands that were really dangerous and in need of proper sandboxing. Things like creating an ./uninstall.sh script with a HOME variable on which it does rm -rf $HOME. In general, when I asked composer2.5 to do things "for me", I knew a third of the initial commands would be failures, and sometimes they could be catastrophic failures (it did actually run rm -rf $HOME on what would be an actual home folder). This just hasn't happened with Grok.
I also have a bunch of vibe-coded apps I built for myself with composer2.5 and it is extremely noticeable that they hit a "this needs to be refactored as it's crumbling unto itself" line much earlier than with Grok and proper frontier models.
If you think anything Elon doing is groundbreaking, you have no idea how the world works. Recent Space X ipo showed that the launches aren't cheaper, they are just heavily subsidized. Tesla was a piece of crap until they got their model 3, the only reason Tesla succeeded with their S model is because Elon was the edgy hype dude who managed to generate enough hype to carry them through the bullshit with the car. Self driving was supposed to be solved last year, and tiny companies like Comma AI manage to build self driving systems that are in someways better than Teslas.
I bet you think Steve Jobs was a visionary as well lol.
>If not for Tesla there won't be EVs you see today.
Most manufacturers already were working on hybrids, which to this day are still suprerior to EVs. Chevy Volt, outside of being Chevy, was still one of the best cars ever made for utilitarian purpose. Nobody wanted to foot the bill to do electric conversions until this was necessary.
Tesla only opened up a market segment for high end electric cars, which I guess is cool, but far from revolutionary. The model 3 was a big success only because again, it was subsidized. Meanwhile BYD actually makes cheap affordable electric cars, and we both know why they are not sold in US.
>If not for SpaceX there wouldn't be gigabit internet connectivity in the middle of the ocean.
Plenty of companies were doing geostationary orbits with satellite connectivity. SES for one.
Any more Elon slop? You realize you are defending a dude that is literally a Nazi, right?
My response was to your statement “Give me one actual reason why a smart person would take an underpaid overworked position at any of his companies.”
I hated seeing him do the “Roman” salute and will not try to defend it. I said nothing in favor of his politics or personality, only that his companies are ambitious. Seems like you may benefit from a few deep breaths before responding with attacks.
Also, the alternative technologies you propose are pretty weak comparisons as they are of a different classes.
Your response was along the lines of "despite Musk's character, his companies do groundbreaking stuff, so in return for being overworked and underpaid, they get to work on things that no one else is working on"
My point is that none of the companies do groundbreaking stuff, and there are other options for people wanting to work at those.
> More than 4,400 current and former SpaceX employees are likely to become millionaires in the I.P.O., according to an analysis by Hill.com, a San Francisco-based investment platform. Of those, about 400 are expected to earn $100 million or more.[1]
Not to mention the whole launching reusable rockets thing which is pretty cool too.
I mean maybe the super smart person will work at GOOG/META/Netflix to do some absolutely ground breaking work stuffing ads and slop pixels into as many ocular nerves as possible.
However, I could see a smart person taking an "underpaid" (SpaceX SWE: ~$200-400k pre-IPO) to do the following:
Neuralink: to see the impact of increased independence and autonomy of a paraplegic one day after the operation
SpaceX: to quite literally approach the final frontier. Currently launches 80-90% of all orbital mass. Starlink is saving lives constantly.
Tesla: to kickstart the EV revolution and reduce fossil fuel dependence
Boring Company: to radically decrease tunneling costs applicable to all sorts of critical urban problems from transportation to utilities etc
Astra fails in similar ways, and at similar frequency, as GPT 5.6 Sol does. It often goes way out of scope, or just stops prematurely, or tries to find odd and even dangerous workarounds when it gets stuck.
It's phenomenal at computer use and 3D stuff. I've been using it less and less for coding.
Same, Astra is extremely RL fried, and nobody is talking about it. I used Astra for a few days on my personal project, and load times went from less than 3 seconds to almost 30 seconds because it kept using the wrong sync primitives and bad architecture overall.
Huh, I've had a totally different experience.
I've used it extensively, maxing out the 200€ plan on personal projects and it's the best model I've ever used, so easy and pleasant to use.
It's great for frontend design and using it in Rust I've had
Coming from Opus 5, it's a breath of fresh air.
Same experience. Astra is on par with or better than Fable 5.1 with a lot more usage on the plans. It has been an extraordinary experience using it so far. 5.6 Sol was very good and Astra is a large upgrade in quality.
Same. GPT-6 has been a huge breath of fresh air for me. Fixed 80% of the issues I was having with Sol. I just gave it the same task I gave to Sol a few months ago, and it knocked it out of the park comparatively.
LLM's introduces problems, and it finds them in its own internal thinking. But instead of actually modifying the previous generated answer to fix the real issue, it adds another layer to deterministically guard around it, greatly expanding the scope of the fix. This scales with effort, and the result is spaghetti and with a side of bugs.
Best to stick with a high end model + low effort, do a manual pass on high effort and fix the bugs you know are reachable.
It's really interesting how different the experience people have is with these models. I tried Codex with whatever they had before Sol and then with Sol, and just kept going back to Claude Opus/Fable because they were better at the coding work I was doing. Despite getting annoyed at the way it replied/wrote, it was just much better. Astra is the first one that feels as good as Fable to me, and it's much less annoying in its replies. I still don't think they have anything I'd want to drop down to like I can drop down to Opus though.
yeah I see this in these threads, I'm guessing the user prompts are the actual wildcard, it has been for my use thats for sure. edit: I wonder if gemini is somehow training me to like it more lol
I tried Astra w/ high reasoning on a design document project and it was horrible. It started duplicating output lines, made document edits without permission, and basically did a poor job writing clear prose. I went back to 5.6-sol and it's great. I'm an OpenAI fanboy and was severely disappointed. I hope Astra is better for coding.
I agree, the models keep getting better at one shotting. That’s useful in a lot of situations, like for small one-off scripts that filter/transform some tool call, or make a clever bash call. For the code itself, it doesn’t help me much though.
I think you're seeing a big shift around it.... since it's been markedly cheaper and also still easily available from OpenCode, it's getting large enterprise traction.
Not sure why you are being downvoted. Until Musk owns up to his Nazi salute, I won't have anything to do with Grok, no matter how good or cheap it is. And yes, we need to keep talking about this because it's absurd.
If you watch the actual video, you’ll see Musk saying “my heart goes out to you all” as he waves his arm in the air. The Left would love us to imagine he’s saying “sieg heil” or “exterminate the j3ws” or some such, but that’s far from the truth. The media hoopla around a freeze frame of someone raising their arm is a desperate partisan attempt to smear a political rival.
If Elon hadn’t worked with Orange Man Bad, then the Left would still be in love with him for his massive former donations to the Democrat political machine, and his work against climate change.
The whole “he’s a nazi” accusation is banal, and people are seeing through it now. That’s why we’ve moved on.
People continually fall into the trap of pushing a false narrative because they are so blinded by their own agenda.
Like the whole pizza parlor pedo basement thing, people will death grip stupid stuff because they are so desperate to manifest the worst possible image of those unaligned with them.
The problem is that it blows up in their face and just makes them look unreliable, dumb, and lost.
Musk has done so many objectively bad things that there is no need for people to dilute their reputation on fringe theories and interpretations. Pushing the nazi thing just gives Musk ammo that his detractors are so desperate that they need freeze frames and hidden context to make him look bad.
The Democrats are not a left-wing party, I'm not sure why you think "the Left" would be in love with him after all the other horrible things he's done if he just gave money to a political party that is at best centrist.
If you want him to get the benefit of the doubt about his "hand gesture" then it would help if he wasn't promoting far-right parties all over Europe.
It wasn't an accident. He did it deliberately. Twice. He enjoyed himself doing it.
There's no value in the mental gymnastics to invent excuses for his fascist salutes. The rational thing to do is to accept the objective reality of it.
Poor Elon put in so much effort into his Nazi Salute, he'd be pretty upset about you downplaying his best attempt, if he could read what you wrote here about him.
I've been using 4.6 for some one-off game mods/utilities and it has done very well. "I have a very niche keyboard (Moonlander) and I play this very niche space sim, make me a SVG keyboard cheatsheet for it". Told me to grab keymap.c for the keyboard and inputmap.xml for the game's key bindings, churned for a while, then spit out a pretty good first attempt, along with the python script used to generate it. Spent another hour of back and forth to refine the script, and now it generates great diagrams that will adapt as my keyboard firmware and game bindings evolve: https://files.catbox.moe/x0u76x.svg
Excited to try 4.7. I hope they fixed the "it's not X, it's Y" that showed up in 4.6.
Impressive! I had to peek at the SVG file and it superficially looks good, however, as is the case with everything AI, the more you look, the more it doesn't make any sense.
By now AI should know of the DRY concept. But no. Hence the keys have a rounded rectangle for the key shape and another rounded rectangle for a clip path, to prevent text overflow. There are 72 * 2 = 144 identical rectangles, when just one would suffice (in the defs), with this being cloned once for the clip path, and 72 times for the keys.
I would not expect SVGO levels of optimisation (rounding numbers, that sort of thing), however, the human, if writing out the same thing for the 72nd time, might think 'is there a better way', to get the manual out. A graphics program such as Illustrator would not do that, but AI 'should' because AI.
The above is not criticism of your work, just an observation regarding AI SVG capabilities.
Nice. Thanks for the feedback. I'm currently having it churn out a refactor so I can use it for other games, but afterwards I will tell it to use base key shapes and clone them for the keys. If I were writing this by hand I may have made the same mistake, not knowing that SVG actually has clone capabilities like that. The script does have the key geometry defined in a single place, and generates the SVG wastefully.
Congratulations on going down the SVG 'rabbit hole'!
There are also interesting inheritance rules with SVG, so you could define the basic shape of a key, well, several shapes, just as rects in the defs, with no stroke or fill specified.
Then, at the group level, you can then specify stroke and fill, so there could be a group of normal keys, another group for modifiers, function keys and so on.
Then there are the keys themselves, how do you clone a shape and put different text inside each clone? There are many ways to do this but I think you are on the right track using the clip path approach, albeit using the rects in the defs.
What is interesting about SVG is that artists don't care for the file format, they just see text as shapes on a page. Then programmers don't care for SVG as that is a graphic designer/artworker thing. So SVG sits in this witch-space, with only a few brave enough to wade in and do cool stuff.
Given your application, and given the fun that could be had with SMIL/JS, you could make your SVG files interactive, so you press a key and a popover tells you more about what that key does. You can even get audio working in SVG, as well as HTML popovers (in foreignobjects, as buttons, but working, nonetheless).
'Views' is another interesting SVG feature. I have a sprite sheet that uses a lot of views, where you are projecting your SVG into some type of virtual canvas, taking a 'picture' of it, and then incorporating that in something else, maybe a CSS variable.
One 'deadly addiction' is animation. Filters are another 'deadly addiction'. Why have a static and actually useful diagram, when you can animate it, move the 'camera' and add the equivalent of 27 Photoshop layers as filters to everything?
For example, supposing you wanted to show what keys to press, with there being modifiers and a sequence, e.g. 'Hello World!'. The animation for one letter could be what triggers the animation for the next 'key press' and so it goes.
My top tip of all: reposition the origin (0,0) to where it makes sense. Many objects have symmetry, so you can define one side, clone it, scale it (-1,1) and do it all around 0,0 to then translate the results to somewhere sensible.
I have found the JetBrains IDEs to be extremely useful for SVG, the preview feature is very helpful, as are the code hints.
AI sort of knows SVG, so I have had some suggestions from Google on how to build filters. These never work, but they do get you thinking. Say you wanted to use filters to add specular highlights and animated shadows to the keys, that would be fair game for AI hints on how to do it.
Additional prompt instructions: "Add scrolling clouds behind the statues. Dynamically light the statues based on mouse position. Use diffui to generate the normal maps/depth maps/roughness maps of the objects, and to separate out the assets on to different layers."
Overall I find these models are getting good at following image as a source of instructions, but their refinement of the output varies heavily between the models. Astra's final output feels more polished, has better visual contrast, and the animations between the pages are smoother. Grok also chose to light all of the background elements, which imo overcooks it a bit.
Still though, for the price it's a great starting point.
At every Grok release I commented on here how much I love Grok. It’s the consumer app and model I like the most, but my sentiment has changed. The usage limits on all the Grok subscriptions are now terrible, maybe because 4.6 and 4.7 (not in the app yet) eat more compote? I’m not sure what happened
My SuperGrok subscription previously easily lasted me through the week even with mild coding through Grok Build. Now when I use the app 1-2 times a day to ask some questions, I’m almost running out by the end of the 7 days. It’s terrible.
I want to keep using Grok but logically it makes no sense for me to keep paying for it on the side when my quota just doesn’t last. I have also no desire to upgrade to Plus with these terrible limits, while previously I would have eaten up a $100/mo Grok plan. Rumors say SuperGrok got heavily nerfed with the SuperGrok Plus introduction, and that sounds about right to me.
I’m sure it’s a great model and I’d love to use it. I hope they get their plans under control and only only focus on Grok Bot.
That's odd to me. I have SuperGrok with X Premium+. I use the crap out of Grok in my daily life, including to build a couple self-hosted apps as an amateur. I have a Grok bot monitor my email every 15 minutes and file things away for me. I have another bot that monitors for blood test results through Goodlabs. And I'm talking to it all the time on my 2 hour round-trip commute . . . and I never even get close to using my quota.
Opposite experience here. SuperGrok allowance is drained extremely fast. About 20-30 simple coding or code review prompts in grok build, and it’s over for the week. When using it via the Grok app, it can last longer, unless you need to edit photos. I didn’t bother to properly measure grok’s burn rate on the SuperGrok plans. It’s just not there yet.
I mostly use grok voice mode (on iOS) and share similar sentiments (just 1-2 conversations per day before quota runs out).
Even worse, the mere risk of quota exhaustion mid-conversation makes me not risk starting convos with Grok, instead I'll use ChatGPT or Claude (even though Claude is inferior for non-coding tasks, and ChatGPT is inferior for all tasks).
In fairness to xAI, they're a profit-motivated company like any other, so they cannot give us tokens for free or less than it costs them. Reality is we may have to simply pay a lot more if we want that Grok goodness.
For caching, only if you don't specify your preferred providers and let OpenRouter route each request itself. I have stuff like this in my OpenCode config for each model I use and I regularly get ~90-95% cache hit rates.
It still won't be quite as high as you'd get by just using DeepSeek because occasionally a request will fail and you'll get routed to a backup provider with nothing cached, but it's close enough not to matter in most instances.
But I can't argue with the lower off-peak pricing when using DeepSeek directly. The downside is they train their models on your input, which might be a deal-breaker for many users (as it is for me).
"Privacy#
All these models are hosted in the US. Providers follow a zero-retention policy and do not use your data for model training, with the following exceptions:
Big Pickle: During its free period, collected data may be used to improve the model.
DeepSeek V4 Flash Free: During its free period, collected data may be used to improve the model.
MiMo-V2.5 Free: During its free period, collected data may be used to improve the model.
Laguna S 2.1 Free: During its free period, collected data may be used to improve the model.
Ling-3.0-tiny Free: During its free period, collected data may be used to improve the model.
LongCat-2.0 Free: During its free period, collected data may be used to improve the model.
North Mini Code Free: During its free period, collected data may be retained and used to improve the model. Do not submit personal or confidential data. See the provider’s Terms of Use and Privacy Policy.
Nemotron 3 Ultra Free (NVIDIA free endpoints): Trial use only — do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about data processing practices, see the Privacy Policy. By interacting with this endpoint, you consent to the collection, recording, and use of such information and the NVIDIA API Trial Terms of Service."
just checked, yes they don't seem to provide that information, most other providers are advertising fp8 or fp4 which is okay, but "together" doesn't, so they are likely using fp4
update: coreweave/fp8 is at 191 tps, launched this morning, but really bad cache hit rate (~60%), coreweave is good for privacy but let's hope they improve cache
I use it on fireworks which is US/ZDR and pretty reliable. We run a few hundred million tokens/day through it for dollars. Many are cached, which is super duper cheap.
Define easy. I am running 40+ probes to crack the best compression algorithm, and I spent $3. If you surgically tackle the problems, you can do really complicated work for less money than by assuming a frontier top model will one-shot everything.
Well, at least I spent lots of dollars, and I had to use those models the same way I am using local and cheap models, with the same results.
Right now I'm using several different models for reverse engineering (DS V4.1 Flash, MiMo V2.6 Flash, GLM-5.3 Flash, etc.), and so far none of them are able to finish the task - it's been ~1.5h and several dozen million tokens used, but still struggling with the algorithm (FFT and some other stuff on an image manipulation library, which appears to be hard for them).
On the other hand, Grok and GPT finish these tasks in <5min with no issues, and significantly better output.
It's a real dud IMO, worse than 4.6. I told it to fix a depth-testing issue with a WebGL scene and provided it a screenshot: told me it was fixed but it wasn't. I tell it to try again and it says it's "FOUND THE ROOT CAUSE!" then hasn't fixed it.
I told it to compose an image (putting headgear on top of a head) - kept getting it completely wrong, generating new headgear, getting that wrong and screwing up the scaling.
I told it to diagnose a webhook issue that was happening in production from a local environment and it kept giving me moronic answers like that environment variables weren't set (despite me telling it that the values WERE set in production).
Most people who comment positively on AI are either shills or people working in the AI industry (gotta keep the bubble expanding). The OP experience matches mine with most models for any kind of serious work. In fact, it was the reason why Claude was previously successful because it was the most railed model.
I've tried the latest models across OpenAI, Claude, Chinese, etc. They just do stuff. That's not how work is though. You want them to do specific work, at which point it's a real hassle to follow up on all the garbage they have been outputting.
No doubt xAI has seen rapid progress, but it's been several months of them being "just behind" OpenAI and Anthropic. It seems the gap between just behind the frontier and pushing it is a lot wider than most people thought it was a year ago, and that's why a clear third contender in the frontier model space has yet to materialize.
Every Grok release obscures their cache pricing while highlighting their input/output pricing
From their headline comparison:
Grok: $2/$6 per million
Fable: $10/$50 per million
What this doesn't say: Grok costs 0.50/M cache read, Fable $0.25/M cache read
Long running agentic workflows are dominated by cache reads.
