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.
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 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.
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
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.
> 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.
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.
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.
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.
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.
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 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.
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
> 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.
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).
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!
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. Spent another hour of back and forth to refine it, and it's done: 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.
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.
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
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.
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.
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)
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.
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)
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.
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.
I have to say I'm a little tired of whenever a Musk related product comes up there's random nolifes that arrive to rant about politics. Luckily they're relatively rare on hacker news.
Also it's kinda hilarious how you think any money spent on Grok will go toward furthering climate change versus literally any other AI model that does the same thing. Grok at least seems to be more efficient than most models.
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.)
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.
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?
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.
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 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.
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 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.
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?
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.
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 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
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.
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.
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.
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.
Does not work for Claude, at least for me and I put it as the system prompt
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.
This fixed claude! Thanks!
> 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 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.
> 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.
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.
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.
If you can't explain it simply, you don't understand it well enough
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.
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.
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
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 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.
I've found grok 4.6 speaks heavily in Claudish. It especially likes using verbs as nouns.
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
> 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.
Using a variety of models feels similar to the benefit of having a team of individuals from different backgrounds.
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.rsBased on?
It's pretty much the biggest complaint of Claude compared to its competitors, so they really should adress it .
it's definitely not bigger. smaller if anything looking at how much faster it is
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!
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. Spent another hour of back and forth to refine it, and it's done: 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.
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.
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...
What is the default reasoning level?
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
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.
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.
Does anyone have any experience with Grok's subscription? How does it compare price-wise to the API?
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.
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)
Good thing they used 5.6 sol instead of Astra for benchmarks, the EEbench one is crazy[1]
[1]https://eebench.org/
Grok it's really expensive. I'm getting really amazing results using DeepSeek 4.1 Flash for fraction of the price.
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.
Link for the lazy?
Yes, but with subpar caching and higher cached token pricing, compared to directly using the DeepSeek platform.
I like devcontainers
Brought to you by...
By no one. For the price of 1M token you can get more and with better results with other models.
Significant regression in token efficiency compared to Grok 4.6 suggested by artificialanalysis.ai Intelligence Index Comparisons.
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.
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)
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...
Yeah, not touching xAI for several glaring reasons. I share your confusion.
I wont touch his products and neither will my organization
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.
Yes, but the other ones we don't like for ethical reasons, rather than religious reasons.
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...
I have to say I'm a little tired of whenever a Musk related product comes up there's random nolifes that arrive to rant about politics. Luckily they're relatively rare on hacker news.
Also it's kinda hilarious how you think any money spent on Grok will go toward furthering climate change versus literally any other AI model that does the same thing. Grok at least seems to be more efficient than most models.
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.
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.
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.
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?
$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
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
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.
( why is the x-axis on the first chart in descending order ? )
after using cursor grok & trae.ai for several months , grok curor is highly superior results to trae.ai
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.
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 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.
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 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
what do you use and why do you prefer it over omp
you are a joke if you think omp is a joke.
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.
Congratulations to the team!
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?
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?
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.
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 can benchmark it because you can use an openai api key with cursor. Astra is just not included in the cursor plan.
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"
this is exactly it.
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.
> it doesn’t work nearly as hard
Until you ask it to start generating horrific imagery and then it's best in class.
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.
> 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
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.
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...
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).
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.
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.
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.