Yeah, I think this is it! Google tried to hype their model but they have no chance against queen Dario. Perhaps they should just delete Gmail and say that Gemini did it. That way they would get some attention …
Page says it is now available to Ultra and Pro subscribers. Although in AI Studio it currently says you need Ultra. But it's technically released either way.
Blatantly obvious that models will not slow down. For any task, if we can build a dataset or environment of verifications, it can be automated. This will eat all of human tasks.
The fact that multiple companies can breach any benchmark means there is no ambiguity in terms of how to build AI, its just a matter of time.
Certainly Meta and Google are benchmaxxing to please public markets, but it still proves the above
but they have slowed down. the delta in capability between model releases now is smaller than ever before and i expect it to continue to diminish until we reach some kind of asymptotic maximum, which hopefully will mean turn towards optimization and local model improvements. The current frontier models running at 10x the tok/s would be incredible for my use cases
We're not living in the same universe. Look at capability year-over-year. The asymptotic maximum is wishful thinking. Someone needs to step in before this gets wildly out of control.
Year-over-year, yes I would agree with you, but that is not the cycle time of models. And while I share the same hunch as GP, I'm waiting another cycle before putting more confidence behind it.
> Someone needs to step in before this gets wildly out of control.
This sounds like a paid bot, lmao.
I wonder how much is actual improvements in the model and how much comes from better harnesses. I'd be willing to bet that the combination of better harnesses + the models being trained around agentic workflows (i.e the harnesses) has made it significantly better in many things, but it's hard to find other improvements imo.
You can see the difference between GPT 3, 4, 5, 6 each year. Same with Gemini and Claude. Look at image and text generation. Code generation. Math ability (Navier Stokes, Quasi-Riemann.)
I do not see the current training regime of "relentlessly try anything to get the task done" as a true step change in intelligence. This is one of the reasons I suspect capability acquisition is slowing.
A more intelligent model would not default to spaghetti throwing, it would pause to consider the problem fundamentals, the accuracy of assumptions, and ask questions that remove ambiguity. This however does not lend itself to increasing token sales while prices remain inflated from market and brand dominance.
i burn through a $200 claude and $200 codex plan every week. opus 5.5 is not "step change" it's just a bit better, and the benchmarks show this. Honestly with my workflow I cannot really tell the difference between the top models, they're all pretty much the same in capability, just a bit different. You can build software with all of them, and with all of them you have to validate the change thoroughly to not ship stupid bugs
Models just solved a Millennium price and you think their progress is slowing down? I will concede that their capabilities vary a lot from one field to another, but still.
A little over a year ago they were winning their first gold in an elite high school math competition. Have you not seen what they are doing in math now?
The delta isn't really slower, we're just unlocking capability bundles in batches. The capabilities bundles you care about might have mostly been unlocked already, and just need refinement, which is coming slower than the initial capabilities came, but don't discount the breadth of advances being made across all possible tasks.
The "Explore the latest" section is nearly blank for me - are there supposed to be diagrams or visual aids, or is it one headline and sentence taking up the whole page on cards?
Model announcement pages are the absolute worst. This has to be some kind of inside joke among labs, they're trying to see who can build the shittiest page.
To everyone saying not available yet: it looks from the page like Pro and Ultra subscribers have it today and given the play links, it'll probably show up in the API in a few hours.
I like this phrasing and am curious what new word or phrase we might use to describe big companies over pushing Ai internally at the expense of their product quality. This pattern is so ubiquitous across google cloud products I have taken to calling them the 21st century IBM, having been a IBM baby and witnessing first hand their fall from exceptionalism.
The internet and gaming has ruined my brain because scuffed was a way to describe a bad dungeon run in mythic plus dungeons in WoW, or a bad tower dive in LoL a few years ago. I see scuffed and think "here's a WoW/League knower".
HP is the other company to consider as analogous. And maybe more explicitly so, as they had a similar "engineering first" internal culture that degraded markedly over time to be a shadow of their former self.
And took similar companies that were quality engineering focused -- like DEC or Palm -- down with them through acquisition.
I couldn't see it either, then I clicked the 'Antigravity' button in the top right, switched back to the main screen, and it appeared in the model selector.
Same. It just told me "agent execution terminated due to an error". There was a little chevron underneath it that let me expand the error to view more. I was hoping to see what the error was, so I clicked it, and it said... "agent execution terminated due to an error".
It's crazy to me how care there is in most of these vibe-coded vibe-coding harnesses. I don't like oai's models much but I have to say their UI has by far the best attention to detail of any major player.
I'm on Pro and it's trying to get me to upgrade to Ultra in the AI Studio UI when using Argon. In Antigravity CLI and the Gemini website it's not showing up at all despite being logged in
Available in agy for me as of now, I'm running my new model benmark of having it do comprehensive code audit on one of my more complex projects, it spun up 1 subagent per audit section and it took ~10 minutes per subagent on an 800k LOC, 60k complexity, ~4k file project. Will take me much longer to go through and determine the quality of the audit work.
Antigravity CLI 1.3.4
[My account email] (Google AI Ultra)
Gemini 4 Argon (High)
~/[working folder]
> /model
⎿ Model set to Gemini 4 Argon (High)
Finally, gemini 3.8 has been falling way behind opus and sol in my experience. It's showing up in my antigravity. My work account though still has 3.6, 3.8, 3.1.
Good God, man. Google has the worst frontier lab rollout of them all. And they're delivering products that are behind the curve constantly.
Now, I happen to believe that's an excellent strategy. I bet they actually resolve more LLM requests than any other company at this point. The lay person still uses Google exclusively.
Google AI pro in the USA, if you have Verizon wireless it’s $10 a month add on. Without Verizon it’s $20 a month I believe. You can also share most of the benefits with up to 5? People.
Google One - Pro tier. I have it via Lenny's Product Pass which, imo, is a much better deal since it includes Cursor Pro, Granola, and like dozens of other paid sub tiers: https://www.lennysproductpass.com/
I use the hell out of both. Kind of sad that they took Spark out of beta-access, being able to orchestrate via your phone on something that has direct access to your Drive meant I was authoring skills and other functionality on a schedule with spreadsheets serving as databases, deterministic tests, etc.
Remembering the horror stories about lost Google accounts, I would be comfortable paying the next lower tier (100 GB) because I can backup everything myself, but not the 5TB plan, I'm sure I'll lose something if the account is lost. Hopefully these plans guarantee a human in the tech support loop.
Yeah, very true. I need to set up a recurring backup-to-external-HD automation for it. It's vanishingly easy with the app and I don't doubt they're training on all the data itself.
just cancelled AI pro myself, since I exclusively used it for AI and also pay for youtube premium family it was becoming quite the monthly just for google
if they throw in youtube premium in that package then I might reconisder
this is why antigravity is a doomed product at a pro level.
they gave away so much pro that they need to have smaller usage levels than competitors or they'll lose a ton of money. $20 was already a loss for users actually using their quota. the majority of pro users are paying far less than that.
so they'll lose their paying users, and keep their free or subsudized, which will make the economics even worse.
Oh, I didn't notice that they switched from 1.5 to 3 flash about six months ago. I know someone there and they talked about how 1.5 was hardened and it was a pain to do so on newer models that is wasn't worth it for a long time. But that convo was in the beginning of the year. I should have looked it up.
Afaict, they are targeting difference user bases, Google being after their existing user base, having lost in the developer ecosystem to the two labs and open weight models.
Corporate companies. Bog-standard office workers don't need top-of-the-line Mythos intelligence, just something to add to Google Workspace. I personally doubt developers use Gemini for coding beyond marketing materials.
Are you suggesting it’s BETTER than their competitors?
Because if it’s not, and it’s not available to all paying users (Right now, it’s only available to Ultra users), then they are behind the curve if they’re treating it like Fable.
I see it is now. I tried all the services 3 hours ago and the only interface to acknowledge its existence at the time was the API interface which told me to upgrade to Ultra.
FWIW, it's available via API to everyone. (I just tested it out via OpenRouter).
Whether it's actually better than OAI/Anthropic offerings, probably not, but if Google has managed to get back to parity, that's good for competition, prices, and increased model performance in the future. Three strong western competitors is better than two.
Moreover, you need a Google account in order to use it. I wouldn't bother paying 200 USD for it but I just don't want an entire google tracking package just for using one product.
Maybe? But it's so many orders of magnitude apart. I can easily do 1B tokens a day (output tokens is probably like 3M?).
When I see non technical people use that Google reply I'd be surprised if it's more than 1k output tokens, and with a tiny model. So a 3000x in output tokens, on a model at least 10x as expensive, I wouldn't be surprised if hardware usage is 30.000x for a dev that uses coding subs vs someone who uses the Google AI overview a couple of times a day.
And that's not counting the absurd difference in cache reads.
The slides they show in the catering video demo are so bad (in addition to having all the usual signs of AI design), I would genuinely laugh if a supplier sent me this.
I'm using this model via API. I am most excited about its ability to write the english language (or any language). My least favorite trend on twitter has been people posting 2D illustrations/3D renders as a proxy for model capability. Well-written prose is far less likely to go viral but far outstrips the importance rendering a fantasy world in one shot.