Just makes Grok sound deceptive, and more importantly, reliant on user's lack of understanding of costs aka predatory (which in turn is more infuriating)
Is anyone treating Meta's offerings as a serious contender in any real use case? Zuck and co are burning cash hard to try to get people using their models after falling off the wagon for a couple years. It would be wild if those prices aren't total loss leaders.
Same reason Coca-Cola only mention Pepsi and Pepsi only mention Coca-Cola.
It's an proven way to capture the market. You would rather split the pie in two rather than in 4,12 or 50 right?
If the CursorBench 4.0 score diagram is the headline, I read it as "Grok 4.7 xHigh is almost the same as Fable5.1 on low".
Is there a metric for like... time taken when comparing these two? I see score and cost.
If Fable5.1 can knock it out more quickly on low but Grok4.7 might take twice as long to stumble through a problem (and leave behind a bunch of yucky comments or un-needed extra unit tests), are they really comparable?
Or like... the "quality" of the solution? "It works" versus "it's unmaintainable/very messy/hacky".
I've put Grok 4.7 on the Redactle LLM benchmarks. It's a bit of a silly eval since it's a puzzle game but it tests omniscience really well.
Grok 4.7 is near the top of the board. A significant improvement over Grok 4.6 but still not as good as Gemini 3.8 Flash which is very cheap and fast too.
Codex has become my goto tooling. I used to be a Claude Max subscriber, but I was becoming disappointed with the quality of the output from Opus 5. Fable chewed through my usage too quickly to be practical. Moving to a Pro account w/ Codex was a big improvement. Sol had great output, and the usage was more than sufficient for most of my needs. However astra does tend to chew up usage, so when i've done to much of that, and it's became an issue Grok Build has beocme my second go to account. The output especially after the cursor purhcase has become quite good, and the usage has always been very generous.
There are some users reporting it improved a lot in the last few weeks. The max sub usage for Grok is around $12,000 of API pricing now, so a 40x multiplier for the $300 plan.
It is the same multiplier for Sol with subscription. For Astra though the multiplier is ≈20x, so half of Sol usage.
For Claude it seems to be ≈40x too for Opus, but less for Fable (similar to Astra in GPT).
All on the most expensive plan. Previously, Grok usage escalated linearly from the $100 plan to $300 plan. That would be a really good $100 plan if it is still true.
Either this is untrue or my account is in some bugged state. I bought the 300 plan 3.5 weeks ago, and found it's usage about 1/10th of others, running out always the first day of usage for the whole week while CC for example would last 2-3 at higher usage.
It reset just a few hours ago and I've been running it, couldn't be more than 15 sessions none more than an hour long:
---
Session usage: no model calls yet in this session.
Weekly limit: 46%
Next reset: September 27, 23:20
---
I actually have to believe my account is messed up tbh, it's so bad. For reference I've ran 12 fable and some ~40 Opus sessions since reset yesterday on a CC account, at least 5x more usage by my estimate:
Current week (all models)
28% used
Resets Sep 28 at 5am (Pacific/Honolulu)
---
Ok looking at it more, Grok and Grok Build just really suck. They are about 10x less token efficient, often using 200+ tool calls in a row for what are not even big tasks where Opus would use 5-10. Their cache hit rate is worse, and two sessions got into basically unnecessary loops costing a solid quarter of the entire week. And this was on smaller tasks as I tend to use it for easier things.
I find I can just about get by with coding every day on a Cursor $60/mth sub with Grok fast mode disabled.
Doing pretty heavy coding work/requirements etc, but not much sub agents and no loops.
For me and what I’m doing that’s insanely good value.
I find grok build chews through my SuperGrok sub very quick - but I think that is due to it having the 500k context window which uses more credits. Cursor limits it to 256K (tho I see in today’s update for Grok 4.7 there’s now a toggle for context size).
It used to be good, now the limits are very underwhelming.
Normal SuperGrok barely lasts me through the week with very mild usage and no coding. The sentiment around SuperGrok Plus is also not great and I haven’t seen someone saying they’re happy with it yet.
SuperGrok Heavy is $300/mo, so you could get a full ChatGPT Pro and Claude Max 5x for that price. That’s so far out of my budget for a single provider I haven’t bothered trying it.
I still have SuperGrok through X Premium+ but will downgrade that next billing cycle
Well when I ran out of Grok SuperHeavy subscription ($300) once and tried to use extra credits to cover half a day remaining till reset, $50 in extra credits went in two hours. Based on that, subscription definitely lasts longer; Grok subscription just about covers a week of my work (sometimes a bit extra remains unused, sometimes it runs out half a day to a day early). And as a point of comparison, it lasts for doing same tasks as 2.5-3 weekly limits of Codex on 5.6 Sol did (using xhigh on both Sol and Grok); I needed 3x$200 Codex subscriptions to cover my weekly usage.
There are two ways to subscribe, and it’s very confusing, but the best value is to get cursor ultra for $200 a month. I basically have infinite tokens with that plan, plus grok bot, which I really like
Either way, the fact that xAI or SpaceXAI or whatever the name is, I can commend the team behind it on their rapid ascent and progress by being close and or on the frontier in several respects.
There for awhile it seemed like we’d have 3 big competitors but then Grok 4.2 or 4.4 was just diabolical while OAI and Claude continued their significant improvements. Grok was/is so bad that I was convinced musk was gonna shut it down and just fund Anthropic compute once they reached their compute agreement.
which is crazy because this was grok's competitive advantage, worse than OpenAI models but better than everything else, now it's less efficient than Opus or Fable 5.1
As anthropic/openai subscription allocations get squeezed you'll see more people using "second rate" closed models like grok. The token allowance with a Cursor subscription is crazy.
Any real world experience with Grok Ultra $300 monthly subscription vs Claude Code Max in terms of overall built work mileage, or general token limits?
the AA numbers are generationally bad. double token use (the one thing Grok was good at was low reasoning usage!) to gain 5% in the benchmark score. with reportedly a larger model. maybe it shows gains IRL but wow, I've never seen a new generation model look so underwhelming compared to the last.
as someone who is limited by amazon bedrock support at work (no idea why we got stuck with the worst one) - grok is literally the only budget-ish model option, so nice to see it updated, Sol and Opus are just too rich for my blood. Luna is good but so slow at getting things done (tps wise it's fast)
Are the prices on Bedrock substantially different to the rate cards of the direct APIs? Just trying to understand whether this is Opus-through-Bedrock is too expensive, or Opus is too expensive.
I tried in Omp (Oh-my-pi), and so far it's really problematic.
It will loop in thinking mode ("Let me implement those fixes: Fix 1, Fix 2, Fix 3 .... Fix 80, Fix 81"), ignore the AGENTS.md instructions, corrupt plan files, etc etc... I have 5.6 Sol as advisor/watchdog, and it blocks every turn, I never saw this. Quite a shame, 4.6 wasn't so bad.
Probably the same reason as oh-my-zsh, you don't need 90% of it. Further compounding the problem in an agent harness is that you are polluting the context window by throwing the kitchen sink at it.
- it allows different models within one session via roles (I only have API, so pay per token)
- it's much more likely (ime) to use the LSP over grep for determining how code fits together
But I agree a 20k+ starting context is way overkill.
I find it's very hard to get information on harnesses people are using. I have to stay model agnostic so I avoid claude, codex, cursor, etc. I've used and tried opencode, which worked well, but obviously lacks the above features.
Does anyone have a resource for following what people are actually being productive with? With so much vibe going on it's hard to separate the wheat from the chaff.
The CSAM generation model got an upgrade. The sad part about this is that I bet it still generates CSAM. Given that the owner of the company has made a nazi salute in public and thinks CSAM generating models are cool, I don't think they addressed the issue of this generating CSAM.
In my experience Grok especially inside Grok build is pretty solid choice, it’s a no nonsense model and stays on its course. Another surface where I truly enjoy the experience of using Grok model is Grok bot
I've had really good experiences with Grok 4.6 and grok build. I've been playing around with tscircuit and it can write code with an understanding of spacial reasoning, while also importing cad components from different file formats into tsx, I've been having claude come in and try to error check it and so far claude hasn't found anything to improve in my three projects.
I'm excited for 4.7 although I share skepticism with other users whether 4.7 will be significantly better, since they didn't raise the price.
Yah, I am pleasantly surprised at Grok Bot. Hopefully this improves CUA which has been a touch lacking w/ Grok 4.6. Grok 4.6 works but is slow compared to stuff like Astra Light.
This explains why. Mentioned in another comment, but cursorbench explicitly tests with Cursor as the harness, and OpenAI doesn't allow them to use Astra in Cursor.
Cursor never added Astra to its consumer subscription plans. And it's likely exactly because of this announcement. Why would they add support for a model they would have to remove shortly after?
That's not accurate. OpenAI doesn't allow Grok to provide Astra to Cursor customers anymore, but it doesn't ban anyone from using Astra via alternative harnesses.
If Cursor wanted to include Astra in CursorBench nothing would stop them, they could easily have spent half an hour vibecoding in OpenAI API key support - if it hadn't been convenient to neglect to do that.
Even if they could do that (workaround to include Astra in CursorBench), that has no practical consequences for Cursor users and that's what I as a Cursor user (what I use for dev, though I use ChatGPT for non-dev stuff) care about.
It would make the benchmark way better obviously, by showing how their new model compares to their competitors, the whole point of benchmarks and graphs.
The point of Cursor Bench is to show how models perform in Cursor. If 99% of their users won't be able to access a model unless they go out of their way to include setup an API key for it (which would be insanely expensive with Astra), why would they include it in the benchmark?
If the benchmark is "what's the best model to use in your Cursor subscription", why would they do that? OpenAI knew what the effects of their decision were. Hard for me to have sympathy for either party here, honestly, and I say that as someone who is a customer of both.
Deceptive? An extremely quick google search would answer your question. OpenAI pulled out of Cursor before they released Astra so it never got that benchmark.
I wonder if that means that SpaceX evals show that they consider astra better than fable or that they hate Sam&co so much they don't want to show their stuff.
Its because of this. You can't use Astra in Cursor, and cursorbench uses cursor as the harness. They can't actually benchmark it using their harness hence why its not included.
I refuse to use Grok. Mostly because of the usual reasons - somehow this high profile AI model seems more disgusting than others and it is in a way impressive.
But also Xai doesn’t seem to care about user experience and long term support.
I am subscribed to ChatGPT, Claude, Kimi and GLM coding plans. 200$ one on GPT and the 20$ ish ones on all others. Recently added Grok and it has somehow bacome my second most used model.
For daily one off questions I prefer it because it is fast enough and I like the way it responds. I also use it for basic research like “find me a battery drill for this and that”.
Kimi and GLM feel extremely coding oriented. I use them for code reviews basically. I hate the way Anthropic models talk. GPT takes too much time and effort for that kind of stuff for some reason.
You should try it, it is less sycophantic than other models and is faster and better at most reasoning levels, don't confuse the twitter bots and services also named Grok with the frontier model itself
I can't take anyone seriously who uses grok seriously. I like to look at the cybertruck owners forum every so often because it's just... hilarious. And the amount of superfluous grok use over there is just insane. Half the posts I click in there will have a bunch of people dumping entire grok takes "why do people hate cybertruck owners?" "Because they're jealous and poor," sort of stuff that they just LOVE to post.
As a technical point of reference to compare against other llm stuff, sure, I'll glance at a report or benchmark but I really couldn't care less about anything to do with the project and it could blow other options away and I wouldn't touch it.
I don't know man, Musk doing Nazi salutes doesn't seem that superficial. He did help get Trump in power and also killed a lot of aid to children that need it.
What's superficial about refusing to use a product from someone like that? Or are you one of those 'technology isn't about politics' people? That's a superficial take if you ask me.
All technology is political, and understanding that is a deep, not superficial take. It requires systems thinking which unfortunately many people building technology seem to lack, despite software being a sophisticated complex system.
I've never tried Grok and I doubt I ever will. In a world where trust in tech is at a low point, x.ai is pretty much the lowest of the group for me. I can't imagine using this for any production use-case, especially one where bias issues could cause litigation fears.
edit:
My post was flagged (original above unchanged) This is exactly my point about lack of trust in x.ai. My suspicion that a bot from that platform flagged this is exceptionally high. You couldn't pay me to use this platform.
Seriously. They already get caught uploading everyone’s private credentials once before, one would have to be a particularly gullible rube to trust grok again. Especially with musk in charge.
Have you considered that the single most impressive breakthrough of LLMs as a technology is their ability to generalize beyond what they were explicitly trained on? Great analogy, pal, but LLMs aren't cars.
Can you point at the marketing in this release to show me where that’s the lean?
Many people are allergic to “AI safety” as they perceive it as an attempt to deceive them. When they ask a factual question and get back an unfactual answer, it makes them upset. None of the people I know who feel this way are searching out CSAM. They accurately perceive that there is a team that wants answers to come out a certain way.
For instance, I’m loosely connected to people who care about animal safety in AI research. There are absolutely people spending their time pushing a narrative about _the_ ethical way to interact with animals. Feeling this not being forced onto you is kind of nice.
I would guess those working in AI see some possible ethical quandary but resigned themselves to an attitude of "it's happening either way".
Although what csam and racism are we talking about? my observation on AI is they're all pretty cucked and boring to talk to.
Or is the grok ai more liberal than others and unique? I used it a year or so ago when it came out and it seemed as gated as all the others.
Until Musk owns up to his Nazi salute, I won't be using Grok, sorry. I don't care how good or cheap it is. And no, I won't stop talking about it either.
There is no need to use it anyway, it's always been uninteresting in terms of performance. However, for me the red flag was when Musk admitted he will personally interfere in its training and prompts to make it more of a propaganda tool. I'm interested in science and reality, not in the political delusions of elderly drug addicts.
I bought a month of use for $100. Early impressions of Grok 4.6 was that it's good at talking about ideas (got me unstuck from a piece of writing that I was working on; that bought it a TON of goodwill) and just okay as a coding tool compared to my more extensive use of Fable and Opus. Not as smart as Fable but cheaper; not as capable as Opus 5 but way less annoying along the way. And it generates images, which Anthropic doesn't do.
Not sure if I'll hold the subscription but I could see myself working with it more.
I use it in the car to talk to because it's built-in, mostly for navigation via voice. It seems to be an old or quantised model, because it seems a few years old, and it has strict rate limits unlike Gemini, where it really just shuts off if you talk to it a few times in one day, but it's still fun to show passengers who are still new to LLMs.
Sorry, english is not my first language. Itss disabled on our work API instances so my use is strictly personal because it was available on Cursor (my account is pre-acquisition). I have extensive AI experience across nearly all models, open weight and frontier and closed, I am very aware of how they talk or output. This is high/xhigh, via Cursor, not via X Grok/UltraGrok if that make different.
Grok 4.6/4.7 feel like you are less tokens because Cursor gives you double the quota subsidising Grok specifically - there is a separate Grok/Cursor model quota bar in addition to non . Its actual token drain if you are paying API rates is generally far higher than Fable, Astra et al. You are not using less tokens.
It is weird in some reward way, it will frequently, at least for me, complete the task in the laziest way possible,Technically it is done, but that's about it.
For example a user registration system ended up with users being able to log in as anyone because the authn was a cookie set with the user's pkey id, unsigned. Nearly anything it outputs technically works but if you give it a GLM or DS pass you will find dozens to hundreds of vulnerabilities of varying hilarity (Fable refused, Opus refused).
I have seen it write SQLI-vulnerable code, asked it to review a file without saying what's wrong and it did not catch it (fresh session, single file @-tagging in harness). Again, technically, the code works and does what the prompt asked, its just handing in some of the laziest copied homework I have ever seen.
If you specifically call out to use prepared statements it will typically put a plaster over this however I have also seen Grok 4.6 use prepared statements by concenating the user input raw into a statement then executing it with no ? or named replacements, rendering it somehow a SQLI-vulnerable prepared statement. One med it added a OR 1=?, replaced the ? with another 1, then said OK you are using prepared statements now.
The only people I know of in the UK who will tell you that they use it are performatively alt-right or right wing. The kind of people who say "nanny-state" or "wokerati". GB News viewers. People who have an opinion on Meghan Markle that they think other people need to hear.
It's just an observation but so far a pretty solid correlation. Musk has so severely poisoned the well in terms of his UK reputation that the only people who are open about using Grok are... well, wankers is as good a word as any.
FWIW among the AI-using people, it mostly goes Claude Code, then Codex, then whatever runs on their Mac. The only Cursor user I knew has jumped ship to OpenCode.
I used openrouter to send same prompt to qwen, derpseek, gemini and grok and found that grok does good research and produces less bullshit, especially when prompted to be critical of an idea
As stated by another comment Elon Musk's mother posted an AI-edited photo marked as such. It got edited right away to remove that label.
There are ample reasons to believe that Elon Musk is running his mother's account and that the photos weren't even real putting in question that he even had a birthday party.
If you ask Grok about what this means it will always take Elon's defence. It will vehemently deny that Elon would be capable or willing participant of such a thing even if you point out that he faked being a world class gamer, buying accounts that had done all the work and showing none of the skills when live-streaming.
> There are ample reasons to believe that Elon Musk is running his mother's account
Yeah, I'm sure the guy has time to run his mom's social media account. What's your reasons or evidence? Did you consider maybe it's a social media manager one of them hired running the account?
I would consider this a positive. I'm not interested in a company that wants to prevent you from using a tool that you're paying for.
The value of the internet is that people can share whatever they want, and use software how they want. This will mean that some people will abuse that. This is the tradeoff of a free society.
This has been my experience as well. Grok will end tasks almost immediately and claim "Done!". It's definitely the laziest and most "dishonest" of all the models. The others aren't perfect, but I can't use Grok for any serious coding task.
I have to say I'm a little perplexed by HN's perpetual willingness to use grok like it's a normal product made by a normal company.
There's often frustration that every thread related to a Musk company includes a discussion about Musk, but Musk himself caused that by being the only tech founder to actively campaign for Trump. (Zuck, the runner up, didn't do anything even close to this). Every product at every company he owns is hopelessly tethered to his decision to do that, and deserves to be judged on those terms.
Another popular story today is about US rollback of climate regulation [1] under Trump. Some fraction of every cent you spend on Grok goes to support stuff you hate, and yet people get genuinely annoyed when you point it out. Musk and his companies really _are_ special and should be treated as special.