I've been trying it out via the API and the model has been a delight so far. Clear in the head, not RL-fried, distinct writing style, and big model smell. That said, the em-dash is back w/ this model.
That said, I would be so frustrated with Sundar Pichai if I was on the Google team. The botched rollout of this model seems to be entirely a matter of capacity, and Pichai has been more than happy to give it to anybody but his own team.
this happens to me as well, meanwhile Pangram claims their false positive rate is 1 in 24000 as if that should be practically negligeable. I bet it's closer to 1 in 10 for gen-x'ers
Announced the model two weeks ago to a ton of hype, model was unavailable for anyone to try. On twitter, Google folks went on a great run taking shots at Muse ("Muse who?"). The hype died down bc nobody could touch the models and meta/muse came out with a similarly capable model in the meanwhile.
At the same time, OpenAI had a disastrous dev day that led a lot of users to jump ship to Claude.
Couple weeks later, Gemini-4-argon is still unavailable on anything less than the ultra tier, which means there's no natural funnel to get ppl to pay for the more expensive ultra plan other than "trust us the model is good".
If Google had argon broadly available earlier this month they would have picked up a ton of new users.
All the power users are always jumping around by now and many hold the smallest subscription with all the models or at least two.
Narrating this as if it’s the game of thrones is a fun exercise, but it’s just becoming commonplace now that models jump ahead of each other on a weekly to Monthly basis.
> and many hold the smallest subscription with all the models or at least two
This was part of the issue, as stated in their comment. We couldn't jump around to try it for the reason that is wasn't made available to, as you say, "all the power users".
Gemini 4 is announced be available to Pro users in the Gemini app.
I mean, I heard rumors too that it would be ultra only, but that doesn't seem to be the case, unless you are specifically talking about antigravity?
Realistically, market adoption isn't going to be the result of terminally online people (like me, I confess) following things way too closely on social.
There weren't "rumors" that it would be Ultra only, that's what Google has announced two weeks ago. Happy to see they've went back on that, but I haven't seen Gemini 4 on any apps till now, and I'm a Google AI Pro subscriber.
edit: just a few hours after this comment I got access to Gemini 4 on the Gemini app. Yayy! :)
That's correct, I've misquoted it. Although, if I understood correctly, it got released to all plans together today right? Or did AI Ultra subscribers have access to it since the first announcement?
As someone internal at Google I don't understand why there's so much criticism of Google models... but right now I'm using the next model beyond Argon, and Flash 3.8. In my personal Gemini app I only have access to 3.5.
Models move so fast now and Google is very cautious about releasing them.
Because Google models are crap. They are on par with local shit models. Last time I tried they were unable to even hold a longer conversation, because they would enter loop and reiterate last answer regardless of the prompt etc.
Then basic mistakes (inferring wrong information from the given text, hallucinations...). Gemini is okay for some absolute basics and the rest of the work goes to actual frontier models.
How long ago did you try it? Gemini models seem extremely capable to me. I've been using them in ag for over a year and to me the results are great. switching to opus in ag doesn't produce any better results for me
I agree that reply was unnecessarily rude, but... idk man. I'm a huge cheerleader for Google [1], use 3.1 Pro via AI studio, I'm on a Pro plan... and I can't access this model? Not even a "4 chats per hour" type thing?? I mean, I have video generation access for some reason (no good for me), but Google's policies are baffling to say the least.
Ofc I know this isn't your fault in person, but I really wish Google would get its shit together.
...As a long time tech enthusiast I should probably stop being so delusional. Heh (cries internally)
1: lol I know who cheers for a trillion dollar company but I'd rather not cheer for OpenAI
There's nothing unnecessarily rude about my comment, they are literally unable to get their act together on product.
The top level comment blamed cheerleading but let's apply critical thinking for a second as product people and look at the funnel:
1. Potential users sees new release
2. Potential user takes time to install and set up Google harness (you already lost 90% of people here, the funnel better close quick!)
3. Potential user cannot use new model.
Then what? You hope they developed good will towards your model through this experience?
You stuck a two week wait in your funnel? Is that the definition of not having your act together or what?
We're on HN, how many of us have heard from Google staff this kind of stuff is a result of them growing so big that AI Cloud has to compete with Vertex Cloud, and AI cloud exists because Vertex Cloud needed 2 years to get OAI/Ant API keys working and they were losing dev mindshare in the meantime?
My complaint, and the complaint of many is not the models - they can be good to very good depending on use case.
What sucks, hard, is googles ability to deploy direct to devs and customers at scale when the deployment is not a longstanding Google project.
Case in point: I’m an ultra subscriber and see in my app right now an ad to try Gemini 4; meanwhile the only models I have available are 3.1 pro,3.6 flash, and 3.8 thinking.
Clicking the try gemini 4 link takes me to a demo prompt that loads 3.6 flash. Srsly
I won’t even start telling you what getting api key based access together was like a year ago.
I'm still a codex man myself but lots of people feel like opus 5.5 just gets it for some projects in a way that astra doesn't. Especially given the fact that astra and sol 6.1 are often at capacity late at night during US hours, when lots of people want to run longer unsupervised projects while they sleep. There's a general sense I've felt reaching some comment threads that openai failed to react with something better than opus 5.5 and are rushing to release small tweaks to make people feel like they're still getting something new.
Sol is just hilariously slow. Even Luna is slow. It is unusable compared to Claude. I was pretty unhappy with Opus 5 and really gave OpenAI a shot for personal projects, but their quotas are just too small and their capacity issues in the last few weeks have just been untenable. No good. Opus 5.5 is just a very good model, very efficient with usage, gets things done at a reasonable speed. Sonnet 5.5 is also a very nice worker improvement. It is probably on par with Opus 4.6-4.8.
The sense I get from your comment and the GP comment is that OpenAI’s pricing changes alienated individual users for the sake of the enterprise market. I live in the enterprise market, and was quite pleased with the changes. We don’t really use Sol 6.1, just Astra.
$500/month for 40+ hours a week of Astra usage, with ultrafast mode available when you’re near the weekly reset has made our jobs so much easier. Our product has some sciencey bits as well, ands Astra kills it as a rubber duck in this area.
As a consumer whose 20x account got downgraded, I am a bit sad. I can’t justify $500 a month on personal AI spend. As an engineering manager, I could not be happier with OpenAI’s services. Also, Codex App Server is amazing.
Hey, account created 39 days ago. Did you really have to tag that on after all the other stuff? Could you make it any more obvious?
That said this thread is hilarious because it's just an open ai sales manual debating with an anthropic sales manual. It's funny, but it's not, because the truth is that you people are just shitting all over the commons. Someone needs to kick you out but that's not going to happen here.
:shrug: I spend a lot of those token make local models better, resurrecting old hardware to make it more accessible and usable. Frontier models and AI is cool. This is my lived experience doing real systems engineering projects. My real sales manual is: https://stealthgoat.com/deepswe-flash-next.html local models are kind of awesome now and everyone should be using them in addition to frontier models. I will build the stuff I want which includes optimizing local inference engines until they are at my hardware ceiling. I use this capacity in my house to do reversing, security research, and internal OpenClaw type stuff I find useful.
They are all very slow at the moment. Some tasks are taking hours to even days. These are DevOps related tasks in which I create hundreds of servers in an agentic way. It works. But it's slow. That's still annoying.
Pulled astra 6.1 at the last moment (allegedly) and only released a dirty looper sol 6.1. Also released dots which are unavailable in EU. There may have been more but no one cared.
"Disastrous" is obviously a loaded term, and it can be debated, but from what I collect, the reasons are
- Dots. People don't understand it. Their presentation didn't explain it properly at all. Additionally, many people thought it's stupid, and that the cutesy mascots are dystopian.
- Voice mode didn't work in their presentation. The demo failed.
- 200$ plan goes 20x -> 10x usage. 500$ plan introduced, 25x usage. The contrast is stark.
- "Ultrafast": 8x pricing on subscription plan (6x API). That's 80$ input, 400$ output, 100$ cache write. Hello?! Additionally, since it generates 8x faster, it consumes your quota 8x faster. Per wall-clock minute, it's 64x more usage spend per minute of generating. People report that on the 500$ plan, their weekly usage is gone in 40-100 minutes.
- People believe gpt-6.1-sol was planned to be released as astra-minor, but OpenAI renamed it at the last possible time, because gpt-6-sol is a disaster (this I can get behind)
I've been using it for a while internally at Google. I prefer Argon over Opus 5.5 because of the clear thinking and directness. It phrases things in an organized, straightforward way.
Yes, exactly! Maybe not sarcastic but definitely using jargon and being opaque like we all know it, it’s just hinting. Feels like talking to someone who’s constantly trying to prove to me they are smart(er).
Agree I do not like the way Opus 5.5 communicates with me. It feels like it is trying to act superior in a condescending way. DO NOT LIKE. I have not used Argon yet but Gemini 3.8 Flash has been a joy to use in comparison (and so fast!) as a daily driver.
Opus 5.5 has the personality of a proud righteous nerd, definitely incomprehensible at times, unless you explicitly tells it to slow it down, it crams information far too dense.
Great model to architect and resolve eng. problems in a harness loop tho. Poor handoff.
I have used it as well. It is very dense, but it cites with evidence and has a direct and straightforward approach and manner. It doesn't really have a "tone" or mannerisms the way Opus 5 did. It follows instructions and sticks with pretty clean language by default. Argon is solid and handles long horizon well.
I have a pet theory that there's some overlap of writing patterns that A) indicate quality, clear communication and B) those that the LLMs have been converging on. As a result, we're ruining the reputation of some great writing patterns because we've associated it with AI slop.
I did at the beginning, but there is only so much you can take, and no one cares if you have read books and seen it before. There were a bunch of programmers whom I thought would understand em dashes, but they did not and said no one uses such dashes only normal hyphens.
Em dashes ended up as one of the first victims of llm age
Em dashes were already "doomed" at least half a century ago, because they didn't make it into ASCII character set - which arguably is just because they were seen as redundant on ancient typewriters; that's also why they aren't there on normal keyboards, which was a double whammy: inconvenient for programmers to support, inconvenient for users to type.
In other words, since the very start of computer era, the use of em dashes was always a signal.
My pet theory is that this was happening, because labs naturally worked to source highest quality data sources they could get. Even if they initially slurped everything indiscriminately, the obvious next step is to sort them by "quality", and bias towards the high end while trimming from low end.
So obviously, government documents, top publications from liberal arts scholars and STEM > Wikipedia > Reddit (and within, r/AskHistorians > r/all, etc.). The first group is the one most likely to (over)use correct / fancy typography.
I have a related pet theory: the telltale sign of AI writing is being too good for the context it's found in, in terms of vocabulary and style as well as structure.
What is jarring about this is precisely the quality - we associate certain styles with important (or self-important) venues, so it's uncanny to suddenly see random shitposts, copywriting spam, or regular chat replies look like work of NYT bestselling authors or legal scholars - it feels wrong in places we expect basic language, grug-brain reasoning, and lots of typos.
Also, what makes the above much more noticeable, is that AI systems don't have cross-session stylistic memory. From the POV of an LLM, that perfectly fitting, masterfully crafted starter is the first and only time it used it. From the user's POV, it's the tenth time they're seeing it in the span of an hour.
I didn't say it's copying anything. It's learning styles - all of them - in pre-training. Post-training is just about giving it the right defaults.
Doesn't change my point anyway - even if post-training, labs naturally want the LLM to come off as smart (well, except for Grok). Post-training is where they "untrained" em-dashes and such, due to complaints of users.
They were in models in the first place because they are used ubiquitously published formal writing. As, of course, are semicolons. There is nothing wrong with using punctuation for nuance and structure.
I think they just used them too much. I suspect that as they naturally form a thematic break point in writing, their probability was unnaturally high at the end of phrases and this led to overuse.
I don't ever recall seeing an LLM using them incorrectly, as opposed to simply at high frequency but correctly (although I'm sure some low param or early models must have done so at some point).
Em dashes are commonly used in most countries that speak English. I get the feeling that people from the USA don’t use them often and now have tarnished the use of them.
Do you remember when the AIs were all writing with bullet points all the time? I miss that! I'd prefer that to the current more-information-density-than-any-human-would-ever-muster approach where sentences are packed so deep you can't get any meaning by skimming.
> Well-written prose is far less likely to go viral but far outstrips the importance rendering a fantasy world in one shot.
I'm not entirely sure you're correct. Your claim boils down to "Writing natural human prose" vs "Broad use of complex software and spatial awareness". My gut feeling is that there's more untapped and fruitful applications in the second group than the first - at least in the short term.
Gemini isn't perfect but I find it a lot less annoying than other model families (personal preference or stockholm syndrome). Interested to read the reviews.
Seconded. Anthropic feel the need to limit how abusive you can be to Claude because god, I want to throttle that snotty little shit. Google don't have to do that with Gemini because it just isn't as irritating. It does what I ask and doesn't try to second-guess my requests, or do "the quick fix".
Maybe it's all about how often we encounter the quirks of specific model? Or simply that one's way to prompt triggers more annoyances with a model than another?
I'd be curious to see if people have managed to just add custom instructions to make the outputs more standardized and less annoying. I never have such annoying cases, whatever the model, it's just too verbose, but in this case I ask it to be more concise and it's usually fine.
Opposite for me. Output of 5.5 is better but its safety and moral standing skyrocketed. I am constantly hitting refusals for simple tasks, which previous generations (like 4.8) do without giving me a tirade.
Anthropic’s vision of “safe” is so frustrating to deal with, it makes me want to go back to ChatGPT.
It's been really bad at lyrics but gotten better. You look something up and it will just make something up and it takes a bit of digging to discover it's because of copyright
The previous gen pro used to have this weird tick where if you ask it a reasonably open ended question, it would number things in the response and assign each one some weird label starting with 'The...'
e.g.
X: The Parameters
Y: The "System"
Z: The "Ongoing Grind"
The first two prompts I tested in AI Studio does the same, unfortunately.
Another quite unpleasant tick was that if you specify a peculiar term in your prompt as a conversational shortcut, it would keep repeating that throughout the conversation. e.g. "...What is a bitter lesson pilled way to do this?", then you'd see it will quote "bitter lesson pilled" at like 7 places in its response. This one seems to have eased off a little.
> Across Google and our early access partners, Argon is quickly becoming the preferred model for engineers tackling long-horizon software engineering.
"Across Google", wonder how much that is because of an effort by Google to curb usage of Anthropic models. MSFT and Meta similarly are pushing for in-house models. It doesn't mean the models are better when you push your engineers to dogfood and restrict access to other LLMs.
(Not that I know for sure this is the case, it's more of a hypothesis).
Unlike most people it seems, I like all the progress in AI but I really do wish they would reign in the over-the-top marketing. I mean, can we just get this stuff to the point where I can reliably work with it to design a well-architected software project without having to constantly struggle against bloat and nonsense directions no experienced or sane developer would ever take.
fyi: argon is an interesting choice of name, coming from the Greek argos meaning "lazy or living w/out labor".
3.1 Gemini was amazing for anything non-agentic. I switched to it for my primary chatbot purposes.
I never touch 3.8, it's awful. Curious to try this, but I've yet to use any Gemini that is good for agentic work.
Also, unrelated but this made me look at Artificial Analysis to see where it lands on Cost per Task, and it ranks Opus 5.5 at almost double Astra 6. That does not align with my experience.
Because you have an android phone and don’t want to mess around with anything else(i.e the same reason people just use internet explorer on windows) or you hold Google stock so you want to support your investment :)
> The model launches today at an introductory price of $2 per million input tokens and $10 per million output tokens (with cached input tokens at 95% off).
Couldn't you just say what the price will be after the introductory period and when it'll take effect? Do they have some SKILL.md for these blog posts that requires the most important information to always be buried ten levels deep and hidden behind a login page?
> They don’t really. Most normies which are the vast majority of people just use ChatGPT. All tech folk just use Claude.
It was the case a year ago, but it's less clear cut nowadays, I've seen non-tech people using claude on their phone in the train, and many tech people seem to have switched from Claude Code + Opus to Codex + Sol over the past few month.
they are target with 6 month lag. Say, if current Gemini will be demonstrating obviously superior perf compared to Opus, many normies devs will switch within 6 months.
With the pace they're delivering models, there's gonna be 1-2 new Gemini 4 versions by December 1st, presumably with their own introductory price windows. We just got Gemini 3.8 on 2 September and Gemini 3.7 on 13 August.
I wonder if that’s more to price in the cost of keeping old models around on expensive inference hardware. It’s not like old models get cheaper to run, and a more heterogeneous fleet is less efficient to manage.
This reminds me of telephone commercials that ran back around 1987, saying they were offering long distance calls for 10 cents a minute (a pretty good price back then) and -- this was emphasized, a huge selling point -- they guaranteed your rate would never go up. In retrospect, all the lols :-)
> Couldn't you just say what the price will be after the introductory period
+1. FWIW, I didn't even get far enough to wonder about the price.
The lead (and only) sentence states "Our next era of frontier intelligence, built to solve your hardest problems" a statement equally true of any new Google or competitor model, hence completely devoid of useful meaning. I then kept scrolling down... and down... and down, giving up after a half dozen screens of big images, huge videos and some customer stories. The first sentence of every text block was equally vague or meaningless so... tv;dr (Too vague, didn't read).
Me, watching the AI world from the sidelines while using DeepSeek at $0.15($0.003 cached)/$0.60 - still bitter about the pricing changes.
It might not be as smart, though my employer gives me access to Claude, so I tried giving the same task to Opus 5.5. Both DS4.1 Flash and Opus5.5 produced nearly identical outputs.