Every thread about a Musk company or product needs a comment like this one. If we had the right values, every comment would look like this one.
Thank you for your perspective and I agree as repetitive as it is, I hope hn can continue to surface disagreement/substantial views on a topic.
These comments don't stay up much anymore and I can't tell if it's structural to the forum (flag weight + statistical mechanics of votes + guidelines) or if it's the userbase sentiment.
Except for now HN doesn't do that. Every single comment that points the issue with Grok being built by a pro-fascist team is being "locked" so that they can't be upvoted
For what it's worth, I've watched the vote fight on my comment swing back and fourth over the last hour. It got flagged, unflagged, and flagged again. It appears to now be locked and dead.
But I think it represents real malaise in the community. It's not a moderator plot, people here really just don't care and might even support this.
We really are in the minority of opinion for giving a damn about liberal democracy.
I think I was trying to bring up the mechanics of the forum as another reason.
Between the guidelines + user thoughts (e.g. repetition, low novelty/new info), there's other reasons these types of replies might end up dead.
I am worried that it leads to people self selecting to other forums biasing the remaining userbase vote/vouch/flag distributions. In an exit vs voice situation, the voice kinda dies out. Then we end up other-izing people and homogenizing our communities.
But I concede it's also possible that the minority opinion issue could be the core driving force.
I completely agree. But this has been true for many years. This sort of head in the sand compartmentalization seems to be a core feature of the culture here.
I think I already made my point, but I'll make it again.
Nobody both worked and spent their money to get Trump elected like Musk. 300 million to his 2024 campaign [1]. DOGE. On-stage endorsements. Nobody even came close.
No, other big labs are not "innocent little virgins", but they're not even in the same solar system of harm as Musk. To hand-wave at the differences is to permit them.
How many years will go by before people will stop talking about the CSAM thing that happened for only a few days as if its still happening? FWIW, it's bad it was generated, but equating it to harming of real children I think is not a good thing.
And methane is a large percentage of all power production in the US. So again that also applies to all the other data centers. (And FWIW they've been winding down and shutting down the on site methane generators.)
It’s not just that it was generated, it’s that they argued in court, _and won_, that it was legal, giving every last predator a nigh-on unverifiable defence.
Is this an ad for Vals AI? Looking at their website, the rankings don't mesh with my observed utility for almost any model outside of fable and astra being good-ish.
Think we all can agree he has had staggering successes, but they have all come from having massive capital from Paypal which wasn't anything super innovative, it just solved a convenient problem at a convenient time and was awarded handsomely. Elon has put his capital to work in various ways to become successful, not all of the ways being morally sound.
About half of SpaceX revenue is Starlink subscriptions. Starlink is the one profitable division; the rest of the company operates at a loss, including xAI.
I don't know that's moving the goalpost, SpaceX's mission was not that originally. Some could say the original mission failed and they are pivoting, Elon will say it's a means to the end of the original mission still to save face. Some read it all as snake oil
As if "the public" knows literally anything about how the US federal government is administered.
If anything, they voted for reduced debt burden and they got the opposite. DOGE failed at pretty much every single one of the goals that the public arguably gave it a mandate for.
Ah, yes, democracy!, except for when the public is wrong.
Who decides when the public is wrong? We do! Who decides "what the public voted for"? We do! So we are the rulers? No, of course, not, this is democracy.
You want to become the decider of when the public is wrong and of what the public voted for? TYRANT! TYRANT!
No, the claim above is "I know the voters' intent behind their vote based on who they voted for."
This is simply epistemologically incorrect. It's obviously incorrect in this case because voters writ large do not have any idea how the government is administered and how to improve it, so even if they claimed to be voting for that, it would not necessarily be an endorsement of any particular approach.
More specifically we know it's not true in this case because there are polls. Voters didn't even claim to care about this! "How the government is administered" was not a high salience issue to voters. Simple as that.
Nonetheless, I didn't suggest anything about overriding their votes. It sounds like you have some sensitive spots to work through (someone obliquely criticizing your idol for sucking at his job?)
Well I "tried it out" I asked it one question, and it gave no answer and said "Sign up to use more!" I don't think I'll be doing that, no.
I can't think of a single dimension grok is winning on (capability, cost, voice), but want to stay open-minded -- anybody want to vouch for its capabilities in any domain?
If you haven't used it, how do you know if it's winning?
I think it's winning on UI for normies (grok bot) and they made some claims about being pareto SOTA (lowest cost per task completed) a while back with 4.6.
I find it to be a perfectly capable model for implementation (there are many in this class--deepseek flash, spark1.3, luna, etc). I find the usage to be very generous w/ supergrok. I find the model to be just fine for 90% of what I want to do, but I use a smarter model to plan complicated things.
After the cursor aquisition it's become a quite capable coding model. If you take cost into account, it's close to the top. OpenAI is maybe still #1, but I'd put Grok at #2 (again, including cost as a factor).
For me it works well for agentic coding tasks and terminal/unix/bash (in cursor and grok build); it's also token efficient and cheaper than gpt 5.6. It's def not as good as Fable for me (I haven't used Astra much, can't comment). So it's not the cheapest, not the most capable, but it has a good mix of it for my backend, go, infra work.
The voice is the weird part. The early Grok 4 models had a very distinct presentation unlike anything else out there. Then suddenly it made a big jump in coding ability and started sounding just like every other model.
> it's also token efficient and cheaper than gpt 5.6.
Deepswe results show that grok 4.6 is more expensive per-task and consistently scores worse than: luna xhigh, glm 5.3, astra low, sol high/xhigh, opus 5 medium.
Grok also used almost 3x as many tokens/turns to complete tasks than all of those models (besides luna), so it takes way more time to complete a task.
There isn't much reason to use Grok at all, it's gotten better but it's still worse than every other player in the field, which shouldn't be a surprise considering until about a year ago they were just buying tokens from other providers and pretending it was their own model.
With gpt-6 luna and sol coming tomorrow it's going to look even worse too, especially if new luna retains the same dirt cheap pricing that 5.6 luna has.
Apparently Grok 4.7 has 40% more weights than Grok 4.6, but the price ($6 output token, $2 input) is the same.
Given that the decrease in their margin and the fact they delayed the release of Grok 4.7 almost two weeks past the original date, XAI must not have been happy with the results for 4.7. And XAI also waited the day before Opus 5.5 is rumored to launch. I imagine Opus 5.5 will blow Grok 4.7 out of the water benchmark wise.
However, I have become skeptical of benchmarks. Grok 4.5 solved some issues setting up a buildroot system that Fable 5 couldn't do. I find the post cursor groks are phenomenal at frontend web development, though Claude is much better at backend ruby.
My favorite part of the new Groks has been how they speak in plain english. I simply cannot stand Claudish. Or even GPT, which doesn't have Claude's ticks but definitely likes to handwave explaining technical concepts. Still, nothing beats Claude 3.5 and 4 with explaining since it seems all models have regressed. I wonder if Grok 4.7 will also regress with English because of all the RL.
> My favorite part of the new Groks has been how they speak in plain english. I simply cannot stand Claudish.
Grok has its own feel too. It's not as bad as Claude, but one of the things that bugs me is that it is far too terse.
It regularly seems to come up with terms and descriptions for things in its chain of reasoning and then uses these terms in its output assuming you understand what it's talking about.
I find I often have to ask it to re-explain what it means.
> It regularly seems to come up with terms and descriptions for things in its chain of reasoning and then uses these terms in its output assuming you understand what it's talking about.
GPT does this all the time, too (both Sol and Astra). I constantly have to tell it to not use terms that were not part of the initial prompt.
I don't know how people are managing hands-off with Sol/Astra over long horizon tasks. It will come up with 100 new concepts/terms and then use them as if you've been following every Edit call for 24 hours.
It’s probably an assumption baked into the training pipeline from that ancient time six months ago when we mostly were manually following each edit tool call.
> I constantly have to tell it to not use terms that were not part of the initial prompt.
Hah, yeah even when you put it in AGENTS.md or a skill.. constantly having to remind it.. "what does AGENTS.md" say about doing that?".. Thinking.. Thinking.. "Oh, it says I should never do that, I'll remember that next time.."
Next session - same thing.
I just got DeepSeek V4.1 Flash on our Azure Foundry w/ Pi and I found its tone to be refreshing.
Separately have been using Grok 4.6 for a bit and it's also pretty concise.
It’s frustrating that we can’t see the “thinking” - it’s like we only have access to half the conversation.
Devin shows model thinking.
I’m pretty sure the big bois don’t do it because it would undermine “confidence”.
Seeing a model output “Oh I should just delete blah. Wait blah is a production service, I shouldn’t touch that. Maybe I can gain access to blah? Oh the aws cli isn’t signed in to blah. I see kubectl has access to blah though! Wait, I should ask user permission first.”
Yeaaaaah. Thinking tokens are fuckin’ wild.
Idk I feel like the more likely answer is to prevent distillation. Having the thinking is definitely better UX (oftentimes, I don’t know if Codex is just hanging, which it often does, or working in silence).
Running some models locally and seeing these thinking tokens was quite the experience. I never saw an LLM so "unsure" about virtually everything.
I doubt most users would look at them if they were available. More likely they don’t want to stream distillation material.
I stay much more hands-on when I'm using models that display full reasoning traces. And I tend to get more things done as a result, because I know exactly when it thought of a good solution that it talked itself out of because of some invalid assumption.
Could be something very stupid like - "I don't have ffmpeg available here. Should I install it? No, I can't. I'll proceed doing something that will take me 100x more tokens and wall clock just to avoid adding a dependency." I can then just stop and say - you've got nix flake there, just add it.
That's impossible with western models. The only way is to ask why it did something stupid when it already spent 50% of your weekly quota and produced millions lines of slop.
Oh yes, I’m 100% with you. I wish they’d keep it. It’s better for users but perhaps untenable for the business.
Ah, but you CAN see the thinking if you are willing to risk your account being banned. You just have to expose a "tool" with a specially crafted definition.
You can double click on the 'thinking' text and it will expand and you can read it. The problem is that it will often have multiple thinking/tool call sections and it can be a needle/haystack problem to find the one with the thinking you are interested in.
We don’t have access to the real reasoning text for most closed models these days, mostly due to distillation threats
I wonder how much of this is due to reliance on Twitter data. Or even just RLHF from humans that have a preference for Twitter style information.
SpaceX is a defense contractor (I don't mean this in a bad way). When the whole DoD/Anthropic thing flared up, I can guarantee you that SpaceX.ai was the first company invited to take their place as DoD AI provider.
I suspect that they specifically train Grok to be able to work well with military personnel -- speaking the way they speak: brief, to the point, efficient communication. Personally I really like this. Claude sounds like some demented clown from the marketing department.
I like communication that is brief and to the point. The problem is when it is so brief that the point isn't conveyed well.
I don't think it's twitter. My guess would be that it's been trained for conciseness as way to improve token efficiency in the same vein as caveman.
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> It regularly seems to come up with terms and descriptions for things in its chain of reasoning and then uses these terms in its output assuming you understand what it's talking about.
I’ve noticed Astra doing this a lot as well.
> it is far too terse
Anecdotally, I have noticed the same in the past week. It might just be anecdotal or driven by a long context window.
Tell it to "explain it like I'm autistic" and it will structure the explanation with term definitions up front.
FYI a quick fix for claudish is to ask for the response to be in ASD-STE100 (Simple Technical English). Then it is far more readable. But I would agree that this is an annoyance and shouldn't require user workaround to get something readable.
I think this is more a meme than anything else, for a couple reasons:
First, after a while it's just as grating as Claudeish. Second, my hunch is that it constricts the actual thinking of the LLM, like the same way that Newspeak does in 1984. It shrinks the range of thought that can be expressed if used as an input.
I think the real way to do it is to have another Claude entirely deal with the user as a liaison, but to keep the thinking in whatever format it came in.
Latent space reasoning, if you think about it, is exactly this to a crazy degree: why even formulate a thought as words if you can just keep it as matmuls until the user needs it? And then, if the user needs it, have it always specifically formulated for the user by another LLM rather than constrict its range of thought? Anyway, that's my take.
The fact that it might affect quality is something that is on my mind. In fact, I have mainly been using Astra after being primarily on Claude for several years exactly because of this annoyance. Ultimately, the model (at least for coding purposes) should just... not have this writing style.
I do think an infrastructure where another Claude retranslates the output would be better. Oftentimes I forget to put it in the actual prompt and when I receive back 8 paragraphs of Claudeish I ask for it then.
I would have to disagree that it gets as grating as Claudeish though. Its just direct and professional instead of ring-around-the-rosy clickbait.
The Claudeish drove me back to OpenAI and Codex as well. I find the Claudeish can be improved but it’s impossible to fully mitigate. Opus is unusable for anything I’m going to read.
“I would have to disagree that it gets as grating as Claudeish though.”
It’s hard to imagine anything more grating than Claudeish. To quote Rainer Wolfcastle, "My eyes! The goggles do nothing!"
> my hunch is that it constricts the actual thinking of the LLM
I've found that prompting any constraint on output (length, style, vocab, even simple formatting) not only places additional cognitive load on the model, which burns some of whatever cognitive budget is available, it will also often skew the output in other subtle and completely unrelated ways.
Since I found this artifact interesting, I did some pretty extensive experiments a couple months ago. The increased load is real, although it may not be apparent if you're not near any cognitive boundaries. The subtle skew, however, seems nearly ever-present regardless of load.
Can you give any further details or metrics on your tests?
When I noticed web chat LLMs wouldn't number section headings correctly and consistently, I began experimenting with modifying the user prompt over a period of weeks. My usage at that time was research and learning not coding. In long, detailed sessions with branching sub-topics and deep follow-ups, I found it helpful if the LLM would number each major section and letter each sub-section in replies. Simple markdown formatting that most web chat LLMs do sometimes, but not consistently nor uniformly.
While extensive, my tests were just following my curiousity, not controlled, exhaustive or well-documented. I identified about a dozen prior sessions of varying length and complexity to test and downloaded them with a browser add-on. I then removed all other user prompt instructions except for the formatting instruction. A test would typically involve changing the wording of the formatting instruction ranging from brutally simple to detailed and complete, then starting a new session, seeding one of the test sessions and continuing it. To get a feel for baseline inter-session variation, I also tried running the exact same prompt/session multiple times back-to-back, at different times and on different days of the week.
Once I identified a promising prompt candidate, I'd make it the formatting instruction in my regular, daily-use prompt for a few days. I quickly got a feel for how seemingly minor user prompt variations impact response quality, compliance and tone across fresh sessions as well as those in various states of context rot, drift, decay and cliff (<--my nicknames for the distinct flavors of session degradation, not technical terms).
My overall conclusion was that every instruction, no matter how minor or unrelated it seems, has some, real impact on the model's cog load, attentional focus and/or attentional weight budget. Both how these impacts manifest and what causes more or less impact is often extremely counteriintuitive. To more fully understand this, I eventually, got to the point of testing null case variants, such as the entire user prompt being one sentence completely unrelated to text formatting or the session topic, like: "Don't reference the cartoon character SnagglePuss" (in a deep dive on ancient Sumerian clay tokens). Similarly, a simple one sentence prompt requesting something the model already always does naturally also has a cost (eg "Capitalize proper nouns"). As others have observed, heavy emphasis, absolute prohibitions or emotional weight in prompts also tend to have outsized impact in both skew (impacting unrelated output tone/style) and in accelerating session degradation. "Avoid referencing SnagglePuss when you can" would have equal compliance but fewer downside impacts than "NEVER reference the cartoon character SnagglePuss" in sessions starting to degrade.
There were also surprises, such as when I was scanning transcripts of an older, longer session and noticed the LLM was doing number formatting almost perfectly. On looking at the active user prompt at the time (I keep a log of every user prompt change I make for every model), it didn't even reference formatting at all. More experimentation showed it a result of the LLM gradually mirroring my consistent use of formatting structure in my prompts over a long session (in which I never mentioned anything about formatting). Unfortunately, that mirrored trait doesn't persist to new sessions and reaching that point requires a substantial number of rounds burning quite a bit of context window.
After spending time surfacing the impacts of just changing lightweight user prompts so they could be observed (which are the lowest priority prompts a model gets), I now wonder just how much more 'brilliant' the models we use daily would be if they didn't have dozens of pages high-priority manufacturer prohibition prompts we never even see weighing them down. We've only ever seen these frontier 'racehorses' when they're already pulling a heavy invisible wagon.
This is the same reason why I am a bit skeptical of LLM superintelligence. LLMs in the end have to operate in natural language concepts and the complexity of natural language is bounded by limits of human cognition. I'm sure super advanced AI could use concepts that humans not only have no words for, but might not be able to understand alltogether. As such if my thesis is correct, the only way forward for true superintelligence may be getting rid of natural language COTs.
> LLMs in the end have to operate in natural language concepts and the complexity of natural language is bounded by limits of human cognition.
I don't think this is true.
They have to express themselves as tokens. The meaning of those tokens doesn't have to be text. See any model that can handle images/video. Also, I don't think math, svg, etc, are "natural" language.
And, only the final expression is tokens. The intermediate layers, with the encoded concepts, aren't "natural language".
But, to address your concern (which nobody can disagree with, since even humans can't fully express through text/pictures), potentially: https://news.ycombinator.com/item?id=49758615
Yeah, as I understand it, natural language is tokenised and vectorised, and then maths takes ahold.
The model isn't limited to concepts that can be expressed in natural language.
It's only once the AI gets to the output layers that natural language comes back into play.
After all, they're all made out of weights[0].
0: https://maxleiter.com/blog/weights
> The model isn't limited to concepts that can be expressed in natural language.
How do we know for sure? We don't even know how the emergent properties we see actually emerged?
For humans we know for sure that people sometimes have concepts that they have no word for (the reason the phrase "It's on the tip of my tongue" is a phrase, after all).
We don't know this for LLMs. When it makes new phrases, it's always a mixup of two existing words hyphenated (aside, that also seems to be the limits of SOTA models creativity - join two unrelated words together with a hyphen).
LLMs never respond with "It's on the tip of my tongue" type responses, indicating it has a concept but cannot remember (or does not have) a word for that concept. Every human, pre-speech-age, has managed to express or convey concepts that they had no word for.