After that, my company switched the entire engineering department to Azure hosted DeepSeek4.1 and costs were cut by 3/4. So far, no one has really noticed the change.
what is even the point of these now? labs are most definitely training on this question now. I feel like this test scratches the surface of a "real" test for these new models
It attracts at least one comment like yours on every single thread, so I guess the main purpose is to kick off a race to see who can post that comment first.
The roof is always raising month over month. If you were to make a harder version of the benchmark, what do you think you'd like to see the agents do better?
People who are unable to comment on the underlying technology or capabilities because they don't know or don't care to inform themselves sure can feel good that they have an opinion on pelican art.
Medium and high are fixies apparently, (or they have a worm gear, although the hub doesn't look big enough for that), since neither has a derailleur. That would also explain the lack of brakes at least.
Low is still obviously failing the "test". It's pedals are not actually attached to the bike either.
Medium has a handlebar that goes through the pelican's beak. So I'd say also failing.
For the high, the only nitpick would be that the bell isn't quite on the handlebars and the stripes on his scarf don't line up correctly.
What I'd kill for would be an app where you take a pic of scribbles and drawings on a whiteboard/notebook and the app turns it into SVGs you can then continue to manipulate digitally on PC/tablet.
Last time I tried, it did not. That's why there's a place on the market for an app just tuned to handle the transition seamlessly, rather than having you fucking around with prompts in LLMs.
I for one don't want a whole app for that, not anymore. It's a small task whose result is an input to something else - ideal for a tool for LLM (or script) to use.
Everyone says that until ms, apple, google, etc introduces this polished feature as part of their tablet imaging editing/document collaboration office suite. Then everyone can;t get enough of it.
> It's a small task whose result is an input to something else - ideal for a tool for LLM (or script)
Have you actually tried this? If it's a small task then why can't LLMs actually do it? Kind of like the pelican test. Every LLM can do a SVG pelican but most of the results are unusable in practice for production/productivity purposes.
Every LLm can extract some half-broken SVG hallucination of your jots, but I'm asking for an app that's polished and works accurately 99% of the time, which means a dedicated app/model tuned specifically for this task, and nobody makes this yet.
> Everyone says that until ms, apple, google, etc introduces this polished feature as part of their tablet imaging editing/document collaboration office suite. Then everyone can;t get enough of it.
I don't feel like I'm a representative sample of general userbase, so I won't dispute this too hard.
For me, it's rare but it does happen. Still, 90% of my mobile experience is "how is this so broken, why is it missing the obvious follow-up feature that completes a workflow, and why, again, am I not using a laptop for this?".
> If it's a small task then why can't LLMs actually do it?
What if they actually can?
This is exactly what Karpathy was talking about the other day[0]. If your only LLM experience is the default chat app in chat mode, then this doesn't make sense. If your experience includes using agentic harness like Claude Code/Cowork / Codex/ChatGPT Work, then it's obvious.
The LLM app in "chat mode" will just zero-shot you a pelican, or digitize your notes into SVG, and maybe improve on it a bit if you complain about the result. The same app[1] in "agentic mode" will digitize your notes, refine the SVG against the original image, reduce it to probable strokes based on high-frequency patterns in the photo and knowledge of how people write, OCR it, save both the text and SVG to your library, then extract parts you wanted and insert them into a document, typeset the rest of it, and print it on your printer - all in response to a single prompt.
LLMs in agentic mode are very good at stringing long and advanced workflows; today, if you give them shell access or computer use, they will use regular apps for you if that's the easiest way to accomplish the goal.
> Have you actually tried this?
Yes![2].
That's why I can confidently say: there is no limit to this pattern. LLMs can handle apps just fine; giving them tools just saves time and tokens.
Another example: I'm currently resurrecting a 30 year old game, and the other day I asked Claude to hack on a way to run it headlessly, so I can use my computer while it plays with it. It did, and then immediately leveraged it to just causally run several instances of the game in parallel, entirely in the background, whenever it needed to playtest something.
[1] - Claude and ChatGPT now have both modes in their mobile, web and desktop apps. I personally use Claude Code a lot, but exclusively through these surfaces (I can't be arsed to deal with TUI at home anymore). IMO, these tools are already within reach of regular users - the users just didn't notice it yet.
[2] - Not with SVGs, but equivalent with voice recordings, and yes, Claude Code set up and is managing the whole local processing pipeline. Recordings go in, Markdown (or more advanced signal processing) comes out, and in itself, it's not a task, but merely a step.
They can represent something in vector, but it's always very hard to use the result for anything else. Like, the paths doesn't make sense, aren't grouped to the logic elements etc.
Beyond SVG, these things have been RL'd on 3d reconstruction (which carries over), and I expect given the public reaction to recent frontier advancements in 3d capabilities that this will get allocated a larger share of the post training budget in the future.
Certainly true but I think the question is “does targeting the SVG pelican mean that the quality of all SVG output improves?” If so it’s a worthwhile thing to target.
It's a little bit like any benchmark, especially microbenchmarks. It is useful as far as it reflects the broader use cases, but the risk of overfitting to the specific task and not the broader ones is very high.
It's still clearly not a part of any model's training set in the sense of pelicanmaxxing in particular. It's either a capability to generate arbitrary SVGs (or even something broader), or no specific training at all.
Certainly not because all labs are pelicanmaxxing on the same exact image. Most patterns are similar everywhere. That's the result of training on the same datasets and scraped web contaminated with other models' outputs, combined with similar training methods and resulting mode collapse. Try if e.g. dolphins knitting socks in spacesuits are similar on all/most models.
> How many pelican riding bicycle SVGs were there before this test existed? What if the training data is being polluted with all these wonky results...
But Simon has demonstrated before that asking for any animal doing something silly will still get similar results from the same model.
Do you think this might be a kind of subconscious origin of your idea? A second of a move you saw in your early life / teens stayed with you as an example of an absurd thing to draw?
It's possible, but I think it's more likely that I was inspired by the TikZ unicorn thing, my love of pelicans (we have thousands of them in the harbor ten minutes from my house), and my knowledge that bicycles are difficult for humans to draw.
NGL, I think this might be my favorite benchmark, ha. While the Chinese labs asses are a bit off, I certainly have big hopes for their next versions. Their hearts are certainly in the right place.
Sadly, this is all that managers know to do: take a metric and try to optimize the heck out of it. They don't care about research, technology, "don't be evil", etc. And Google is run by managers now.
Expect Google models to be benchmaxxed as much as possible, but don't expect commensurate performance on real-world tasks.
While this might be overly cynical, it's also a powerful validation of the exact feedback loop that you want to have in an organization.
If what you say is true, then the next set of benchmarks will be written to illuminate the true reflection of real-world tasks. Then those get benchmaxxed so managers can show "numbers go up."
Repeat enough times, and you get materially and genuinely improved products.
The burden is on the press, outside researchers, and general tech industry to both write and care about the metrics that matter.
The models that are really good at 3D modeling tend to also be really good at pelicans. I think the skills are strongly related - it's about having good 2D (and now 3D) spatial awareness.
The test is always going to be hard though, because it's an absurd image to ask for.
Yeah, that's a good point. My basic pelican test doesn't allow the model to render their work and iterate on it. The 3D models all come from agent systems that are rendering with Blender or screenshotting with Playwright along the way.
I’d really like to see what each model comes up with if given a basic harness to render and iterate. They’ve all gotten pretty good at basic one shot pelicans, but seeing what they do when given a direct goal, and even getting a time lapse of each image as they edit and adjust would be really fun.
Have you looked at assbench.com? Even with threeJS rendering, screenshotting with Playwright, and iteration (check the prompt) some of the models are shockingly bad. I wonder whether the rendering quality is affected by the requirement for skin physics on click; if so, it raises a valid question about models creating pretty pictures but break when interactivity is required.
(As I said in a separate comment above, results are all bikini-clad and not revealing. However, whether it is NSFW is up to you/your work policies.)
A lot depends on what the models were specifically trained for using reinforcement learning. Modern models are generally OK and everything, but they're only really good at the things they have extensive RL for.
"Pelican on bicycle in SVG" is an adversarial example on multiple levels - out of distribution, ill choose of tool for the task, and anatomical impossibility of real pelicans using typical bycicles.
Models seem to have very interesting blind spots. While https://assbench.com/ may seem like a joke, the results are very illuminating. One might expect far better results given the detailed prompt, allowance for render checks and iteration, the number of human figures the models are trained on, and clarity of tool use (threejs).
However, result quality really drops off once you get out of the top 5 or so.
(NSFW note: all buttocks are covered by fairly conservative bikini bottoms and show no genitals, bulges, etc.)
It's obvious OAI hillclimbs the image generation -> SVG loop. I'd put money down on that being why OAI's pelicans have a yellowish tint that matches the yellow tint of OAI's earlier image models.
Buddy, there's a Pelican riding it. No real cloud is like that, no real sea is like that, no real gulls are like that. And that's fine because it's a cartoon.
Honestly surprising if other labs aren’t training for svg generation. Feel like SVG’s are going to be really useful for dynamic UI generation stuff that goes beyond cobbling Html together
Is it me or is there maybe some carryover happening where the pelicans are portrayed as expending different degrees of effort too? Like, the high effort pelican has a determined look on his face.