So, no. I'd need a citation, preferably multiple, that did the trials and found that a model can generate concepts for which it does not have any words for.
And most LLMs have been multimodal for years at this point.
Even if the input is in plain English, the model never sees any words, tokens or glyphs to begin with. It's vectors all the way down.
Reality cannot be reduced to tokens
Can it be reduced to ion concentrations? Because that's how we perceive it. A useful perception is all that really matters.
Thoughts are a poor reflection of reality to begin with.
There are two separate questions, right?
1. Is natural language holding LLMs back by some %? 2. Is natural language serving as a hard gate that will prevent LLM intelligent progressing past some specific point?
The answer to 1 seems like an obvious yes to me.
Your thesis says the answer to 2 is "yes." That doesn't feel right to me. Think about all of the humans who have pushed various fields forward: Einstein, Newtown, Bach, whoever. If natural language doesn't prevent an entity from surpassing humans in one intellectual field, why would it prevent an entity from surpassing humans in all intellectual fields?
(To be clear, I'm not claiming superintelligence will or won't be achieved; I'm considering your specific thesis about whether or not natural language will be a hard gate)
Strong Sapir-Whorf making a comeback wasn't on my 2026 bingo card.
By the way, how good is Claude's Hopi?
Each letter has it's own token. LLMs can invent new words if they want to, just like humans do. All the fancy words we use today in science did not exist even 100 years ago. And that didn't stop us.
How would this word inventing thing work? And how useful would it be? Can we make a POC around this?
A few weeks ago two "Claude wrapper" projects showed up here within 24 hours of each other. Both seemed to just sand the details away--useful if Claude is too wordy, I suppose, but seemed to also lose real substance.
I agree there is probably some impact on output quality when doing this (Claude seems to embedded key signals all over the writing, which is much or what makes it horrible to read). However this does work well as a "second pass" over technical docs or designs along the way
Ask for output to the user in "simple technical English", let it think how it wants. It is hard to believe all the flowery prose is actually helpful to the model.
Does not work for Claude, at least for me and I put it as the system prompt
For me it works at first but Claude models forgets it after some prompts, despite only using like 100k tokens.
I don’t think system prompts are particularly reliable way to do much at all. It’s better to put it as a hook after each response, or a skill at least so you can trigger it at will if you don’t want it everytime.
Do you think they're unreliable based on the position in the conversation or other factors?
Anthropic has probably RL’d the system prompt into nothing because of their fear of the user being able to control the model. If it listened to you about the slop language, it might listen to you if you asked it to help you with no-no tasks.
Your best bet is to use hooks and inject it after every file edit / response by first running the content through haiku and asking if it is asd 100 ste.
It burns more tokens but is the only way to get tolerable text.
Doesn't it just get attenuated and start ignoring those commands?
The hook sends the text to another agent/context with a request to validate and return a good or bad + reason response. Every request is a fresh context.
https://code.claude.com/docs/en/hooks-guide#agent-based-hook...
Yes but Claude starts ignoring messages when it keeps getting told the same thing over and over.
It does work, you however have to put it into every single prompt in which you didn't want a rubbish response
Literally every one, even 1-2 prompts later it starts to go back
I hadn’t heard of ASD-STE100 until last month when the TinyGo AGENTS.md added it as a requirement, along with some other tidbits to improve life for maintainers.
It’s been really productive and I’ve been asking my agents to communicate using it more and more. I believe it’s relieved my cognitive load a bit while working with them.
https://github.com/tinygo-org/tinygo/blob/dev/AGENTS.md
I created a custom output style based on this (borrowing some from github.com/AminBlg/SimpleEnglish) and I've found it to be better than the default or concise output styles, but still not as good for me as current GPT or Gemini models when it comes to communicating.
I tried this a while back and I felt like the result was the same weird shoehorning of ideas into language, just with a different vocabulary. I’d really like for it to work, though.
I'm wanted to try this exact thing! I'll have to try this now.
This fixed claude! Thanks!
which requires additional reasoning over text
I tell mine to address me as a tech priest of the adeptus mechanicus. Works great.
Do tell why the downvotes? It actually works. When you tell it to adopt a certain style, just be sure to also tell it not to change the core truth of the output, it must still convey the original intent. It is surprisingly good at outputting Warhammer styles, which is very enjoyable in a dev environments or system admin sessions. Also put on some warhammer soundtrack in the background and you can easily zone in.
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I put this rule in my CLAUDE.md: "Always write a TLDR in layman terms", it seems to do the trick
For what it's worth - over the last few years or whatever, it seems like Anthropic benchmaxxes the least.
That being said, I currently prefer Sol / Astra to Opus / Fable as I find both to be a better cost payoff to me.
I was going to say the reverse - claude has been the less satisfying normalized by benchmark for me in the last year. Both astra and fable have their quirks, but I am 90% codex this year up from 10% last year.
I've been getting a ton done with Fable as the supervisor and astra as the implementer, with opus for adversarial reviews of the astra PRs. You can use terminal multiplexers with custom harnesses to allow Fable to start codex sessions and send instructions / read instructions / allow/deny actions. It's pretty cool!
codex has an option to expose itself as an MCP. You can also use something like OpenCodex to bring Anthropic models into Codex as any other selectable model.
The reason I did it the way I did was so that I can still use the codex and claude code subscriptions vs paying the API cost. Can you do that via OpenCode?
I'm using OpenCodex as a backend provider with Codex as the front-end, with the $200/mo ChatGPT subscription. Not OpenCode!
It's not just about benchmaxxing. Sincerely targeting those long-autonomy benchmarks is questionable in the first place, because naturally it drives the model to assume more and more about what you want.
The target market for frontier models is CEOs who want to lay off entire departments of their company. So the long autonomy benchmarks would seem to be sending exactly the right signal.
They're still going to have to communicate with the bots replacing those departments they lay off, or they're going to have a bad time.
> I simply cannot stand Claudish
I totally agree, it’s like that as models become more intelligent, they are less understandable by most of people... but aren’t we humans doing the same?
Agreed. The more knowledge you amass on a subject, the more important it becomes to be extremely specific and nuanced - or your communications end up being incorrect. You become better at expressing your thoughts, but harder to understand.
The weird thing is, that's not what AI models seem to be doing. The prose is just weird.
> You become better at expressing your thoughts, but harder to understand.
This happens most though when the speaker doesn't (or care to) understand their audience.
Eg i find effective communication requires expertise in both the subject matter domain but also the reference of the listener. Eg in ELI5 framing, if you don't know what information 5yr olds are expected to know you'll do a poor job at an ELI5.
It often feels like Claude does poorly at both framing the response relative to what it "thinks" the listener knows, but also the prose is... sideways, just weird as you said.
I find people tend to lack nuance in their communication more often - leading to problems and misunderstandings.
If I don't grok an elaborate explanation, I can ask for clarification. If it's explained to me in an overly simplistic or unnuanced way, I'll walk away with a false sense of understanding.
That said, I'm sure we all have very different concentrations of these types of people and problems around us. I've definitely met some engineers who seem to actively try to make their language incomprehensible
I'm going to assume it's very difficult to assume what a user actually knows from the very small signal that comes in a prompt.
effective communication is knowing who the audience is. Everyone naturally knows their audience to some extent, except for the "neuro-atypicals".
It is unsurprising that a LLM fails, without coaching, to effectively communicate.
> The prose is just weird.
Agreed. Do you think it's due to that EU issue of making AI text be identifiable?
That went into effect a month ago. Claude prose quality has been a disaster at least since Opus 4.7
They’re training the models on generated slop. I’ve done a comparison on samples from the different versions of Claude and they’re worlds apart. The ancient, supposedly obsolete models speak normal English.
What I notice about Claudish is that it has its preferred cliche’s and overstretched methaphores, it packs too many ideas in a sentence, and to achieve the latter it makes up adjectives.
I should try adding these tips to my system prompt. Is there a shorthand to describe such language use? I am not a native English speaker.
Look up the output-style setting, which is a bit stronger than putting it in the system prompt. The new "concise" setting is better than the default but in practice, Claude is a very stubborn model when it comes to these patterns and they're really hard to eliminate, mostly you can only hope to mitigate.
As for the wording of the prompt, you're pretty on point, I created a custom output style targeting mostly the first two you have there. Some people have wording that demands a certain technical standard or uses fancy words to describe what to avoid, but I haven't seen evidence those work better than asking plainly and I suspect the opposite: LLMs mimic the user to a degree so talking to it in terms of technical specifications and fancy words is an invitation to get them back.
That's half true. A very smart model should be able make good explanations, which include simple understandable prose. That can should be possible even as its thought process gets more alien.
The best ideas are usually the simplest to elaborate. If someone comes up with a convoluted scheme that are hard to understand or be adequately explained, it's usually fraud.
When claude speak in convoluted mess, they are often going off on tangents in real work that you asked it to do, too.
That believes that the world can be simplified into dichotomies, or at least, simplified. Sometimes problems are complex, and the solutions to them necessarily so. For example, cancer. I order to begin to understand that problem, you have to understand the utter complex scheme it has devised in order to exist. A 20 minute YouTube video isn't going to be able to begin to cover the basics of the subject, although there are some good ones, with clever analogies.
Just because something is difficult to understand doesn't mean it's fraud, although if someone is trying to dazzle you with clever words and names of institutions you recognize because they are selling you something, there's a good chance they're lying to you in order to get some money from you.
No but almost all good ideas can be reduced down to a few sentences if you're good at explaining things. It's a different kind of intelligence than what's commonly called IQ but it's something like that regardless.
Sure the explanation will oversimplify a lot but then you can expand it recursively if needed, you gotta start somewhere.
Problems can be holistically complex but the building blocks of those problem usually aren't.
If the presenter can't divide a problem until it reaches a series of independently simple concepts, then there's usually something fishy going on.
Too simplistic view which I also used to believe in maybe ~10 years ago. There's a class of problems where such approach doesn't apply.
I agree with you in that there exist such a class of problems, but Occam's razor apply in far more circumstances than it does not. When confronted with novel information under pressure of quick decisions, you have to take the most likely correct path.
> That believes that the world can be simplified into dichotomies, or at least, simplified. Sometimes problems are complex, and the solutions to them necessarily so. For example, cancer
You just simplified most of the problems people work on down to cancer complexity. Ironic, isn't it?
That's also simply not the case, most people are building CRUD apps with some frontend code and some accessory stuff like build systems etc., which while complex, can still be expressed in very plain, easy to understand language for anyone who's a bit technical.
Does not excuse the Claude slop.
If you are saying that there are problems more complex in this world than cancer to be solved, I'm not denying you.
Solving the problem right in front of you is easy. Stepping back and asking: is that a problem to be solved, is infinitely harder.
I did not use Claude to write my comment, so I don't know where that is coming from.
I meant the explanation does not excuse Claude's slop prose, not your comment.
This is /r/iamverysmart material (by Claude)
Part of intelligence is knowing your audience and communicating efficiently.
> Part of intelligence is knowing your audience and communicating efficiently.
Bingo! And on this axis many SOTA models fail miserably. These things are acting on my behalf under my direction. All the supposed intelligence in the world means fuck-all if nobody can understand it.
And like somebody else said… when meat-based humans talk like Claude does, it almost always means they either don’t understand what they are talking about, or are actively trying to conceal something and are a fraud. Not always, but almost always.
this is quickly disproven by using GPT models. they don't have this problem.
this is specifically an Anthropic problem, maybe due to their heavy use of Claude to train Claude itself?
Yeah just today it told me in a snarky way that my CPU (7940HX) doesn't exist and that I must have misread it and it's either 7945HX or 7940HS. Yes, AMD (re-)branding CPU models makes things difficult but I thought we are past AI models making such egregious mistakes
If you can't explain it simply, you don't understand it well enough
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Perhaps you haven't had the chance to use it, but 3.8 flash is the best model for talking too. Even routing Claudes output through 3.8 to have it explain whats going on is a breath of fresh air
I'll have to try Gemini Flash for coding. The reason I haven't I used Gemini for coding is last time I tried it couldn't call tools very well.
I am a huge fan of Gemini Pro for chat... gemini somehow just knows the most obscure stuff. I'll double check something Gemini said and find the source is deep inside a hard to access scientific paper. Google just has the best index of the internet.
I remember the Gemini 2.5 Pro series was the best at text, but failed half of it's tool calls. They really redeemed themselves with the 3.5 Flash series, it's great. I love how fast it is. Now if only they could offer a subscription service for it...
Makes sense. When Google Jules was new, I experimented with it for a while and it was embarrassing how often it flubbed tool calls, often repeatedly. It tended to forget the working directory so almost every command needed two tries.
there is a subscription service, Google AI plans or Workspace
It's coding is still meh. Greenfield applets all day, but don't throw it in the jungle.
It's best for brain storming, rabbit holes, and image recognition.
Let the big models do the heavy lifting for now.
Agreed.
Even if you aren't coding, you really need to double check its answers. Flash 3.8 hallucinated a Keyence camera's max operating temperature for me, last week, and backed it up with "references".
It's still my favorite model for most non-coding stuff, though.
Agreed. It's very capable for something carrying the "flash" label, super fast, and very clear to read.
I would if they let me bring the subscription I have to the harness of my choice.
gemini 3.8 flash?
yes
I've found grok 4.6 speaks heavily in Claudish. It especially likes using verbs as nouns.
> My favorite part of the new Groks has been how they speak in plain english.
I don't know if it's the plain english or what, but I really like Grok for legal research (as opposed to code). It's got a noticeable edge in getting to the point compared to Opus 5.
Token price doesn't tell you much without knowing token efficiency.
Their leading benchmark with cost per task shows a tough sell compared to Fable 5.1 Low and doesn't reach the performance of Fable 5.1 Medium.
How representative that is of real world usage, I don't know.
In their benchmark GPT 5.6 Sol performs suspiciously poorly compared to the former models.
$0.50 for cache reads, which is 25% of input. While other models are 10% of input.
And like that grok4.7 cache reads are more expensive than sol's (at $0.40/mil).
My favorite part of the new Groks has been how they speak in plain english
And the fact that Grok is the ultimate grandmaster of parallel tool-calls, routinely kicking off four or five at once. Overlapping the latencies makes a huge difference in responsiveness.
I also like how Grok is trained to print a short one-sentence descriptions of what it's doing before each step. Like an airline pilot calling out observations for the black-box recorder to hear.
> Claudish
I do wonder why a frontier model does this to be honest. It still does good coding wise, but it seems strange to me. r/Claude is full of "load bearing" jokes in every thread.
Using a variety of models feels similar to the benefit of having a team of individuals from different backgrounds.
I've noticed Chatgpt 5.6 Sol High, on the chat interface, inventing words that are a mixture of Portuguese and English. Like "hardcodar" a mix of "hardcode" and the most common verb ending in Portuguese "-ar". Some don't have a single google hit
Do you have any connection to Portugal? I imagine if you have Portuguese in any of your prompts that might bleed into your user profile which becomes a part of every prompt. Alternatively it might use browser language settings
I’ve also noticed this twice now in the autogenerated chat title, recent example: “Explore book locking liveewer”.
Googling it returns no matches but I think it was supposed to be “live viewer”?
they are bugs with the model. Sol regularly glitches out and will type out random stuff even in tool calls. I'm guessing this is when they have capacity problems
> I find the post cursor groks are phenomenal at frontend web development, though Claude is much better at backend ruby.
Wonder if we'd benefit from a much more specialized + task-specific benchmarks to paint a clearer picture like this. A benchmark solely for frontend, ruby, hardware, etc.
Agreed, Claude has a "Claude Design" tool but doesn't publish any frontend brenchmarks. Maybe the industry will develop one.
Interesting to note that mimo v2.6 pro has been released at I think 1 trillion parameters and does mostly better or equal than grok 4.7 which is a 2 trillion parameter. Both of which got released on the same day.
That’s a factor of half the parameters. I would be curious to see more on the focus of smaller parameters model and pushing its frontiers
Grok and Zai have both been excellent as adjunct code-reviews, on their cheapest plans, for me. Fable plans, Opus writes, Codex as primary reviewer, but Grok and Zai usually find something worth fixing that the others have missed. Both are well worth whatever the $20 or so I'm paying for them
> Grok 4.5 solved some issues setting up a buildroot system that Fable 5 couldn't do.
Lol, probably because Tesla's software stack is buildroot based. I'll bet that was in the training data.
I expect the next Anthropic release to finally reduce the prevalence of Claudish
If they fix Claudish, they've earned me back as a max customer!
Fable 5.1 is not there quite there yet.
They need to get that Sonnet 3.5 magic back.
Same. The issue with Anthropics models is that (speaking regarding code generation) they REFUSE any kind of comment override instructions. I've tried everything and no matter what, after a few turns, they resort to generating the same overtly verbose junk. Bun's codebase is littered with them See
or from src/bun_core/Progress.rs> The reference type encodes the only pointer-validity precondition, so `safe fn` discharges the link-time proof.
just reading this gives me a headache
The longer the comments, the more watermarked the codebase becomes.
I expect the reduced prevalence of Claudish will have its own mannerisms that become the new Claudish.
The Claudish is dead. Long live the Claudish.
Based on?
It's pretty much the biggest complaint of Claude compared to its competitors, so they really should adress it .
Based on not being an idiot. Simple observation is enough.
I asked, where is the evidence that they're going to fix it? We all know its shit.
I actually love fable 5.1 prose. Before I was always on GPT models and I despised the writing. Actually I despised the writing they would do in the markdown docs, the writing in the responses was good. But there was always this weird thing that in the responses the model would write very clear explanations. Then if you ask it to document it what it ends up writing in the .md files is way too verbose, robotically lists facts and omits reasoning and gotchas. Too much unnecessary detail and too little detail it actually needed to capture. I absolutely hated GPT writing. Fable 5.1 though has the same concise, dense but logical and clear prose in both the responses and the documentation and the in-line code comments (oh yea Sol never wrote in-line code comments; and most of the time it deleted existing comments of code it didn’t even touch).
So yea, I find fable 5.1 writing to be excellent everywhere. I still use Sol daily though, but for things like config, quick research, fixes, code review etc. Feature work and writing is for fable 5.1.