Is the prompt context telling the models what their effort level is, and the ambient presence of that concept of ‘high effort’ in the context window is leaking through and affecting the portrayal?
xhigh: "Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer."
low: "Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration."
simonw, your pelicans are so famous now that the frontier labs can just RLVR for SVG images explicitly.
It's a simple manner of prompt...generate concept art with nanobanana, measure, llm creates svg with text, measure the distance between rasterized svg embedding to nanobanana art....do post-training RL on a 3 million such images and matching embeddings.
I swear this will be a canonical example of Goodhardt's Law in action.
You have to switch to a new benchmark that isn't so easy to run a verifiable rewards pipeline on...Perhaps a longer horizon task where it's easy to mess up midway.
Why? Don’t you think the steady improvement in pelican bicycling SVG art is itself a worthy field of endeavor for LLMs to be optimized for?
Yes, Simon has made pelicans a benchmark and now models have grown very good at rendering them. Is there a reason to believe that this isn’t manifesting as useful skill in general in SVG generation?
The sample is too small. As long as the models are reasonable close enough to each other there is really nothing you can learn from this benchmark when its just one prompt.
It would perhaps be slightly interesting if the prompt was run 100 times for each model. I doubt the pelicans would look identical.
The models are solving Millennium Prize questions and making progress on the Riemann Hypothesis, yet the top comment is still looking at pelicans somehow. To me, it feels even more superficial and pointless than arguing about the presidential candidates' tie choices in a debate.
Why are all these AI's making the pelican's pouch so large though? Unless they have some huge fish in there or something they don't tend to look like that... Is it that it's drawing a "cartoon" pelican or something?
It starts to be so good that the model doesn't really matter. Each model starts to have its own personality, and it's the personality of the drawing, like a real artist, that defines the style of the pelican, and that makes it harder and harder to decide if it's good or bad.
At some point Simon needs to move from Pelicans to something more complex. Every time a new model is launched by major Frontier company, I already know with certainty that first HN comment on the news would be about how Model is drawing the Pelicans.
Front bicycle wheel in all Argon examples is still wrong. This bicycle will not be stable. Axis of rotation of front wheel needs to be in-front of axis of rotation of steering wheel. Frontier VLMs still do not understand how bicycles work.
Check the "high" thinking output again. For what it's worth, it's there.
However, how the front fork rake affect stability is I believe a little complex. I doubt this old article is the last word on the subject, but it's a great read nonetheless, and note especially the ultra-stability of the reversed fork bike!
As a cyclist, I tend to pay more attention to the bike shape than most people. Everyone knows what a bike looks like, but as with LLMs, most people would struggle to draw one - correctly connecting all the different tubes at correct angles etc.
I note that even these bikes are not actually rideable. For a bike to be stable, the front wheel axle needs to extend forward a little ahead of the fork - the fork must ”bend forwards”. This is what actually keeps the bike upright, not gyroscopic effects or some such. Given LLMs are generally good at basic maths, im surprised they get this wrong.
Maybe a bit less so in this case though. As per the announcements, the model was actually trained for this prompt, so was fed some training data. I can well imagine the data there was just not so good.
I feel like perhaps this is a bit too nuanced of a critique. While I do see what you are saying on many images of bicycles, there are also many that that I do not see it on. Close to half of them, in a quick Google image search, have forks appear straight and the axle is dead center on the ends of them. If there is something there, I am not seeing it even when trying to specifically look for it.
I'll also note that, using a piece of paper as a straight edge against my screen, there is a very slight forward curve on the low and a bit more on the high responses. Medium does appear to be perfectly straight.
How many cicles before pelicans become photoreallistic SVGs and them come back to stylistic artistic abstract renderings?
Also, that first tweet contains a commentary that, for me, explain a lot about the public misconception about how current AI works:
> wait, does this mean you guys are actively training svg generation? i was mostly amazed by it thinking the models doing better at it by itself due to becoming better at reasoning.
No, it's not better reasoning that drives current AI, it's better examples we have been giving them. Whole army of people generating content for the frontier labs.
Also, reasoning improving the out of distribution part, like computer use, tool use etc.
Another case where allowing oneself to anthropomorphise LLMs a little yields better intuitions.
People don't get more skilled by raw reasoning, either. They improve their skills with better textbooks (pre-training data), more practice exercises (RL data), and generally goofing around (self-play).
Recently, I’ve discovered that Claude can render great SVG versions of user interface screenshots. I ask it to substitute simple SVG friendly landscapes for any photographic images that happen to be part of the screenshots. The results are much better than they should be, especially with Opus. Usually good enough to be used on a website as a way to get an infinitely scalable, much smaller version of a screenshot. But clearly, I should try the Gemini models on this real world task. That’s where we’ll find out if all of this training to beat the benchmark actually pays off.
I've been dismissive of the SVG-of-pelicans benchmark, but last night ChatGPT (on the website, toggle set to GPT-6 High) generated some SVGs and included them in our chat. I'm not sure that this feature was that valuable in this case, but it seems that textually generating SVGs is now a product feature at least for ChatGPT. The SVGs had some clear issues and I found myself wishing that it had done a better job: the nose of the rocket is overlapping with the rocket body, and in the second image I think there's only supposed to be one orange line but it tried to add styling or something that went wrong.
- I was having trouble embedding the SVGs as links, and ChatGPT recommended Simon Willison's SVG Renderer as a workaround.
Just my 2 cents on the pelicans benchmark: I think it might help if you were a bit more explicit about not taking this one benchmark too seriously. I know you say that at times, but at other times (such as the comment I'm replying to) you elide it which can read as a seriousness about the benchmark.
Digging in the model card, "Gemini 4 is the next generation in the Gemini series, a suite of highly-capable, natively multimodal, reasoning models. Gemini 4 Argon delivers frontier performance..." If they're using noble gases there are 2 obvious lighter naming candidates and 3 larger (or 4 if you count Oganesson). I'm not seeing them claiming Argon is the top/biggest/bestest model among the Gemini 4 series, just that it has frontier performance.
Edit: noble gases not noble taxes, though the latter would be a funnier naming scheme.
Really? Reminds me of Gemini 3. It took so long before being able to get a subscription for it, and then I would run out of their equivalent of the 5-hour usage window in a heartbeat.
Yeah maybe I've just become used to how much I can use Flash 3.7/3.8 but on the less expensive Ultra plan I basically never exhaust my quota even when working over multiple projects, but this was pretty much immediate. I did ask it to audit a project but still, I do that in Flash regularly and it's not especially costly.
Yeah, the limit was exhausted weirdly fast compared to openai and anthropic models. I checked the thread to see if more people had this issue on the 5x plan, but why pay for more when it's barely usable for real work.
Which is even weirder given that the api costs are less than for the other providers
Maybe they don't really care about antigravity users. Also, monitoring usage is horrible.
It seems the model is a little verbose, using more tokens to complete a task that other similar models as stated more precisely in the linked article about Artificial Analysis's work on this model.
"Argon autonomously turns raw video to a physics-accurate simulation, estimating depth and physical boundaries, and writing the exact simulation code required to replicate those real-world environments."
Geometry could be understood today with the model but what also really matters is the sensing, friction, mass how smooth the subjects are, dexterity is a very difficult problem so solve, not sure how simulations could handle such factors
Game engines have many of these features. At one point, iirc, Unity was positioning to be the simulation environment for world model agents before we spoke about it in these words.
Meanwhile I paid a subscription and they only provide access to 3.6 Flash. Consequently, I have moved on to open-weight models. It is what happens when you screw your customers over.
I'm open to Google winning me over again, but there isn't enough hype in the world to do it. They will need to earn it after these disappointing 6 months.
I appreciate how it's being integrated into the Google ecosystem, but the user experience still feels unpolished when actually using the system. The marketing, however, is impressive.
When you are on "gemini.google.com" there is a little lock icon next to Gemini 3 and Gemini 4. When you click it you get the prompt to subscribe (pay). Once you have successfully done so, the Gemini 4 option disappears!
I have the Free AI Pro plan from when I purchased my Pixel 11 Pro. I still don't have Argon in AGY nor web nor Gemini app. I have a free product and still feel cheated.
Of all models I like to write with Gemini the most. The language appears much more natural and elegant than what even Opus 5.5 or Astra do. Also, they give 5TB of cloud storage and discounts, it’s a steal for what you get.
Agreed. It's much better at working with stuff (like documents and presentations) in other languages too. It feels like it's trained in multiple languages from the ground up rather than as an afterthought.
Claude has particularly bad prose. Somewhat improved in 5.5, but it has historically clearly been the most annoying prose among major models because is had so many obvious tics that made it clear it was Claude rambling. Still extremely verbose.
They all ramble, they're all allergic to getting to the point. But, Gemini historically has pretty good prose. Even the self-hosted Gemma models have pretty nice, inoffensive prose. I wouldn't want to read a novel written by any of them, but I tend to ask Gemini questions in chat more often than Claude or GPT, because it has good prose and is good at using the web to research.
All AI pages now include canvas animations. There isn't a single page without one. This is neither good nor bad, just an observation. I think OpenAI has the best animations so far, with Anthropic in second place. This one looks a bit off.
It's a great model. I have had it trying to decrypt the Voynich manuscript for the past couple of days without being biased by other research/other people's attempts. If anyone is interested: https://github.com/d2kx/voynich-research
> An interactive companion to our ongoing exploration
Eyes glazed over again.
Did you even read your own site before you posted it?
One of the first pages I opened:
> Smoking-gun proof of plant-label ingestion: in Row 2, the central cut root is labeled okol (f88r.15), and directly underneath it on Line 2 (f88r.19) the recipe writes...chokol daiin qoekol qoekol qockhol okol cheol...!
How about you post something you've done/built instead of just insulting other people. Spend your mornings using people stuff just to poke holes in it?
Pricing is interesting. At launch Argon is the same price as GPT-6 Sol, half the price of Claude Opus 5.5 and 1/5th the price of Claude Fable 5.1 and GPT-6 Astra.
But on December 1st Argon doubles in price - so it will be the same price as Opus 5.5.
I've kinda stopped looking at token pricing. Argon might be the same token pricing as Sol, but in Artificial Analysis' testing, Argon costs 5.8x more to run their coding tasks and 2.2x more for their general index.
Likewise, you look at Artificial Analysis' general index and it cost $8,708 to run with Opus and $2,407 to run with Argon so even if Argon's token price doubles, it won't be the same price as Opus.
Sonnet is cheaper than Opus per-token, but in their coding tests Sonnet burns through enough tokens that it's 7.5% more expensive.
So much depends on how token efficient something is and whether it gets you a good result or not, right?
Plus, if one is using a plan instead of paying token rates, what does my $200 get me from OpenAI, Anthropic, or Google?
It just feels very hard to compare pricing given that the number of tokens used can vary so much. In Artificial Analysis' coding tests, Sonnet used 7.1x more tokens than Sol. Sonnet and Sol might have the same per-token pricing, but there's a huge difference in the number of tokens used.
The model used is irrelevant when there's the critical issue where their "AI" assistant can't understand the word "nearest". Literally worse than a second-grade understanding of English.
I also have had shockingly bad results with gemini on android. Ended up giving up on it after a few months. Silly silly google with their trademark UX polish and attention to usability.
which is more or less the crux of the problem android auto's gemini implementation. It sometimes does not even know that it is in a car. The ghome implementation is also like this.
Yeah, whatever they have running on Google Maps is probably a pretty low tier model, but it is total trash. I’ve only used it twice though and that’s when it first came out. I don’t know if there have been any changes since then. The main problem is I felt like it was not keeping track of the context of the session.
This reflects pretty much every result of mine from Google these days. Not just navigation, but search too.
The only thing I can figure is that Google's consumer-facing free-to-use models are set to "reason as fast as possible with only the most basic plausibility checks." I have to correct them like this every single time.
On Android, the public APIs available for digital assistants are more limited than the ones that Google gets to use for their own products. So if you want a digital assistant and you'd like to be able to hold a button on your phone and have it open a thread with an LLM (even if your screen is off), your digital assistant has to be Gemini. You can configure ChatGPT or Claude in its place, but then they can't manipulate or interact with apps in your phone very much. Or you can use an app like that for all of your LLM use but you can't conveniently summon it.
Similarly, you can run local LLMs on your Google Pixel smartphone, but if you want them to be hardware accelerated using the chip that's included for that very purpose on your phone... it has to be Google's models via Google's apps. So you can't say "alright, a fast, local model which sounds great, but I want one that is trained to always run a search before answering, in a harness with good search tools for answering the kinds of practical questions I often ask", you're actually not free to put that together in a practicable way.
So there is indeed some competition here. But it's not really fair competition.
Often it seems like the problem with the Gemini apps is the harness, not the model itself. For example if I upload an image PDF it recognizes text worse than if I use the API.
The auto version is extra horrible because what it reads to you is just a summary of what the model actually said. I don't ask it anything when driving because it's too frustrating.
this is like that tiktok guy who asks the spoken ChatGPT model very simple questions, like 'count down from 60', or 'how many e's in seventeen' or whatever and the model shits the bed every time it's hilarious
I think these companies have good models but expose them poorly like others have mentioned
Is this from you car ? Gemini in car is probably less intelligent than a spider.
I tell it to "Play Let it go from frozen". It plays it on youtube music. 5 seconds later I tell it again 'Play let it go from frozen" it then just dies saying "I can't play videos in car".
Just switched, and it seems to be much better. I'm hoping it stops lying. I have Pro max subs for Claude, Codex, Grok, and Google AI... I was forced into using Google by running out of credits elsewhere.
I have found that Gemini often claims it did something, but didn't actually complete the task.
I just had 3.8 Flash do a major refactor -- that never should have needed to be done in the first place -- and switched to Argon 4, and had it review it.
Almost everything had been stubbed out by 3.8, and none of it was properly integrated into the codebase. :facepalm:
I would love to try it out, and the Gemini models had previously been some of the ones I'd liked best in an overall sense, but unfortunately their updated inference endpoint is no longer ZDR on OpenRouter (change takes effect on the 18th). I think this is one of the more unfortunate turns in AI development in 2026, as it seemed like labs offering it was becoming the norm last year, and Google had previously done so consistently.
AI Studio has never been ZDR (retention is noted at 55 days max), but paid usage is excluded from training. Vertex uses enterprise terms, and it's definitely ZDR/no training. What's happening on the 18th?
Why can't the Gemini model code?
I'd guess Gemini probably used the best dataset.
Even Google is the place where the world's best coders are gathered, isn't it?
Yet the GPT code from OpenAI, which collaborated with Microsoft, is beautiful, while the Gemini model's coding is trash.
I have no problem with Gemini Flash 3.8 for coding, though I only use Elixir which is one of the better languages for LLMs. Where does it fall short elsewhere?
I'm still waiting for a model which I can tell to "take these 3 screenshots and make a product launch video", where it doesn't randomly modify the screenshots or garble/rewrite the text as it moves the screenshots around the video.
Every time I try to generate one it's like a slot machine, where a different part will be messed up after fixing the first.
I dont have that problem with opus5.5. I dont even take the screenshots anymore (it does all screen recordings)... I tell it a simple narrative and it follows through. e.g. https://x.com/plannotator/status/2108589088139886769?s=20
I'm constantly blown away by it. I do think Astra is slightly more intelligent (although worse at this particular benchmark), but Opus 5.5 has become my default model for 99% of what I do. It's so good.
Truly S-tier. It's sharp, creative, intuitive. Can't believe how much better it is than Opus 5, then they went ahead and made it cheaper and faster too.
Interesting! Do you have webgl disabled for incognito or for chrome in general? I wonder if it's trying to do software rendering.
FWIW, I have literally the exact same configuration (M3 air, google chrome). Here's a recording on mine where I'm seeing 60fps: https://non.io/video/video-3587018401.mp4
Mine doesn't stutter on on Firefox on M1 Max, but it pins 7 cores the entire time the page is open, not just while loading. It also uses 50% of GPU in addition to that.
Edit: The argon built site pins 1.3 cpu cores. The Sol 6.1 site uses 0.18 cores.
Nice research, you are right! Seems that low power mode was on. I have been using the web, Netflix, Apple TV app, and anything else just fine without ever noticing a thing though.
So that all being said, a normal website should work totally fine on low power mode, and this should definitely be a negative on the Opus implementation.
> and this should definitely be a negative on the Opus implementation.
I would disagree with this based on two things:
1. the prompt, which explicitly states to render the planets in the background in 3js (thus the gpu implementation).
2. the purpose of this, which is a test of its ability to convert an image design into a html/js/css implementation that matches it as closely as possible. I've talked about this before when it's come up[†]. The purpose is to be a good test, not a good design or website.
For reference, here's the full prompt used:
> Create a web page implementation from the following instructions: https://diffui.ai/build/Futuristic_Interior_UI_build.md?auth... dont reference any other folders that have similar builds. Focus on the flowing SVGs. Animate elements that make sense to be animated. For the starships that have planets in the background, ask for high quality images with the windows as a transparent background, and recreate the planets behind them in 3js. It should be one single page application that I can just open the index.html file to view.
Glad to see them abandon the absolute train wreck of their model naming "strategy".
Gemini Live vs. Gemini Lite vs. Gemini Pro vs. Gemini Flash vs. Nano Banana Lite (that one apparently has no Gemini prefix?)... Please, just pick a metaphor and stick with it without wildly mixing reasoning modes, model sizes, and input/output modalities in the model name!
I hope all the people very concerned about AI safety are cheering this one. The best guard against one AI swarm taking over is having multiple adversarial orgs all with similarly advanced AI swarms.
I wonder if any of the AI safety people will begin encouraging AI researchers to swap jobs to work at a failing lab in order to keep them all extremely competitive with one another.