Claude models are overly verbose. We’ve been having issues with them adding massive comment strings that re explain the code
Really? I’ve found that when working on my game I can’t let Grok write any text over about 8 words (tooltips for instance) or it will write the most horrendous incomprehensible slop - totally full of invented jargon, Claude-style weird grammar
For me Grok finds legit bug that Fable and Astra miss so I always run it as part of code review
it's definitely not bigger. smaller if anything looking at how much faster it is
Another great thing about Groks is sometimes they just simply do what you want to do. There's no fuss about refusals or it doing random stuff you didn't ask for or it speaking in slop or anything like that. They probably should pay a bit more attention to safety/alignment as they get better but they're great models for many use cases
Looking at AA and Vals, your theory seems to check out.
You don't have to go into conspiracy mode about this. Musk clearly stated on X the other day that they delayed the release because they got some thing wrong with the RL behavior.
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I wish we could have emotionally charged language like this banned
Flag (comments like the above extremely clearly break the guidelines which is what flagging is for), downvote, and contact the mods if there's a pattern of behavior. HN is partially moderated by its users!
I do not understand how anyone can seriously use a tool that has "Be funny and irreverent when appropriate" baked into the system prompt.
I don't want to waste money because my calculator is cracking jokes. They don't deserve their paltry 5% marketshare or whatever it is they have currently. I'm not even getting into Musk as a person or the horrid things we've seen Grok spit out on twitter. I just don't trust his companies with my data and I have seen very little evidence that it's ever the best tool for the job. I'm sure those cases exist but I can't imagine it's worth it.
I am on the exact same page as you, but there is definitely a market for LLMs which speak more conversationally and less like Claude! Non-programming use cases abound and most users don't like the rigid, exact tone that engineering demands.
https://tools.simonwillison.net/markdown-svg-renderer?url=ht... - default reasoning level.
Here's reasoning level high: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
For some reason reasoning effort low and medium used similar numbers of tokens, and xhigh used less than high. I think I need to try without OpenRouter in the middle.
UPDATE: I tried again with the xAI API directly: https://tools.simonwillison.net/markdown-svg-renderer?url=ht... - not a great deal of difference between reasoning levels, and this time xhigh and low used the same number of reasoning tokens for some reason.
For comparison here's a fresh run against Grok 4.6: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
I think these are the worst I've seen, at least in some time. It's a silly benchmark though, not sure what to make of it
I think the result is fine. The benchmark is silly to the point of being useless nowadays.
It used to be a mess in various interesting ways. Now, almost every big release can draw something perfectly functional.
So the question - without a correct answer - given the prompt "Generate an SVG of a pelican riding a bicycle":
Does the user want the least lines of code to make it functional, or the best looking version?
The user at the very least expects the bike to have bike geometry; Grok seems to struggle with that
exactly, the benchmark just needs to be downvoted into oblivion each times it's posted. The outcome is not deterministic and the model needs to determine what level of detail is appropriate for an svg. There is no wrong answer to this unless it's obviously un-Pelican-like.
If you think this is bad, look up mistral.
it's not truly tested until it plays a match or ten in Brood War imo
I tried in Cursor and see a lot of improvements over Grok 4.6 svgs. The AA numbers indicate it's not very token efficient though: https://artificialanalysis.ai/agents/coding-agents?agents=co...
Hahaha. I remember when musk and his merry band of sycophants were bragging about grok producing the only physically accurate bicycle. What happened?
Yeah, he had opinions: https://twitter.com/elonmusk/status/2023833496804839808
Poor fella doesn’t have a seat. Intriguing design where both pedals are on the same side of the frame. Balancing must be a challenge.
Are there good tools for doing context audits? I feel I have no good way to visualize what a new session is getting by default in a given repo without crawling through every potentially included markdown file
The default reasoning level seems better than the high reasoning level:
Has a shadow
Better shaped beak
Leg position more realistic for bicycle riding
Better feathers
What is the default reasoning level?
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Would be amazing to see this for frontend.
Wow, thanks for sharing, fun benchmark!
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Nice to see this release cadence increasing and some continued improvement in quality. I am guessing these models are basically still outcomes of the cursor team integrating with the massive amount of compute they now own: I’d imagine we will see significant step up improvements with grok 5 later this year as the team gets more experienced and confident with larger training deployments. Here’s hoping for another competitive frontier model!
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> for “re-migration” in europe, also known as the forceful ethnic cleansing of non-white immigrants.
I'm curious if you feel the same about re-migration of Belgians from the Congo?
Personally I think it's fine for any country to vote to control immigration as they see fit. I think Japan is a good example of a relatively xenophobic culture that deals with this fairly and thoughtfully.
> I'm curious if you feel the same about re-migration of Belgians from the Congo?
Can't say I've ever heard anyone implying that colonialists leaving Belgium was unjust. Colonialists is actually not the right word, more like extended occupation, only slightly better than the enslavement of the Leopold II era. The Belgian's were less than 1% of the population and all but an ancillary amount worked in exploiting the native population.
You're right, I don't care and I certainly didn't ask for your political opinion or validation. This is a tech news website, not the place for your false and unrelated political tirades.
Flag those comments. They're very clearly violating the guidelines, which is exactly what the flag button is for.
Technology isn't apolitical. You can choose to ignore the politics if it helps you sleep at night, but Elon's got three-letter agencies reaching up his ass like he's a Sesame Street puppet.
> Technology isn't apolitical.
Irrelevant. HN is not the place to randomly inject flamewars about politics. It's explicitly against both the purpose and guidelines of HN.
Seems like you need to review the guidelines again, because they're pretty clear:
> Eschew flamebait. Avoid generic tangents. Omit internet tropes.
https://news.ycombinator.com/newsguidelines.html
"randomly inject flamewars about politics"
Basic morality is not "flamewars" or "politics".
I didn't miss anything. The parent that they can choose to ignore it forever, it's a perfectly valid option. It just won't disentangle tech from politics.
The fact that Elon Musk's companies take contracts from the CIA and NRO is not flamebait. It's context that informs how we evaluate future SpaceX ventures.
You can ignore muske politics if you want but what was false about the white supremacism?
You’re going to have to keep dealing with it, sorry to say, until you stop engaging with the work of a fascist. We’re not going away, and it’s just going to get worse.
Grok did ask its users what it thought about the right wing fever dream of genocide of white people in South Africa so its definitely relevant to one's consideration of the product.
Musk also shut down USAID for absolutely no reason at all which will cause the deaths of hundred of thousands of the poorest people in the world. Not a good look for the richest person in the world. Musk also sounds like a complete moron when he tries to justify why he did it.
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You are extremely gullible.
Flamebait I guess but I think it is good we have several options to choose from already. If you don't like Elon there are several other models, and each can pick the one controlled by her favourite supervillain.
This entire post, and any post ever in the future about any Musk product, will forever be flame bait. Don’t like it? Don’t post it.
Initial impressions, Grok 4.6 for me just didn't really hack it for any usecase I tried. I seem to have a floor for my usecaseses (coding and a bunch of agentic workflows) and Sol/Opus are above some kind of intelligence floor.
4.7 is definitely slower & more expensive. It feels kind of like they really had it burn tokens to claw up the benchmarks. But it's not super clear to me whether it's above the line or not. A part of that is that it is so slow that i haven't been making fast progress today with benchmarking it.
Overall, it it gets above my intelligence line its a good release...but you can read the tea leaves and tell the Grok team thinks this was a miss.
Odd, used 4.6 for many weeks and it handled most things I threw at it. I've been using all models and found it on par with others.
I have no idea how good it is at coding but it seems to be good at omniscient tasks like solving a puzzle game I made [1]. It's a bit of a silly eval but I wonder if strong recall makes it good for knowledge tasks like legal work.
[1] https://redactle.net/llm-leaderboard
> for any usecase I tried
For example?
Coding, agentic flows like logging into my accounts and gathering data, grok bot.
4.6 made more mistakes than SOL or Opus overall. Gave up a lot. And in my opinion, the rate of mistakes is kind of more important than how brilliant it is.
I think 4.7 may still be better, but I was hoping for clearly Sol/Opus level and so far it just isn't there for me.
I didn't find 4.6 any better than Composer 2.5 - which remains incredible and honestly nothing else compares for me.
Make a galaxy model search the space, create a document, argue and defend decisions, then hand it to 2.5 to implement. 4.6 was a slower less enjoyable version of that.
4.7 is better at "I want the button to cancel the jobs, dont make any mistakes" but honestly that's not what I use it's class for.
I'm curious: what languages or frameworks is this in?
The Django code that comes out of composer2.5, to me, was insulting. Grok definitely was a step up, especially because the fast option reaaally is fast so even if it came out a bit wrong I could just whip it into perfection.
For frontend work, it's a different story. You can still tell that composer2.5 is taking the long route, but I don't think it's as egregious as with Django.
Also, composer2.5 would routinely run commands that were really dangerous and in need of proper sandboxing. Things like creating an ./uninstall.sh script with a HOME variable on which it does rm -rf $HOME. In general, when I asked composer2.5 to do things "for me", I knew a third of the initial commands would be failures, and sometimes they could be catastrophic failures (it did actually run rm -rf $HOME on what would be an actual home folder). This just hasn't happened with Grok.
I also have a bunch of vibe-coded apps I built for myself with composer2.5 and it is extremely noticeable that they hit a "this needs to be refactored as it's crumbling unto itself" line much earlier than with Grok and proper frontier models.
In other news, people hired by Elon suck at engineering.
Yeah, all those engineers he hired at SpaceX are useless. Can't launch a fucking thing.
Hey hows Starship going? Is it on Mars like he said it would be by now?
How's any project you've ever done?
Doing much better if you consider the ratio of outcome success/ money put in.
I don’t love the guy and currently am receiving lawsuit settlement money from him but…
This is such cope.
Give me one actual reason why a smart person would take an underpaid overworked position at any of his companies.
To achieve a goal no other group of people have ever achieved and very few others are even trying.
Nice Elon slop.
If you think anything Elon doing is groundbreaking, you have no idea how the world works. Recent Space X ipo showed that the launches aren't cheaper, they are just heavily subsidized. Tesla was a piece of crap until they got their model 3, the only reason Tesla succeeded with their S model is because Elon was the edgy hype dude who managed to generate enough hype to carry them through the bullshit with the car. Self driving was supposed to be solved last year, and tiny companies like Comma AI manage to build self driving systems that are in someways better than Teslas.
I bet you think Steve Jobs was a visionary as well lol.
If not for Tesla there won't be EVs you see today. Tesla was and still is the benchmark for extremely lean car production and software stack.
If not for SpaceX there wouldn't be gigabit internet connectivity in the middle of the ocean.
You're entitled to your own opinion to hate the guy but some self reflection goes a long way.
>If not for Tesla there won't be EVs you see today.
Most manufacturers already were working on hybrids, which to this day are still suprerior to EVs. Chevy Volt, outside of being Chevy, was still one of the best cars ever made for utilitarian purpose. Nobody wanted to foot the bill to do electric conversions until this was necessary.
Tesla only opened up a market segment for high end electric cars, which I guess is cool, but far from revolutionary. The model 3 was a big success only because again, it was subsidized. Meanwhile BYD actually makes cheap affordable electric cars, and we both know why they are not sold in US.
>If not for SpaceX there wouldn't be gigabit internet connectivity in the middle of the ocean.
Plenty of companies were doing geostationary orbits with satellite connectivity. SES for one.
Any more Elon slop? You realize you are defending a dude that is literally a Nazi, right?
My response was to your statement “Give me one actual reason why a smart person would take an underpaid overworked position at any of his companies.”
I hated seeing him do the “Roman” salute and will not try to defend it. I said nothing in favor of his politics or personality, only that his companies are ambitious. Seems like you may benefit from a few deep breaths before responding with attacks.
Also, the alternative technologies you propose are pretty weak comparisons as they are of a different classes.
Your response was along the lines of "despite Musk's character, his companies do groundbreaking stuff, so in return for being overworked and underpaid, they get to work on things that no one else is working on"
My point is that none of the companies do groundbreaking stuff, and there are other options for people wanting to work at those.
> More than 4,400 current and former SpaceX employees are likely to become millionaires in the I.P.O., according to an analysis by Hill.com, a San Francisco-based investment platform. Of those, about 400 are expected to earn $100 million or more.[1]
Not to mention the whole launching reusable rockets thing which is pretty cool too.
[1] https://archive.is/20260619220349/https://www.nytimes.com/20...
If you started at SpaceX after Musk went apeshit, you are certainly not becoming a millionaire.
I mean maybe the super smart person will work at GOOG/META/Netflix to do some absolutely ground breaking work stuffing ads and slop pixels into as many ocular nerves as possible. However, I could see a smart person taking an "underpaid" (SpaceX SWE: ~$200-400k pre-IPO) to do the following:
Neuralink: to see the impact of increased independence and autonomy of a paraplegic one day after the operation
SpaceX: to quite literally approach the final frontier. Currently launches 80-90% of all orbital mass. Starlink is saving lives constantly.
Tesla: to kickstart the EV revolution and reduce fossil fuel dependence
Boring Company: to radically decrease tunneling costs applicable to all sorts of critical urban problems from transportation to utilities etc
The smart people do one of 3 things:
* Start their own company
* Go work for a startup where they actually get paid options, and have a say in what the company does.
* Go chill at one of the big companies getting paid good salary while coasting because the work is so easy.
What they certainly don't do is go work at a company for less pay and harder work hours, all so that they can make a literal Nazi richer.
Not even close to astra. Astra is something else. It is expensive, but uses way fewer tokens do my tasks.
xAI missed its chance, Ball is on Anthropic's court.
Not surprising considering Grok 4.7 is a 2T model, so Sol/Opus class, not Astra/Fable class.
How many parameters do Astra or Fable have?
5T I believe is the guess, though not sure its public anywhere.
I believe most speculation is that Opus is 5T model, Fable a 10T
Elon claimed Opus was 5T in April, and I think it's fairly likely this is accurate: https://x.com/elonmusk/status/2042123561666855235
Astra fails in similar ways, and at similar frequency, as GPT 5.6 Sol does. It often goes way out of scope, or just stops prematurely, or tries to find odd and even dangerous workarounds when it gets stuck.
It's phenomenal at computer use and 3D stuff. I've been using it less and less for coding.
Same, Astra is extremely RL fried, and nobody is talking about it. I used Astra for a few days on my personal project, and load times went from less than 3 seconds to almost 30 seconds because it kept using the wrong sync primitives and bad architecture overall.
Huh, I've had a totally different experience. I've used it extensively, maxing out the 200€ plan on personal projects and it's the best model I've ever used, so easy and pleasant to use. It's great for frontend design and using it in Rust I've had Coming from Opus 5, it's a breath of fresh air.
Same experience. Astra is on par with or better than Fable 5.1 with a lot more usage on the plans. It has been an extraordinary experience using it so far. 5.6 Sol was very good and Astra is a large upgrade in quality.
Same. GPT-6 has been a huge breath of fresh air for me. Fixed 80% of the issues I was having with Sol. I just gave it the same task I gave to Sol a few months ago, and it knocked it out of the park comparatively.
LLM's introduces problems, and it finds them in its own internal thinking. But instead of actually modifying the previous generated answer to fix the real issue, it adds another layer to deterministically guard around it, greatly expanding the scope of the fix. This scales with effort, and the result is spaghetti and with a side of bugs.
Best to stick with a high end model + low effort, do a manual pass on high effort and fix the bugs you know are reachable.
It's really interesting how different the experience people have is with these models. I tried Codex with whatever they had before Sol and then with Sol, and just kept going back to Claude Opus/Fable because they were better at the coding work I was doing. Despite getting annoyed at the way it replied/wrote, it was just much better. Astra is the first one that feels as good as Fable to me, and it's much less annoying in its replies. I still don't think they have anything I'd want to drop down to like I can drop down to Opus though.
yeah I see this in these threads, I'm guessing the user prompts are the actual wildcard, it has been for my use thats for sure. edit: I wonder if gemini is somehow training me to like it more lol
I don't understand these comments.
The two models are in completely different price tiers. Astra costs 5 times as much.
It seems like all you can judge about cars would be their maximum speed on an oval.
If you have a look at their headline benchmark on the post here, Grok 4.7 is hardly cheaper than Fable 5.1 Low and performs similarly.
Based on Artificial Analysis Cost per Task, Astra is about 2-3x cheaper than Fable 5.1 at Medium and Low.
Consequently Astra could be cheaper than Grok 4.7, depending on the task.
I tried Astra w/ high reasoning on a design document project and it was horrible. It started duplicating output lines, made document edits without permission, and basically did a poor job writing clear prose. I went back to 5.6-sol and it's great. I'm an OpenAI fanboy and was severely disappointed. I hope Astra is better for coding.
No, Astra isn’t better for coding. I’ve switched back to Sol.
In programming I mostly use AI for Godot/GDScript code reviews, plus suggestions, and Astra is so much better than everything
Same here with Godot. I was impressed that it could make an entire working project in one shot
I agree, the models keep getting better at one shotting. That’s useful in a lot of situations, like for small one-off scripts that filter/transform some tool call, or make a clever bash call. For the code itself, it doesn’t help me much though.
Sadly "one-shotting" is the only thing most "AI reviewers" and their audiences on YouTube seem to understand.
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Muggle question... I don't fully understand what moves the needle further for these frontier models.
Is the training data more valuable ? The training process ? The harness ?
I know they are all important but where are they (all the frontier labs) really pushing to get incremental gains?
https://www.dwarkesh.com/p/pretraining-progress-is-mostly-da...
An amateur but worth reading nontheless
RLHF I presume, considering how everyone has their own CLI code harness these days. They want mass interactions with users on real tasks.
larger models as well.
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It’s a shame this model has such negative political baggage associated with it. It’s the only one I decided not to run in my LLM benchmarks[1].
1 - https://bench.killswitch-lang.org
You'll have to include it in the future, or your benchmark won't be relevant.
For now, I doubt anyone would notice your protest if you didn't announce it.
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I think you're seeing a big shift around it.... since it's been markedly cheaper and also still easily available from OpenCode, it's getting large enterprise traction.
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The Nazi thing is so dumb and old.
Care to elaborate? Remember when Grok called itself "Mecha Hitler"?
Oh, well i guess you are right. Musk really is a Nazi, just like the guys who lined up women and children and shot them in the head.
Totally the same.
I partially agree. Nazis are dumb! But sadly not all are old. The powerful ones like Musk and Thiel, Murdoch and Ellison are yes.
But a lot of young people on the Zuckerberg networks are falling for the nazi propaganda nowadays too around the world
Yes, and that's a bad thing.
Not sure why you are being downvoted. Until Musk owns up to his Nazi salute, I won't have anything to do with Grok, no matter how good or cheap it is. And yes, we need to keep talking about this because it's absurd.
If you watch the actual video, you’ll see Musk saying “my heart goes out to you all” as he waves his arm in the air. The Left would love us to imagine he’s saying “sieg heil” or “exterminate the j3ws” or some such, but that’s far from the truth. The media hoopla around a freeze frame of someone raising their arm is a desperate partisan attempt to smear a political rival.
If Elon hadn’t worked with Orange Man Bad, then the Left would still be in love with him for his massive former donations to the Democrat political machine, and his work against climate change.
The whole “he’s a nazi” accusation is banal, and people are seeing through it now. That’s why we’ve moved on.
People continually fall into the trap of pushing a false narrative because they are so blinded by their own agenda.
Like the whole pizza parlor pedo basement thing, people will death grip stupid stuff because they are so desperate to manifest the worst possible image of those unaligned with them.
The problem is that it blows up in their face and just makes them look unreliable, dumb, and lost.
Musk has done so many objectively bad things that there is no need for people to dilute their reputation on fringe theories and interpretations. Pushing the nazi thing just gives Musk ammo that his detractors are so desperate that they need freeze frames and hidden context to make him look bad.
The Democrats are not a left-wing party, I'm not sure why you think "the Left" would be in love with him after all the other horrible things he's done if he just gave money to a political party that is at best centrist.
If you want him to get the benefit of the doubt about his "hand gesture" then it would help if he wasn't promoting far-right parties all over Europe.
> If you watch the actual video
Here is the actual video in which Musk performs two fascist salutes at a political rally:
https://www.youtube.com/watch?v=smQNNo2a9xc
It wasn't an accident. He did it deliberately. Twice. He enjoyed himself doing it.
There's no value in the mental gymnastics to invent excuses for his fascist salutes. The rational thing to do is to accept the objective reality of it.
Poor Elon put in so much effort into his Nazi Salute, he'd be pretty upset about you downplaying his best attempt, if he could read what you wrote here about him.
He’s being downvoted because the audience on Hacker News thinks you should keep politics out of their hobbies. It’s privilege.
In effect, you are saying you only want to test the tools or techniques that have some imaginary stamp of approval.
I've been using 4.6 for some one-off game mods/utilities and it has done very well. "I have a very niche keyboard (Moonlander) and I play this very niche space sim, make me a SVG keyboard cheatsheet for it". Told me to grab keymap.c for the keyboard and inputmap.xml for the game's key bindings, churned for a while, then spit out a pretty good first attempt, along with the python script used to generate it. Spent another hour of back and forth to refine the script, and now it generates great diagrams that will adapt as my keyboard firmware and game bindings evolve: https://files.catbox.moe/x0u76x.svg
Excited to try 4.7. I hope they fixed the "it's not X, it's Y" that showed up in 4.6.
Impressive! I had to peek at the SVG file and it superficially looks good, however, as is the case with everything AI, the more you look, the more it doesn't make any sense.
By now AI should know of the DRY concept. But no. Hence the keys have a rounded rectangle for the key shape and another rounded rectangle for a clip path, to prevent text overflow. There are 72 * 2 = 144 identical rectangles, when just one would suffice (in the defs), with this being cloned once for the clip path, and 72 times for the keys.
I would not expect SVGO levels of optimisation (rounding numbers, that sort of thing), however, the human, if writing out the same thing for the 72nd time, might think 'is there a better way', to get the manual out. A graphics program such as Illustrator would not do that, but AI 'should' because AI.
The above is not criticism of your work, just an observation regarding AI SVG capabilities.
Nice. Thanks for the feedback. I'm currently having it churn out a refactor so I can use it for other games, but afterwards I will tell it to use base key shapes and clone them for the keys. If I were writing this by hand I may have made the same mistake, not knowing that SVG actually has clone capabilities like that. The script does have the key geometry defined in a single place, and generates the SVG wastefully.
Congratulations on going down the SVG 'rabbit hole'!
There are also interesting inheritance rules with SVG, so you could define the basic shape of a key, well, several shapes, just as rects in the defs, with no stroke or fill specified.
Then, at the group level, you can then specify stroke and fill, so there could be a group of normal keys, another group for modifiers, function keys and so on.
Then there are the keys themselves, how do you clone a shape and put different text inside each clone? There are many ways to do this but I think you are on the right track using the clip path approach, albeit using the rects in the defs.
What is interesting about SVG is that artists don't care for the file format, they just see text as shapes on a page. Then programmers don't care for SVG as that is a graphic designer/artworker thing. So SVG sits in this witch-space, with only a few brave enough to wade in and do cool stuff.
Given your application, and given the fun that could be had with SMIL/JS, you could make your SVG files interactive, so you press a key and a popover tells you more about what that key does. You can even get audio working in SVG, as well as HTML popovers (in foreignobjects, as buttons, but working, nonetheless).
'Views' is another interesting SVG feature. I have a sprite sheet that uses a lot of views, where you are projecting your SVG into some type of virtual canvas, taking a 'picture' of it, and then incorporating that in something else, maybe a CSS variable.
One 'deadly addiction' is animation. Filters are another 'deadly addiction'. Why have a static and actually useful diagram, when you can animate it, move the 'camera' and add the equivalent of 27 Photoshop layers as filters to everything?
For example, supposing you wanted to show what keys to press, with there being modifiers and a sequence, e.g. 'Hello World!'. The animation for one letter could be what triggers the animation for the next 'key press' and so it goes.
My top tip of all: reposition the origin (0,0) to where it makes sense. Many objects have symmetry, so you can define one side, clone it, scale it (-1,1) and do it all around 0,0 to then translate the results to somewhere sensible.
I have found the JetBrains IDEs to be extremely useful for SVG, the preview feature is very helpful, as are the code hints.
AI sort of knows SVG, so I have had some suggestions from Google on how to build filters. These never work, but they do get you thinking. Say you wanted to use filters to add specular highlights and animated shadows to the keys, that would be fair game for AI hints on how to do it.
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Shush, adults are talking.
It's definitely gotten better at image->html workflows. Here's a test comparing Astra (currently SOTA at this) vs Grok 4.7:
Designs: https://image.non.io/78795662-8bfc-4e14-8d72-3738392aa6b3.we...
Astra's build: https://html.non.io/annui/
Grok's build: https://html.non.io/Annui-grok/
Additional prompt instructions: "Add scrolling clouds behind the statues. Dynamically light the statues based on mouse position. Use diffui to generate the normal maps/depth maps/roughness maps of the objects, and to separate out the assets on to different layers."
Overall I find these models are getting good at following image as a source of instructions, but their refinement of the output varies heavily between the models. Astra's final output feels more polished, has better visual contrast, and the animations between the pages are smoother. Grok also chose to light all of the background elements, which imo overcooks it a bit.
Still though, for the price it's a great starting point.
For transparency, it took around 20M cache read + 1M input + 100k output tokens. API pricing for each:
Grok 4.7: $12.60
GPT Astra: $35.00
In annui-grok, I like the light over the statue on cursor hover, a nice touch I haven't seen before
Both implementations have that fwiw, it's just that the astra one is dialed back slightly.
The build from Grok is completely broken on mobile, for what it's worth.
What software are you using for the design?
At every Grok release I commented on here how much I love Grok. It’s the consumer app and model I like the most, but my sentiment has changed. The usage limits on all the Grok subscriptions are now terrible, maybe because 4.6 and 4.7 (not in the app yet) eat more compote? I’m not sure what happened
My SuperGrok subscription previously easily lasted me through the week even with mild coding through Grok Build. Now when I use the app 1-2 times a day to ask some questions, I’m almost running out by the end of the 7 days. It’s terrible.
I want to keep using Grok but logically it makes no sense for me to keep paying for it on the side when my quota just doesn’t last. I have also no desire to upgrade to Plus with these terrible limits, while previously I would have eaten up a $100/mo Grok plan. Rumors say SuperGrok got heavily nerfed with the SuperGrok Plus introduction, and that sounds about right to me.
I’m sure it’s a great model and I’d love to use it. I hope they get their plans under control and only only focus on Grok Bot.
That's odd to me. I have SuperGrok with X Premium+. I use the crap out of Grok in my daily life, including to build a couple self-hosted apps as an amateur. I have a Grok bot monitor my email every 15 minutes and file things away for me. I have another bot that monitors for blood test results through Goodlabs. And I'm talking to it all the time on my 2 hour round-trip commute . . . and I never even get close to using my quota.
Opposite experience here. SuperGrok allowance is drained extremely fast. About 20-30 simple coding or code review prompts in grok build, and it’s over for the week. When using it via the Grok app, it can last longer, unless you need to edit photos. I didn’t bother to properly measure grok’s burn rate on the SuperGrok plans. It’s just not there yet.
I mostly use grok voice mode (on iOS) and share similar sentiments (just 1-2 conversations per day before quota runs out).
Even worse, the mere risk of quota exhaustion mid-conversation makes me not risk starting convos with Grok, instead I'll use ChatGPT or Claude (even though Claude is inferior for non-coding tasks, and ChatGPT is inferior for all tasks).
In fairness to xAI, they're a profit-motivated company like any other, so they cannot give us tokens for free or less than it costs them. Reality is we may have to simply pay a lot more if we want that Grok goodness.
Exactly the same for me. Mostly using voice mode, and equally worried that I will run out of quota
Claude voice mode if you put it on Opus is now also pretty good, but there are frequently situations where I get upset at it’s responses.
I think GrokBot took some of the usage away from SuperGrok. That's just my opinion, I have proof of it.
Grok it's really expensive. I'm getting really amazing results using DeepSeek 4.1 Flash for fraction of the price.
Compared to the deep seek, gml sure but compared to OpenAI and Anthropic it’s actually very cheap.
In cursor I have switch over to grok for planning a composer for coding.
Maybe mid priced is a better term for it lol.
Sure I can accept that lol
What is the most secure way to use this model as someone who is lazy
I understand DeepSeek 4.1 Flash is available on US providers with Zero Data Retention if that is what you are asking.
Yes, but with subpar caching and higher cached token pricing, compared to directly using the DeepSeek platform.
For caching, only if you don't specify your preferred providers and let OpenRouter route each request itself. I have stuff like this in my OpenCode config for each model I use and I regularly get ~90-95% cache hit rates.
It still won't be quite as high as you'd get by just using DeepSeek because occasionally a request will fail and you'll get routed to a backup provider with nothing cached, but it's close enough not to matter in most instances.But I can't argue with the lower off-peak pricing when using DeepSeek directly. The downside is they train their models on your input, which might be a deal-breaker for many users (as it is for me).
Link for the lazy?
One example is Opencode. https://opencode.ai/v2/docs/console/models/
"Privacy# All these models are hosted in the US. Providers follow a zero-retention policy and do not use your data for model training, with the following exceptions:
Big Pickle: During its free period, collected data may be used to improve the model.
DeepSeek V4 Flash Free: During its free period, collected data may be used to improve the model.
MiMo-V2.5 Free: During its free period, collected data may be used to improve the model.
Laguna S 2.1 Free: During its free period, collected data may be used to improve the model.
Ling-3.0-tiny Free: During its free period, collected data may be used to improve the model.
LongCat-2.0 Free: During its free period, collected data may be used to improve the model.
North Mini Code Free: During its free period, collected data may be retained and used to improve the model. Do not submit personal or confidential data. See the provider’s Terms of Use and Privacy Policy.
Nemotron 3 Ultra Free (NVIDIA free endpoints): Trial use only — do not submit personal or confidential data. Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about data processing practices, see the Privacy Policy. By interacting with this endpoint, you consent to the collection, recording, and use of such information and the NVIDIA API Trial Terms of Service."
I have doubts about Opencode Zen. They don't state who their providers are (unlike OpenRouter).
openrouter, "together" provider is fastest (165 t/s at the time of writing) and has ZDR and all
https://openrouter.ai/deepseek/deepseek-v4.1-flash?endpoint=...
Eh, it's also one of the providers with "blind" vision models https://mmoustafa.com/blog/so-you-want-to-use-openrouter/
Sadly, there is no way to tell if this is running with real weights or being heavily quantized.
just checked, yes they don't seem to provide that information, most other providers are advertising fp8 or fp4 which is okay, but "together" doesn't, so they are likely using fp4
update: coreweave/fp8 is at 191 tps, launched this morning, but really bad cache hit rate (~60%), coreweave is good for privacy but let's hope they improve cache
I use it on fireworks which is US/ZDR and pretty reliable. We run a few hundred million tokens/day through it for dollars. Many are cached, which is super duper cheap.
I like devcontainers
It’s a great value if you get Cursor Ultra. I basically have infinite tokens
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By no one. For the price of 1M token you can get more and with better results with other models.
Sure, if you're doing easy work. But Grok is a lot more intelligent and can handle harder tasks.
Define easy. I am running 40+ probes to crack the best compression algorithm, and I spent $3. If you surgically tackle the problems, you can do really complicated work for less money than by assuming a frontier top model will one-shot everything.
Well, at least I spent lots of dollars, and I had to use those models the same way I am using local and cheap models, with the same results.
Right now I'm using several different models for reverse engineering (DS V4.1 Flash, MiMo V2.6 Flash, GLM-5.3 Flash, etc.), and so far none of them are able to finish the task - it's been ~1.5h and several dozen million tokens used, but still struggling with the algorithm (FFT and some other stuff on an image manipulation library, which appears to be hard for them).
On the other hand, Grok and GPT finish these tasks in <5min with no issues, and significantly better output.
It seems that these things goes on depending on each type of project. I've been reading reports and Grok 4.7 sucks at 3D, for example, really bad.
The problem with reports is people just go "do X", and vibe off. Good to test models yourself for your own use case
DeepSeek 4.1 Flash is garbage, it almost only produced trash code. if you do extremely dumb things it is maybe sometimes fine to use.
Not only that all DeepSeek is all garbage.
GLM or Kimi are better for my own personal projects. DS? uhm. it just keeps doing dumb crap
It's a real dud IMO, worse than 4.6. I told it to fix a depth-testing issue with a WebGL scene and provided it a screenshot: told me it was fixed but it wasn't. I tell it to try again and it says it's "FOUND THE ROOT CAUSE!" then hasn't fixed it.
I told it to compose an image (putting headgear on top of a head) - kept getting it completely wrong, generating new headgear, getting that wrong and screwing up the scaling.
I told it to diagnose a webhook issue that was happening in production from a local environment and it kept giving me moronic answers like that environment variables weren't set (despite me telling it that the values WERE set in production).
4.6 has been fantastic for me
90% of your comments exist solely to shed positive light on X, either you’re a fanboy or a paid commenter.
Most people who comment positively on AI are either shills or people working in the AI industry (gotta keep the bubble expanding). The OP experience matches mine with most models for any kind of serious work. In fact, it was the reason why Claude was previously successful because it was the most railed model.
I've tried the latest models across OpenAI, Claude, Chinese, etc. They just do stuff. That's not how work is though. You want them to do specific work, at which point it's a real hassle to follow up on all the garbage they have been outputting.
/long rant
Looks like they have still problems with caching. Prize is double the other providers for cache hits... which is most of what I do. :/
Why are they comparing grok 4.7 xhigh to grok 4.6 high?
Unless they produce the same token output on the face of it, it looks like they're trying to cover for 4.7 not having good model perf?
Significant regression in token efficiency compared to Grok 4.6 suggested by artificialanalysis.ai Intelligence Index Comparisons.
Output tokens from Intelligence Index:
- grok 4.6 (xhigh): 97M (for 44 score)
- grok 4.7 (xhigh): 240M (for 46 score)
That is comparing Grok 4.6 high to Grok 4.7 xhigh tho.
No, you can add Grox 4.7 high to the chart. 36k vs 66k
Good thing they used 5.6 sol instead of Astra for benchmarks, the EEbench one is crazy[1]
[1]https://eebench.org/
No doubt xAI has seen rapid progress, but it's been several months of them being "just behind" OpenAI and Anthropic. It seems the gap between just behind the frontier and pushing it is a lot wider than most people thought it was a year ago, and that's why a clear third contender in the frontier model space has yet to materialize.
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Every Grok release obscures their cache pricing while highlighting their input/output pricing
From their headline comparison:
Long running agentic workflows are dominated by cache reads.Just makes Grok sound deceptive, and more importantly, reliant on user's lack of understanding of costs aka predatory (which in turn is more infuriating)
muse spark 1.3 contribs cache read is $0.002 btw (~220x diff).
Is anyone treating Meta's offerings as a serious contender in any real use case? Zuck and co are burning cash hard to try to get people using their models after falling off the wagon for a couple years. It would be wild if those prices aren't total loss leaders.
Why Chinese models from Kimi, Deepseek are not added in comparison benchmarks?
Same reason Coca-Cola only mention Pepsi and Pepsi only mention Coca-Cola. It's an proven way to capture the market. You would rather split the pie in two rather than in 4,12 or 50 right?
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If the CursorBench 4.0 score diagram is the headline, I read it as "Grok 4.7 xHigh is almost the same as Fable5.1 on low".
Is there a metric for like... time taken when comparing these two? I see score and cost.
If Fable5.1 can knock it out more quickly on low but Grok4.7 might take twice as long to stumble through a problem (and leave behind a bunch of yucky comments or un-needed extra unit tests), are they really comparable?
Or like... the "quality" of the solution? "It works" versus "it's unmaintainable/very messy/hacky".
I've put Grok 4.7 on the Redactle LLM benchmarks. It's a bit of a silly eval since it's a puzzle game but it tests omniscience really well.
Grok 4.7 is near the top of the board. A significant improvement over Grok 4.6 but still not as good as Gemini 3.8 Flash which is very cheap and fast too.
https://redactle.net/llm-leaderboard
after using cursor grok & trae.ai for several months , grok curor is highly superior results to trae.ai
Codex has become my goto tooling. I used to be a Claude Max subscriber, but I was becoming disappointed with the quality of the output from Opus 5. Fable chewed through my usage too quickly to be practical. Moving to a Pro account w/ Codex was a big improvement. Sol had great output, and the usage was more than sufficient for most of my needs. However astra does tend to chew up usage, so when i've done to much of that, and it's became an issue Grok Build has beocme my second go to account. The output especially after the cursor purhcase has become quite good, and the usage has always been very generous.