Right now there are two top posts one about GLM-Legal and one about Argon. Both score about the same in the Harvey Lab test, but the prices are $0.15 versus $10.55, the $0.15 is Vals AI's estimate using the base model since GLM-Legal has not published prices.
Yeah, but one is a general purpose model, and the other one is specifically geared towards the legal field. Considering Opus 5.5 only gets a 4% on the test compared to Gemini’s 20%, that’s actually pretty incredible.
In particular, where cost is the x axis, a well-funded company with a good but not best model can discount their new model until it reaches the frontier. In some sense this is as much a statement about the efficiency of markets in the presence of public measurement-based comparison and public list pricing as it is about research pace.
Why do these benchmarks often show models running on Max i.e. Opus 5.5 (max) is on the frontier? I would think it is never really economical to run max
Muse reminded me we should have a time based chart as well - this year I hope we will begin to see time to completion stats at various intelligence tiers. The waiting makes a lot of things more tiring.
It passed the test of using latest crystal-lang concurrent feature (with web search) when gemini 3.8 flash failed (again, with web search enabled). I think it is at least useful for coding, for sometime.
>"Argon helped the Chrome team separate core webpage handling from a ~6 million line legacy folder of browser features held within Chromium’s 40 million-line codebase. Piping multiple clean code changes at a time, Argon helped the team finish an architectural refactor across hundreds of files, completing months of work in weeks."
Now that needed to be done for some time!
Regardless of if an AI helped or not, regardless of whether that was Google's or some other AI or not (though Argon does sound pretty cool!), regardless of whether an AI cut the time from months to weeks or not, refactoring Chrome -- decomposing it into individual clearly demarcated non-tightly coupled software parts with core webpage handling at the center -- that needed to be done for some time!
Now all of that being said, Gemini 4 Argon does sound pretty cool, and we congratulate both teams at Google -- the team that created Gemini 4 Argon, and the team that refactored Chrome with it!
But all of that being said, while the advancements made for Gemini 4 Argon are important and impressive (and they are!)... refactoring Chrome properly (IMHO) is slightly more important and impressive!
(You know, one man's humble opinion! That is, I am not the guy who is responsible for awarding performance-based bonuses at Google at the end of the year, so take everything I say with the proverbial "grain of salt"! :-) I am probably biased, one way or the other! :-) )
Only available on Ultra, so I thought maybe I'll try it for one month to see if it's good. Well, I have Google One and for some reason this means I cannot sign up for AI Ultra? This is just one of the worst product rollouts I've ever seen
I checked gemini, set it to "gemini 4 argon" and it offered me Pro and Ultra to get access. I checked the normal plans, saw there is also plus.
Okay, so I'll get Pro to try it.
I subscribe.
No gemini 4.
The most generous reading I have is that it's a mistake. But I also downloaded the PC app, and now I really wonder why I did that, it seems to offer nothing beyond the web experience and also doesn't even know its a local app. (When asked about its capabilities it always responded with reasons pertaining to it being a web app.)
It's available to Pro in the Gemini app (and the gemini.google.com). It isn't available in antigravity. They know that the people who are using these tools for coding are most likely to cough up for the Ultra subscription.
EDIT: Okay, the AI plans page claims under pro - "Expanded access to Gemini 4 Argon in Google Antigravity." So maybe it is just a matter of it rolling out. Though Google has a long history of serious confusing and misinformation on those tier descriptions.
EDIT2: And they changed it again, and now it is explicitly excluded from antigravity for Pro users.
Not available for AI Pro subscribers in Antigravity. What a disappointment.
Google...why. You keep getting so close but constantly fumble at the last moment. I can use Opus 5.5 and Sol/Astra on the $20 Anthropic and OpenAI plans.
You are already playing from behind. You need to GET YOUR MODELS INTO MORE PEOPLES HANDS by any means possible. Continuing to make it difficult to use your products DOES NOT HELP.
This model might be great but the majority aren't going to subscribe for $100/month just to try it.
Have they announced that it definitely won't be? If not, it might be just a roll-out hiccup, because Argon is available to me as an agent in Xcode and I only have a Gemini Pro subscription. (Whether or not I'll ever use Argon in Xcode is a different question. I've been so impressed by Claude that I rarely even use my Codex sub. I'll be very interested to hear from others how well Argon does with Swift and SwiftUI.)
I seriously doubt their ability to double API prices on Dec 1. Token prices are in a clear downward trend and Google should maximize revenue by competing for volume. Currently OpenAI is the only US frontier lab trying to seriously compete with open-weight models that you can run yourself for an order of magnitude lower than what frontier labs want to charge
Adding my five cents: initial usage through OpenRouter has been great. Very fun model to spar with, clever, intelligent. On par with Opus 5.5 but without the Claudism's and more of a Sol type of conversation. Though speaking of Sol, I've been very dissapointed with Sol 6.1 to the extent that I feel OpenAI has neutered it compared to a few months ago. Especially when giving it goals it will happily run in dumb circles just burning tokens without any real work.
I gave the model my usual question of "I got a raise from X to Y, please explain what is the impact on my net salary". Answer was detailed and nailed all payroll edge cases, only to miserably fail in basic math at the end. It tried to calculate 430 minus 60 and got 410.
I just created a Google account, which was a hassle. I tried to find an app and found AI Studio, but I’m not sure what that is. Then I found Antigravity, which apparently is Google’s alternative to Codex, and I installed it. Then I tried to buy the small Gemini AI Ultra package, but it didn’t let me pay. It accepted neither my credit card nor my PayPal account. It’s crazy how bad the Google experience is nowadays. You don’t know what to use or where to find it, and the security measures seem totally overkill. Am I really the only one having these experiences? Is Google aware of that?
Using google services has always been miserable. It used to be way worse. Now you can at least get an api key from AI studio without going through 20 esoteric steps to configure everything.
I hate everything with Google and consumer facing services, they dont give a shit because 99.9% are monetized through spyware or are buisness customers.
They had gemini cli, what happened to that? Was fine
Same thing, I've always paid my bills, I have had some sort of google subscription for the last 10 years. Now they're requesting me to switch to pre-paid billing. They won't accept my card (that has worked every time this year so far).
Is there anybody in Google having a look at how bad and complicated their payment system is? In all the other AI providers you just sign in, pay, get a key, done. In other clouds like AWS, you add a card, pay little to verify the card the first time, monthly bill, done. In Google it looks like you have to fight them every time for the very thing they should make as easy as possible: opening your wallet.
I bought a google play card (or whatever it's called) with cash due to these issues. Result: Instantly rejected + locked after entering the code, no credit, no dispute, no customer service, no refund.
First install Antigravity and see if it works on Free with your account at all. You can buy Ultra and then find out you don't have "Antigravity eligibility" on a given account or it will ask you to send SMS to some nonexistent number.
I would also advise against buying Gemini if you have any other Google services, because you get banned across board if they don't like something. To use Google it's best to first migrate off of Google.
Otherwise great product, I really like and would recommend Gemini. The usage is also very generous, at least Flash models.
I recently had to verify my YouTube account with a phone number recently because it requires this in order to set a thumbnail.
Questions right off the bat:
1. Why do I need to verify to post a thumbnail that will take 1MB on their servers but not to post a video that will take 100MB on their servers and be public??
2. Why do I need to verify my phone number on YouTube when it's linked to my Google account which has a verified phone number and 2FA etc.?
In any case, it takes you to a CSS-less page that asks you to choose between getting an SMS or being called to get a code. I choose SMS and it doesn't work. It shows an error message with no description just "something went wrong". I try a few times and it keeps not working.
I then switch to the call, and guess what! I have tried "too many times" and will have to try again later. Call worked the next day, but geez, what a mess.
i live in French Polynesia, a French territory, i'm a Google AI subscriber and i can't use Google AI Studio or antigravity cli because i'm in a geo restricted area ...
It seems Google has no issue laying out cables across the Pacific Ocean from/to Tahiti, they don't have an issue selling their services and plans there but i can't use AI Studio or antigravity cli because of geo restrictions ...
I think it’s a typical strategy for scammers to create a new account and then immediately try to buy an optional service with a stolen credit card.
What you did isn’t wrong, but is unfortunately very similar to what real scammers do. The heuristics behind these anti-abuse efforts are always going to have false positives.
This is the first time I'm hearing about this email (thanks!) and I'm wondering: If it was already known in 2003 how bad Windows was, how did we end up with a Windows that's so much worse? Bill said it was his job to send such emails but apparently he didn't do his job very well…
Yeah, a month ago I wanted to test out Gemini-3.5-Transcribe, but had to wait a completely indeterminate time, got the offensive message "Your Google Cloud billing account is being processed. Processing time varies from a few moments to a few weeks.", like I'm just worthless scum. Took over a week for no reason.
Ended up with Soniox instead, took minutes to get started.
I recently tried to create a new Gmail account for a small app I've made. I wanted a way for users to get hold of me other than my personal email address.
They now ask for your mobile number during signup. And it wouldn't let me register any more accounts with my number. So frustrating.