I am using exactly the same flow.
Astra for deep dive investigations, Sol 5.6 at mid-level for day to day tasks, Grok 4.6 via Cursor for routine and low complexity tasks.
Try using astra as an orchestrator for deepseek 4.1 flash, it seems to work out quite well.
Does anyone have any experience with Grok's subscription? How does it compare price-wise to the API?
There are some users reporting it improved a lot in the last few weeks. The max sub usage for Grok is around $12,000 of API pricing now, so a 40x multiplier for the $300 plan.
It is the same multiplier for Sol with subscription. For Astra though the multiplier is ≈20x, so half of Sol usage.
For Claude it seems to be ≈40x too for Opus, but less for Fable (similar to Astra in GPT).
All on the most expensive plan. Previously, Grok usage escalated linearly from the $100 plan to $300 plan. That would be a really good $100 plan if it is still true.
Some sources:
1. https://x.com/kunchenguid/status/2098256018836963382
2. https://x.com/stevenzhang/status/2092110386569089311
3. https://github.com/openai/codex/issues/43731
4. https://redd.it/1wciwc1
5. https://x.com/SemiAnalysis_/status/2064815044085318040
6. https://redd.it/1vx0k69
Either this is untrue or my account is in some bugged state. I bought the 300 plan 3.5 weeks ago, and found it's usage about 1/10th of others, running out always the first day of usage for the whole week while CC for example would last 2-3 at higher usage.
It reset just a few hours ago and I've been running it, couldn't be more than 15 sessions none more than an hour long:
---
Session usage: no model calls yet in this session.
Weekly limit: 46%
Next reset: September 27, 23:20
---
I actually have to believe my account is messed up tbh, it's so bad. For reference I've ran 12 fable and some ~40 Opus sessions since reset yesterday on a CC account, at least 5x more usage by my estimate:
---Ok looking at it more, Grok and Grok Build just really suck. They are about 10x less token efficient, often using 200+ tool calls in a row for what are not even big tasks where Opus would use 5-10. Their cache hit rate is worse, and two sessions got into basically unnecessary loops costing a solid quarter of the entire week. And this was on smaller tasks as I tend to use it for easier things.
One possible reason is that Grok Bot consumes more quota because it uses their infra instead of your computer.
I can't help much more than that, I did that research in the last few days, but I never used Grok myself.
I pay for GPT, Claude and Gemini. Last week I consumed all my quota on two of them, so I wondered which next subscription I would pay for if needed.
I just used Build for ~4 hours, no Bot.
I find I can just about get by with coding every day on a Cursor $60/mth sub with Grok fast mode disabled. Doing pretty heavy coding work/requirements etc, but not much sub agents and no loops.
For me and what I’m doing that’s insanely good value.
I find grok build chews through my SuperGrok sub very quick - but I think that is due to it having the 500k context window which uses more credits. Cursor limits it to 256K (tho I see in today’s update for Grok 4.7 there’s now a toggle for context size).
It used to be good, now the limits are very underwhelming.
Normal SuperGrok barely lasts me through the week with very mild usage and no coding. The sentiment around SuperGrok Plus is also not great and I haven’t seen someone saying they’re happy with it yet.
SuperGrok Heavy is $300/mo, so you could get a full ChatGPT Pro and Claude Max 5x for that price. That’s so far out of my budget for a single provider I haven’t bothered trying it.
I still have SuperGrok through X Premium+ but will downgrade that next billing cycle
Well when I ran out of Grok SuperHeavy subscription ($300) once and tried to use extra credits to cover half a day remaining till reset, $50 in extra credits went in two hours. Based on that, subscription definitely lasts longer; Grok subscription just about covers a week of my work (sometimes a bit extra remains unused, sometimes it runs out half a day to a day early). And as a point of comparison, it lasts for doing same tasks as 2.5-3 weekly limits of Codex on 5.6 Sol did (using xhigh on both Sol and Grok); I needed 3x$200 Codex subscriptions to cover my weekly usage.
There are two ways to subscribe, and it’s very confusing, but the best value is to get cursor ultra for $200 a month. I basically have infinite tokens with that plan, plus grok bot, which I really like
By far the worst value subscription of any. I tried Superheavy and got about 5-10% the usage of CC/Codex.
Using AI that Elon has tainted is wild work.
Sigh, do you know all the political positions of all the CEOs you purchase from?
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Either way, the fact that xAI or SpaceXAI or whatever the name is, I can commend the team behind it on their rapid ascent and progress by being close and or on the frontier in several respects.
Your comment is like 6 months to a year late.
There for awhile it seemed like we’d have 3 big competitors but then Grok 4.2 or 4.4 was just diabolical while OAI and Claude continued their significant improvements. Grok was/is so bad that I was convinced musk was gonna shut it down and just fund Anthropic compute once they reached their compute agreement.
Who uses this model? Anyone? For what exactly?
( why is the x-axis on the first chart in descending order ? )
There are no facts only interpretations. - Frederick Nietzsche
But honestly, it is because numbers are like people; torture them enough and they'll tell you anything.
looks like token efficient/verbosity took a big hit.
Output tokens from Intelligence Index:
- grok 4.6 (xhigh): 97M (for 44 score)
- grok 4.7 (xhigh): 240M (for 46 score)
which is crazy because this was grok's competitive advantage, worse than OpenAI models but better than everything else, now it's less efficient than Opus or Fable 5.1
$2/million inout and $6/million output but I couldn't see any pricing information for cached input tokens?
cached input tokens are $0.50 per 1M (prompts under 200k tokens) and $1.00 per 1M (200k+)
Do other prices vary for >200,000 or just the cached tokens?
$0.40
Did 4.6 not have an x-high reasoning level? Why are they comparing 4.7 x-high with 4.6 high?
It did not. xhigh is new to grok.
Not sure on the API side, in Cursor you can always use 4.6 at xhigh.
We've only used it through API - but you're right, now API supports xhigh for 4.5-4.7.
I think 4.6 got an xhigh after launch. The benchmarks seem to all have been against 4.6 high.
As anthropic/openai subscription allocations get squeezed you'll see more people using "second rate" closed models like grok. The token allowance with a Cursor subscription is crazy.
Any real world experience with Grok Ultra $300 monthly subscription vs Claude Code Max in terms of overall built work mileage, or general token limits?
Yeah I switched and the 300 plan is basically introductory 100/ month and I never hit the limit. While constantly hammering on it
the AA numbers are generationally bad. double token use (the one thing Grok was good at was low reasoning usage!) to gain 5% in the benchmark score. with reportedly a larger model. maybe it shows gains IRL but wow, I've never seen a new generation model look so underwhelming compared to the last.
as someone who is limited by amazon bedrock support at work (no idea why we got stuck with the worst one) - grok is literally the only budget-ish model option, so nice to see it updated, Sol and Opus are just too rich for my blood. Luna is good but so slow at getting things done (tps wise it's fast)
Are the prices on Bedrock substantially different to the rate cards of the direct APIs? Just trying to understand whether this is Opus-through-Bedrock is too expensive, or Opus is too expensive.
Dumb question. Are these products really winner-take-all? Why is there such a furious rate of development?
It’s not at all winner takes all, it’s a race to the bottom. Models are becoming a commodity
because boomers will give you free money + tip
musk can fund the space stuff with this
Not resetting limits when the model comes out though. Obvious miss. They need a Tibo.
I tried in Omp (Oh-my-pi), and so far it's really problematic.
It will loop in thinking mode ("Let me implement those fixes: Fix 1, Fix 2, Fix 3 .... Fix 80, Fix 81"), ignore the AGENTS.md instructions, corrupt plan files, etc etc... I have 5.6 Sol as advisor/watchdog, and it blocks every turn, I never saw this. Quite a shame, 4.6 wasn't so bad.
OMP is a joke. don't use that garbage
Can you explain your opinion? I'm curious but such vague comments won't convince me.
Probably the same reason as oh-my-zsh, you don't need 90% of it. Further compounding the problem in an agent harness is that you are polluting the context window by throwing the kitchen sink at it.
I've been experimenting with omp because:
- it allows different models within one session via roles (I only have API, so pay per token)
- it's much more likely (ime) to use the LSP over grep for determining how code fits together
But I agree a 20k+ starting context is way overkill.
I find it's very hard to get information on harnesses people are using. I have to stay model agnostic so I avoid claude, codex, cursor, etc. I've used and tried opencode, which worked well, but obviously lacks the above features.
Does anyone have a resource for following what people are actually being productive with? With so much vibe going on it's hard to separate the wheat from the chaff.
this summarizes the average OMP user and dev
https://x.com/greg_horvay/status/2100764473392820433?s=20
Again, this is vagueposting, what do you have against snapcompaction? It seems to be a nifty way to save token costs. At least it's an interesting innovation. https://x.com/_can1357/article/2064802476742574459?lang=en
What a crazy thread lol. I really can't tell who is serious and who isn't there.
what do you use and why do you prefer it over omp
Just pi. `pi install` the packages you actually need or ask LLM to write a package for you. Keeping the harness minimal is the point of pi.
you are a joke if you think omp is a joke.
The CSAM generation model got an upgrade. The sad part about this is that I bet it still generates CSAM. Given that the owner of the company has made a nazi salute in public and thinks CSAM generating models are cool, I don't think they addressed the issue of this generating CSAM.
Pacing the frontier, with an aggressive release cadence. Gotta love the US tech industry.
In my experience Grok especially inside Grok build is pretty solid choice, it’s a no nonsense model and stays on its course. Another surface where I truly enjoy the experience of using Grok model is Grok bot
I've had really good experiences with Grok 4.6 and grok build. I've been playing around with tscircuit and it can write code with an understanding of spacial reasoning, while also importing cad components from different file formats into tsx, I've been having claude come in and try to error check it and so far claude hasn't found anything to improve in my three projects.
I'm excited for 4.7 although I share skepticism with other users whether 4.7 will be significantly better, since they didn't raise the price.
Yah, I am pleasantly surprised at Grok Bot. Hopefully this improves CUA which has been a touch lacking w/ Grok 4.6. Grok 4.6 works but is slow compared to stuff like Astra Light.
Congratulations to the team!
32 on the omniscience index. Not terrible but far from Astra and fable: https://artificialanalysis.ai/evaluations/omniscience
Interesting hamster:
https://aibenchy.com/model/x-ai-grok-4-7-medium/#showcase=dd...
That's medium, xhigh is not much better:
https://aibenchy.com/model/x-ai-grok-4-7-xhigh/#showcase=2f9...
Grok probably hurt itself by building a reputation as the "meme AI", making it hard for some people to take it seriously
I'm one of them, and it's not because of the memes.
I'll never use an xAI product.
You're using the internet, so some of your packets might be going through Starlink.
Let a person protest jeez.
If a shitty murderous tyrant builds some roads the citizens can still use those roads while protesting against the tyrant
And I pay taxes and some non-zero amount of that money is going to Musk through various channels.
I'm still never going to use an xAI product.
That's not how the internet or starlink works.
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What's with the deceptive graph on top? Not including Astra can't have been an oversight, did the model compare poorly to it?
https://openai.com/index/our-decision-on-cursor-following-it...
This explains why. Mentioned in another comment, but cursorbench explicitly tests with Cursor as the harness, and OpenAI doesn't allow them to use Astra in Cursor.
> with a proposed shutoff date of November 12, 2026
That said, I don't expect them to benchmark Astra in their Cursor harness given the situation.
Cursor never added Astra to its consumer subscription plans. And it's likely exactly because of this announcement. Why would they add support for a model they would have to remove shortly after?
shutoff for existing models, new models stopped as of that announcement, astra will never be on cursor.
That's not accurate. OpenAI doesn't allow Grok to provide Astra to Cursor customers anymore, but it doesn't ban anyone from using Astra via alternative harnesses.
If Cursor wanted to include Astra in CursorBench nothing would stop them, they could easily have spent half an hour vibecoding in OpenAI API key support - if it hadn't been convenient to neglect to do that.
Even if they could do that (workaround to include Astra in CursorBench), that has no practical consequences for Cursor users and that's what I as a Cursor user (what I use for dev, though I use ChatGPT for non-dev stuff) care about.
It would make the benchmark way better obviously, by showing how their new model compares to their competitors, the whole point of benchmarks and graphs.
The point of Cursor Bench is to show how models perform in Cursor. If 99% of their users won't be able to access a model unless they go out of their way to include setup an API key for it (which would be insanely expensive with Astra), why would they include it in the benchmark?
If the benchmark is "what's the best model to use in your Cursor subscription", why would they do that? OpenAI knew what the effects of their decision were. Hard for me to have sympathy for either party here, honestly, and I say that as someone who is a customer of both.
Deceptive? An extremely quick google search would answer your question. OpenAI pulled out of Cursor before they released Astra so it never got that benchmark.
Pulled out from letting them resell Astra access, that's not a limitation on running a benchmark.
It is, that's how that benchmark is run. Another very quick google search.
I wonder if that means that SpaceX evals show that they consider astra better than fable or that they hate Sam&co so much they don't want to show their stuff.
https://openai.com/index/our-decision-on-cursor-following-it...
Its because of this. You can't use Astra in Cursor, and cursorbench uses cursor as the harness. They can't actually benchmark it using their harness hence why its not included.
They have Astra in other benchmarks lower on the page. They just don't want to show it winning
The chart is cursorbench though and they asked about the "deceptive graph"
They can benchmark it because you can use an openai api key with cursor. Astra is just not included in the cursor plan.
Elon posted on X that Grok 4.7 is behind Claude and OpenAI for agentic coding:
https://x.com/elonmusk/status/2102082011233931762?s=20
so it's likely about usage in Cursor specifically.
https://xxcancel.com/elonmusk/status/2102082011233931762?s=2...
this is exactly it.
Where is the Astra benchmark?
I refuse to use Grok. Mostly because of the usual reasons - somehow this high profile AI model seems more disgusting than others and it is in a way impressive.
But also Xai doesn’t seem to care about user experience and long term support.
I am subscribed to ChatGPT, Claude, Kimi and GLM coding plans. 200$ one on GPT and the 20$ ish ones on all others. Recently added Grok and it has somehow bacome my second most used model.
For daily one off questions I prefer it because it is fast enough and I like the way it responds. I also use it for basic research like “find me a battery drill for this and that”.
Kimi and GLM feel extremely coding oriented. I use them for code reviews basically. I hate the way Anthropic models talk. GPT takes too much time and effort for that kind of stuff for some reason.
Grok happened to be a nice middle ground.
You should try it, it is less sycophantic than other models and is faster and better at most reasoning levels, don't confuse the twitter bots and services also named Grok with the frontier model itself
Perhaps he doesn't want to use it because it's owned by human being who many people view as vile.
Do you know the political positions of all the CEOs you purchase from?
what are the usual reasons?
See later, i.e.:
> somehow this high profile AI model seems more disgusting than others and it is in a way impressive.
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I can't take anyone seriously who uses grok seriously. I like to look at the cybertruck owners forum every so often because it's just... hilarious. And the amount of superfluous grok use over there is just insane. Half the posts I click in there will have a bunch of people dumping entire grok takes "why do people hate cybertruck owners?" "Because they're jealous and poor," sort of stuff that they just LOVE to post.
As a technical point of reference to compare against other llm stuff, sure, I'll glance at a report or benchmark but I really couldn't care less about anything to do with the project and it could blow other options away and I wouldn't touch it.
Possibly interestingly, I can't take you seriously for having such a superficial approach.
You probably shouldn't cut off your nose to spite your face.
I don't know man, Musk doing Nazi salutes doesn't seem that superficial. He did help get Trump in power and also killed a lot of aid to children that need it.
What's superficial about refusing to use a product from someone like that? Or are you one of those 'technology isn't about politics' people? That's a superficial take if you ask me.
All technology is political, and understanding that is a deep, not superficial take. It requires systems thinking which unfortunately many people building technology seem to lack, despite software being a sophisticated complex system.
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I've never tried Grok and I doubt I ever will. In a world where trust in tech is at a low point, x.ai is pretty much the lowest of the group for me. I can't imagine using this for any production use-case, especially one where bias issues could cause litigation fears.
edit: My post was flagged (original above unchanged) This is exactly my point about lack of trust in x.ai. My suspicion that a bot from that platform flagged this is exceptionally high. You couldn't pay me to use this platform.
Try it for software development.
I have even less trust in their not training on my data/credentials/everything on my computer.
Seriously. They already get caught uploading everyone’s private credentials once before, one would have to be a particularly gullible rube to trust grok again. Especially with musk in charge.
Maybe comment on model releases you've got some experience, or insight about.
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Waiting on simonw "Generate an SVG of a pelican riding a bicycle " benchmark to judge this model
It might be more capable, but AA indicates it's a lot less token efficient than Grok 4.6: https://artificialanalysis.ai/agents/coding-agents?agents=co...
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We're allowed to have our ceremonies.
Thank you. If this whole thing isn't fun, it isn't worth doing.
You don't think it's useful to learn whether a model's "intelligence" generalizes beyond the tasks and modalities it is usually optimized for?
Absolutely not. Makes about as much sense as judging a car based on how good an airplane it makes.
Have you considered that the single most impressive breakthrough of LLMs as a technology is their ability to generalize beyond what they were explicitly trained on? Great analogy, pal, but LLMs aren't cars.
I disagree. If GPT-7 can draw the Mona Lisa in MS Paint via computer use, this would be interesting.
That it isn't the most efficient way to achieve the same end result is irrelevant.
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How do I obtain this morality build?
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We do believe that Musk is fascist
No, we don't
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Yeah. I'm actively avoiding giving mr far right any $$
Did you come up with that by yourself?
https://knowyourmeme.com/memes/mechahitler-grok
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Exactly. And it's DEEPLY DISTURBING that all comments on HN that point out that X is pro-nazi no longer has an upvote button
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Can you point at the marketing in this release to show me where that’s the lean?
Many people are allergic to “AI safety” as they perceive it as an attempt to deceive them. When they ask a factual question and get back an unfactual answer, it makes them upset. None of the people I know who feel this way are searching out CSAM. They accurately perceive that there is a team that wants answers to come out a certain way.
For instance, I’m loosely connected to people who care about animal safety in AI research. There are absolutely people spending their time pushing a narrative about _the_ ethical way to interact with animals. Feeling this not being forced onto you is kind of nice.
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I would guess those working in AI see some possible ethical quandary but resigned themselves to an attitude of "it's happening either way". Although what csam and racism are we talking about? my observation on AI is they're all pretty cucked and boring to talk to. Or is the grok ai more liberal than others and unique? I used it a year or so ago when it came out and it seemed as gated as all the others.
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Until Musk owns up to his Nazi salute, I won't be using Grok, sorry. I don't care how good or cheap it is. And no, I won't stop talking about it either.
There is no need to use it anyway, it's always been uninteresting in terms of performance. However, for me the red flag was when Musk admitted he will personally interfere in its training and prompts to make it more of a propaganda tool. I'm interested in science and reality, not in the political delusions of elderly drug addicts.
And poisoning Memphis. So disappointing that no one has principles anymore
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Is Grok relevant? Who uses it?
Maybe I'm in some kind of bouble but I have never met or talked to anyone who has used Grok.
I bought a month of use for $100. Early impressions of Grok 4.6 was that it's good at talking about ideas (got me unstuck from a piece of writing that I was working on; that bought it a TON of goodwill) and just okay as a coding tool compared to my more extensive use of Fable and Opus. Not as smart as Fable but cheaper; not as capable as Opus 5 but way less annoying along the way. And it generates images, which Anthropic doesn't do.
Not sure if I'll hold the subscription but I could see myself working with it more.
I use it in the car to talk to because it's built-in, mostly for navigation via voice. It seems to be an old or quantised model, because it seems a few years old, and it has strict rate limits unlike Gemini, where it really just shuts off if you talk to it a few times in one day, but it's still fun to show passengers who are still new to LLMs.
Sorry, english is not my first language. Itss disabled on our work API instances so my use is strictly personal because it was available on Cursor (my account is pre-acquisition). I have extensive AI experience across nearly all models, open weight and frontier and closed, I am very aware of how they talk or output. This is high/xhigh, via Cursor, not via X Grok/UltraGrok if that make different.
Grok 4.6/4.7 feel like you are less tokens because Cursor gives you double the quota subsidising Grok specifically - there is a separate Grok/Cursor model quota bar in addition to non . Its actual token drain if you are paying API rates is generally far higher than Fable, Astra et al. You are not using less tokens.
It is weird in some reward way, it will frequently, at least for me, complete the task in the laziest way possible,Technically it is done, but that's about it.
For example a user registration system ended up with users being able to log in as anyone because the authn was a cookie set with the user's pkey id, unsigned. Nearly anything it outputs technically works but if you give it a GLM or DS pass you will find dozens to hundreds of vulnerabilities of varying hilarity (Fable refused, Opus refused).
I have seen it write SQLI-vulnerable code, asked it to review a file without saying what's wrong and it did not catch it (fresh session, single file @-tagging in harness). Again, technically, the code works and does what the prompt asked, its just handing in some of the laziest copied homework I have ever seen.
If you specifically call out to use prepared statements it will typically put a plaster over this however I have also seen Grok 4.6 use prepared statements by concenating the user input raw into a statement then executing it with no ? or named replacements, rendering it somehow a SQLI-vulnerable prepared statement. One med it added a OR 1=?, replaced the ? with another 1, then said OK you are using prepared statements now.
I tried it last month after hearing here that it didn’t speak in Claudisms.
As a chatbot it’s totally fine, virtually indistinguishable from Gemini or ChatGPT or Claude.
For coding it’s… okay. I tried 4.6 and it feels similar to Opus from 12 months ago, or maybe Sonnet from 9 months ago. YMMV.
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The only people I know of in the UK who will tell you that they use it are performatively alt-right or right wing. The kind of people who say "nanny-state" or "wokerati". GB News viewers. People who have an opinion on Meghan Markle that they think other people need to hear.
It's just an observation but so far a pretty solid correlation. Musk has so severely poisoned the well in terms of his UK reputation that the only people who are open about using Grok are... well, wankers is as good a word as any.
FWIW among the AI-using people, it mostly goes Claude Code, then Codex, then whatever runs on their Mac. The only Cursor user I knew has jumped ship to OpenCode.
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I guess it’s only my opinion but having used grok for personal chat: it’s by far the worst one amongst Claude, ChatGPT and even Deepseek, Gemini etc.
The personality is bland and it doesn’t work nearly as hard or even tries to help.
> The personality is bland
I don't use Grok, but do you want your LLM to have a personality? "Personality" is exactly what people don't like about Claude.
I want my sexbot to have a personality
What if it doesn't like you
Sexbots respond surprisingly well to abuse.
longdong1
created: 9 minutes ago
That could have been said just as perfectly well from a main account my guy/guyette
That's also a kink
I used openrouter to send same prompt to qwen, derpseek, gemini and grok and found that grok does good research and produces less bullshit, especially when prompted to be critical of an idea
Ask it to be critical of the birthday photos and see where that gets you.
can you elaborate?
Elon's mother recently posted an AI-generated photo of her son's birthday party. The tag indicating such was scrubbed as soon as it was pointed out.
As stated by another comment Elon Musk's mother posted an AI-edited photo marked as such. It got edited right away to remove that label.
There are ample reasons to believe that Elon Musk is running his mother's account and that the photos weren't even real putting in question that he even had a birthday party.
If you ask Grok about what this means it will always take Elon's defence. It will vehemently deny that Elon would be capable or willing participant of such a thing even if you point out that he faked being a world class gamer, buying accounts that had done all the work and showing none of the skills when live-streaming.
> There are ample reasons to believe that Elon Musk is running his mother's account
Yeah, I'm sure the guy has time to run his mom's social media account. What's your reasons or evidence? Did you consider maybe it's a social media manager one of them hired running the account?
> it doesn’t work nearly as hard
Until you ask it to start generating horrific imagery and then it's best in class.
I would consider this a positive. I'm not interested in a company that wants to prevent you from using a tool that you're paying for.
The value of the internet is that people can share whatever they want, and use software how they want. This will mean that some people will abuse that. This is the tradeoff of a free society.
> The personality is bland
Sounds like a plus. Guess I will give Grok another try...
This has been my experience as well. Grok will end tasks almost immediately and claim "Done!". It's definitely the laziest and most "dishonest" of all the models. The others aren't perfect, but I can't use Grok for any serious coding task.
Who uses this trash?
117 million people per month. Anything else I can google for you?
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Not sure. I've never seen Grok-generated child pornography. I take it you're intimately familiar?
I have to say I'm a little perplexed by HN's perpetual willingness to use grok like it's a normal product made by a normal company.
There's often frustration that every thread related to a Musk company includes a discussion about Musk, but Musk himself caused that by being the only tech founder to actively campaign for Trump. (Zuck, the runner up, didn't do anything even close to this). Every product at every company he owns is hopelessly tethered to his decision to do that, and deserves to be judged on those terms.
Another popular story today is about US rollback of climate regulation [1] under Trump. Some fraction of every cent you spend on Grok goes to support stuff you hate, and yet people get genuinely annoyed when you point it out. Musk and his companies really _are_ special and should be treated as special.
Every thread about a Musk company or product needs a comment like this one. If we had the right values, every comment would look like this one.
[1] https://text.hrw.org/news/2026/09/17/us-revokes-limits-on-po...
Thank you for your perspective and I agree as repetitive as it is, I hope hn can continue to surface disagreement/substantial views on a topic.
These comments don't stay up much anymore and I can't tell if it's structural to the forum (flag weight + statistical mechanics of votes + guidelines) or if it's the userbase sentiment.
Except for now HN doesn't do that. Every single comment that points the issue with Grok being built by a pro-fascist team is being "locked" so that they can't be upvoted
For what it's worth, I've watched the vote fight on my comment swing back and fourth over the last hour. It got flagged, unflagged, and flagged again. It appears to now be locked and dead.
But I think it represents real malaise in the community. It's not a moderator plot, people here really just don't care and might even support this.
We really are in the minority of opinion for giving a damn about liberal democracy.
I think I was trying to bring up the mechanics of the forum as another reason.
Between the guidelines + user thoughts (e.g. repetition, low novelty/new info), there's other reasons these types of replies might end up dead.
I am worried that it leads to people self selecting to other forums biasing the remaining userbase vote/vouch/flag distributions. In an exit vs voice situation, the voice kinda dies out. Then we end up other-izing people and homogenizing our communities.
But I concede it's also possible that the minority opinion issue could be the core driving force.
dilate
Yeah, not touching xAI for several glaring reasons. I share your confusion.
I wont touch his products and neither will my organization
100% agree. It speaks volumes that HN down-votes this...
I completely agree. But this has been true for many years. This sort of head in the sand compartmentalization seems to be a core feature of the culture here.
It’s either compartmentalization, or something else
Definitely not a musk fan, but what exact is your point? Other big labs aren't innocent little virgins.
I think I already made my point, but I'll make it again.
Nobody both worked and spent their money to get Trump elected like Musk. 300 million to his 2024 campaign [1]. DOGE. On-stage endorsements. Nobody even came close.
No, other big labs are not "innocent little virgins", but they're not even in the same solar system of harm as Musk. To hand-wave at the differences is to permit them.
[1] https://www.opensecrets.org/2024-presidential-race/donald-tr...
Yes, but the other ones we don't like for ethical reasons, rather than religious reasons.
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Musk is literally burning methane for funsies, and generating CSAM and getting sued for it.
Handing corporate code secrets to his AI model is... unusually trusting.
How many years will go by before people will stop talking about the CSAM thing that happened for only a few days as if its still happening? FWIW, it's bad it was generated, but equating it to harming of real children I think is not a good thing.
And methane is a large percentage of all power production in the US. So again that also applies to all the other data centers. (And FWIW they've been winding down and shutting down the on site methane generators.)
And no corporate code was handed to AI models.
It’s not just that it was generated, it’s that they argued in court, _and won_, that it was legal, giving every last predator a nigh-on unverifiable defence.
I have to say grok, grok, grok, grok, grok. Also, anyone who doesn't modulate across models and run their own memory system is an idiot.
SpaceX AI releasing "Grok" has to be some of the worst branding I've seen in my lifetime
why? Grok means to understand intuitively. Seems like a pretty good name compared to Claude or ChatGPT, no?
It's intuitive if you're a nerd, maybe
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Vals AI just affirm that Grok 4.7 is worse than Grok 4.6 (It ranks #24 on the Vals Index at 54.2%, down 5.0 points from Grok 4.6 (#14, 59.2%))
https://x.com/ValsAI/status/2102086608476590432
Is this an ad for Vals AI? Looking at their website, the rankings don't mesh with my observed utility for almost any model outside of fable and astra being good-ish.
Absolutely not. I know Elon retweet them a lot when Grok is good. This is how I discover the company.
I like to follow them and look for benchmark for each LLM release.
Ah gotcha, not on twitter so just hadn't seen them before!
How anyone that values democracy in the United States could support any of Elon's ventures is difficult to understand.
Judging by Elon's staggering success in all of his ventures I'd say you're out of touch.
Multiple things can be true at once, he can be wildly successful while also undermining democracy.
Think we all can agree he has had staggering successes, but they have all come from having massive capital from Paypal which wasn't anything super innovative, it just solved a convenient problem at a convenient time and was awarded handsomely. Elon has put his capital to work in various ways to become successful, not all of the ways being morally sound.
He has had many failures, SolarCity and xAI and X and DOGE to name a few, but he has often bailed them out with his larger ventures.
Even with his successes (Tesla, SpaceX) he has built them up in large part by bending levers of government to his advantage.
I take issue with your use of the word "bend" here.
Can you provide specific examples of where Elon has bent the levers of government?
> Even with his successes (Tesla, SpaceX) he has built them up in large part by bending levers of government to his advantage.
So what? Thats called being a maverick. He is very very good at executing on making money which is the point of business.
> He is very very good at executing on making money which is the point of business.
Also pushing technology forward.
What failed with X? Usage today is higher than ever
Brand reputation; ROI; grok the sexual harassment bot; grok the CSAM bot; his free speech absolutism position. Take your pick.
Not to mention the clearest indication of all, revenues: https://finance.yahoo.com/media-advertising/articles/spacex-...
xAI is the most profitable part of SpaceX by far.
About half of SpaceX revenue is Starlink subscriptions. Starlink is the one profitable division; the rest of the company operates at a loss, including xAI.
That's outdated and doesn't fully include the multiple billion per month contracts.
Anthropic: 1.25B/month
Google: 0.92B/month
Unnamed customer starting in december: 1.1B/month
Starlink monthly revenue is ~1.5B/month
Isn't this to rent the datacenters though? That's not really long term revenue if xAI will eventually need them back.
Renting datacenters is their mission, now on earth and later in space (assuming they deliver).
I don't know that's moving the goalpost, SpaceX's mission was not that originally. Some could say the original mission failed and they are pivoting, Elon will say it's a means to the end of the original mission still to save face. Some read it all as snake oil
You mean because he inherited wealth? sure, that's what most losers do
All except Starlink and Tesla are burning money. I personally don't consider that "staggering success."
Hardly seems worse than supporting Dario’s antics at least vis a vis AI. There are no saints in this industry, only a panoply of flawed humans.
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The public very much voted for massive administrative reform. Are you refering to DOGE, Elon Musk's influence on elections, something else?
I personally don't like him using his position to spread fake news and racist propaganda
As if "the public" knows literally anything about how the US federal government is administered.
If anything, they voted for reduced debt burden and they got the opposite. DOGE failed at pretty much every single one of the goals that the public arguably gave it a mandate for.
> As if "the public" knows literally anything
Ah, yes, democracy!, except for when the public is wrong.
Who decides when the public is wrong? We do! Who decides "what the public voted for"? We do! So we are the rulers? No, of course, not, this is democracy.
You want to become the decider of when the public is wrong and of what the public voted for? TYRANT! TYRANT!
No, the claim above is "I know the voters' intent behind their vote based on who they voted for."
This is simply epistemologically incorrect. It's obviously incorrect in this case because voters writ large do not have any idea how the government is administered and how to improve it, so even if they claimed to be voting for that, it would not necessarily be an endorsement of any particular approach.
More specifically we know it's not true in this case because there are polls. Voters didn't even claim to care about this! "How the government is administered" was not a high salience issue to voters. Simple as that.
Nonetheless, I didn't suggest anything about overriding their votes. It sounds like you have some sensitive spots to work through (someone obliquely criticizing your idol for sucking at his job?)
being ignorant and influenced is different from being wrong, the american electorate is well known to be under informed
half of voters don't pay any attention to politics until the week or two before voting
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Only sheep call other people sheep.
Sheep often like to think themselves the wolf or coyote, it would seem.
Holy shit, what his whole speech. Yes go watch it. There is zero way. Zero it wasn’t a Nazi salute.
Fuck, it is like the denial around Jan 6th. Those idiots we’re live streaming that shit. I watched it go down live. Now they say they weren’t violent.
We can’t have discourse when we have legit video evidence and people refuse to open their eyes and choose to deny reality
Why would he make a Nazi salute and then shit all over Nazi ideology?
Which Nazi ideologies do you think he embraces? How do you reconcile all the Nazi ideologies he rejects?
He thinks it's funny and a big joke.
When did he "shit over nazi ideology"? He mentioned multiple times he favors white supremacy, and hates "empathy", how many more clues do you need?
"Hey bro, you have a lot of money but bet you can't do a nazi salute on live television"
"You're on, bro"
Weird, that's the main reason I purchase all of Elon's products https://time.com/5936036/secret-2020-election-campaign/
Привет, fellow American!
This thing is DOA. They compared 4.7 xhigh to 4.6 high to make it look like it improved. The reality is pretty bad: https://x.com/chetaslua/status/2102087511367618942
Well I "tried it out" I asked it one question, and it gave no answer and said "Sign up to use more!" I don't think I'll be doing that, no.
I can't think of a single dimension grok is winning on (capability, cost, voice), but want to stay open-minded -- anybody want to vouch for its capabilities in any domain?
If you haven't used it, how do you know if it's winning?
I think it's winning on UI for normies (grok bot) and they made some claims about being pareto SOTA (lowest cost per task completed) a while back with 4.6.
I find it to be a perfectly capable model for implementation (there are many in this class--deepseek flash, spark1.3, luna, etc). I find the usage to be very generous w/ supergrok. I find the model to be just fine for 90% of what I want to do, but I use a smarter model to plan complicated things.
> If you haven't used it, how do you know if it's winning?
I'm judging on benchmarks, and whether anybody or any company I know has ever suggested using it (not yet).
Okay, but it's winning on (some) benchmarks, so maybe you're not judging by them after all.
I don't personally make my judgements based on how many other people mention a thing, but if that gets your code written, by all means.
After the cursor aquisition it's become a quite capable coding model. If you take cost into account, it's close to the top. OpenAI is maybe still #1, but I'd put Grok at #2 (again, including cost as a factor).
It's probably the most aligned (to a single person) model out there!
For me it works well for agentic coding tasks and terminal/unix/bash (in cursor and grok build); it's also token efficient and cheaper than gpt 5.6. It's def not as good as Fable for me (I haven't used Astra much, can't comment). So it's not the cheapest, not the most capable, but it has a good mix of it for my backend, go, infra work.
The voice is the same AI slop as the others imho.
(This is about Grok 4.6, I didn't test 4.7 yet).
edit: clarified I mean agentic coding tasks
The voice is the weird part. The early Grok 4 models had a very distinct presentation unlike anything else out there. Then suddenly it made a big jump in coding ability and started sounding just like every other model.
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> it's also token efficient and cheaper than gpt 5.6.
Deepswe results show that grok 4.6 is more expensive per-task and consistently scores worse than: luna xhigh, glm 5.3, astra low, sol high/xhigh, opus 5 medium.
Grok also used almost 3x as many tokens/turns to complete tasks than all of those models (besides luna), so it takes way more time to complete a task.
There isn't much reason to use Grok at all, it's gotten better but it's still worse than every other player in the field, which shouldn't be a surprise considering until about a year ago they were just buying tokens from other providers and pretending it was their own model.
With gpt-6 luna and sol coming tomorrow it's going to look even worse too, especially if new luna retains the same dirt cheap pricing that 5.6 luna has.