That said, asking Gemini.google.com to walk you through the steps seems to suffice. In fact, one of AIs big perks for me is walking my through kafkaesque systems like Google’s to cut the shit and get to the result
In the same boat, I have a single seat Google workspace account, and can't figure out how to add Argon to my workspace. Asking Gemini seems to make it hallucinate pages that aren't there.
Is there a benchmark for reverse engineering compiled programs?
- Grader compiles a program to binary -> Agent has to reverse it back, and match all bugs and behavior.
can for the love of god we get some usage in cheaper subscriptions being Ultra tier only is annoying. I want to just test it out here, well will burn some money via api I guess.
As I approach a transitional period in my career, I'm reflecting on the managerial effort of places like google. How on earth do they keep an engineering org on the 'right track'? I work on products that are not as complex: fewer moving parts, fewer egos, no where near as novel. It feels like nobody does anything and nobody has any expertise
Success for google is defined in a different way than it would be for an ordinary company and many of those would have been successful if they had started outside of google.
The really annoying ones are the ones they buy, and then shutter because they can't make enough money on them fast enough.
Makes me wonder if more growth/innovation could've happened (outside of google) if they didn't employ this many people. Some sort of dutch disease within the higher echelons of the tech sector.
Google did a very good job on things that required longer research times and compute scale, note that Transformers, BERT & Scaling Laws came out of Google (though the latter were also worked on at OpenAI).
Conversely, Google is horrible at product, and without OpenAI, it probably would have taken many years longer to take off. I know this because Google had demos of this internally, but absolutely no stomach to release it, and they didn't believe in the API use case at all.
Which is to say, I think if Google was smaller, we probably would have gotten more SaaS, not more breakthrough research.
It’s like the USA. How do they keep people on track? They don’t. You delegate and hope things work. When they have Google Ads and Search they can experiment a lot and “waste” a lot in search.
They haven't solved management and definitely don't keep things "on track" globally. However, they definitely don't have the problem that nobody does anything and nobody has any expertise.
It's also worth noting, Gemini 3.5 Pro never came out.
Having worked there (but only in a small part of it that eventually got absorbed into Gemini), it's some combination of:
* The eye of Sauron (management) can make specific spots (e.g. Gemini) push harder (and attract the motivated people at the company and be selective)
* They hire a lot better than average (Generally from the top 10%, hotter places in Google are more selective)
* They have a promo process that gives career motivated people a way to prove themselves (not always aligned with things being on the right track ofc, and not always non-political, but they definitely do something)
* Redundancy in teams causes them to compete (not necessarily productively)
Of course, there are other downsides not listed here (insane bureaucracy for launches, GDPR/BCID compliance, etc, etc), but a lot of what makes Google possible is the insane amounts of cash Search throws off.
I made a NHL inspired hockey web game with Opus 5.5, and I let Argon loose on it to try and see if it could improve it, and it found a ton of bugs and improved performance and load times significantly. If anyone wants to play it here:
I ran it through my own coding eval today using pi/OpenRouter (11 small bug fixes from my own projects). It solved 10 of 11. Compared to Sonnet 5.5 and GPT-6.1 Sol, a median run cost me $0.52 vs $0.18 for Sonnet and $0.09 for Sol, and took ~4 minutes vs 32 seconds and ~1.5 minutes.
It thinks a ton, ~24k output tokens a run vs ~3k for Sonnet. It missed a solution by thinking its way into a 10 min timeoout.
Something to look out for - if you're using pi, it doesn't have Argon in its catalog yet and reports cost at Kimi's rates, about a third of what OpenRouter actually bills.
As of my knowledge cutoff, three of the top state-of-the-art large language models are Google's Gemini 2.5 Pro, OpenAI's o3 (and GPT-4.5), and Anthropic's Claude 3.7 Sonnet.
I use Gemini all day at work via the chat interface. It's rock solid. I find it hard to understand which model it's using though. Am I already using Argon, or does it switch models according to the subject?
I haven't tried it for coding yet, but I ran a couple of my recent curiosity driven queries from Claude (mostly used Fable and Opus 5.5) through it.
This is a clear step change, I'm genuinely amazed.
Its answers are to-the-point, logically structured, clearly written. Like a really well made mini essay on your question.
It also really likes to build little simulations / models that you can tweak the parameters on. Amazing to explore how different assumptions affect economic scenarios, for example.
It's also great at picking (sourced) illustrations.
I'll be using this for everything that isn't coding from now on.
We have this same point made every release. I wonder if models actually are getting better or if these companies are just secretly hamstringing the previous models before releasing a similarly performing model
I think it takes a while to start finding the weak points in a model. It seems fantastic until you use it enough to find out that it hallucinates APIs, or can’t count letters, or uses too many em-dashes, etc. you don’t really know someone (or something) until you’ve lived with them (or it).
I'm not the poster you responded to, but I can tell you that historically the Gemini models have lagged behind Anthropic (the clear leader) and OpenAI's best models where coding in particular is concerned. Opus 5.5 is, right now, the consensus best coding model.
That said, I'm extremely impressed with Argon thus far. I take back everything bad I've ever said about their AI strategy. Argon is very good and very fast. It might be competitive at coding, but it's too early to say.
I'm a bit confused, all the announcements say that this is availabe to Ultra and Pro subscribers, but in antigravity, it's grayed out and says it's only available to Ultra.
I've asked Argon to do 3D model for me. It said that it can't do it. I've linked promotional materials and said that it actually can. It agreed and got me a model (not a great one). Man, why is Gemini like this? Every time I fall for the hype I get disappointed.
People should appreciate Google more for how all of their models have:
- Natively multi-modality
- Enormous context windows
- Reliably cheap prices
It's like they don't release a model until it passes the above checklist.
Most providers have some mixture of these three occasionally, but with Google, every model is consistent. This kind of consistency is really nice to have.
It's nice to have it available for more complex tasks, but I'll stick with 3.8 Flash thanks to its high output speed. I really like it for fast iteration and prototyping.
Classic Google: Clicks the "Try in Gemini" button from the Gemini 4 page, gets a page that defaults to Gemini 3.6, with no option to try Gemini 4 without upgrading.
If they don't want to make it available even for small tests for free, that's fine, but then don't put a button suggesting I can try it without qualifying it...
EDIT: It's actually worse: The page then shows "Look what you can do with Gemini 4" and a "Let's go" button that leads to a bunch of links to examples, all with enticing pictures. Except if I click on them I get a box stat strongly suggests it'll run with Gemini 4, except the dropdown shows "Flash" and if you click on it, it shows as Gemini 3.6 again, and if you run it, the results unsurprisingly end up looking nothing like their pictures.
I don't know if that page was built by humans or AI, but clearly nobody tested it properly.
I have $6 free credits from Google. The hoops you have to jump through are insane. $200 free credits from Anthropic are stupid simple to use. I know which one I’m using…
username_my1 | 6 hours ago
idbnstra | 6 hours ago
w4yai | 6 hours ago
nitinreddy88 | 6 hours ago
bigyabai | 6 hours ago
theplumber | 5 hours ago
bigyabai | 5 hours ago
https://youtu.be/DlTNN0gvkLM
modeless | 6 hours ago
llmslave | 6 hours ago
The fact that multiple companies can breach any benchmark means there is no ambiguity in terms of how to build AI, its just a matter of time.
Certainly Meta and Google are benchmaxxing to please public markets, but it still proves the above
efficax | 6 hours ago
alecst | 6 hours ago
verdverm | 6 hours ago
isqueiros | 5 hours ago
I wonder how much is actual improvements in the model and how much comes from better harnesses. I'd be willing to bet that the combination of better harnesses + the models being trained around agentic workflows (i.e the harnesses) has made it significantly better in many things, but it's hard to find other improvements imo.
alecst | 4 hours ago
llmslave | 6 hours ago
verdverm | 6 hours ago
A more intelligent model would not default to spaghetti throwing, it would pause to consider the problem fundamentals, the accuracy of assumptions, and ask questions that remove ambiguity. This however does not lend itself to increasing token sales while prices remain inflated from market and brand dominance.
efficax | 5 hours ago
david-gpu | 6 hours ago
cma | 6 hours ago
CuriouslyC | 5 hours ago
IanCal | 6 hours ago
Like a working scroll on a webpage.
God damn this is impossible to use of safari mobile.
rs_rs_rs_rs_rs | 6 hours ago
jedbrooke | 6 hours ago
InvisibleUp | 6 hours ago
jstummbillig | 6 hours ago
winwang | 2 hours ago
pierreozoux | 6 hours ago
throwawayy6767 | 6 hours ago
medler | 5 hours ago
oh_no | 5 hours ago
dymk | 4 hours ago
yipinwong | 3 hours ago
Argon is trying to solve the "hard" problems like those.
layer8 | 3 hours ago
boutell | 3 hours ago
InsideOutSanta | 3 hours ago
tekacs | 6 hours ago
catigula | 6 hours ago
owlninja | 6 hours ago
verdverm | 6 hours ago
I like this phrasing and am curious what new word or phrase we might use to describe big companies over pushing Ai internally at the expense of their product quality. This pattern is so ubiquitous across google cloud products I have taken to calling them the 21st century IBM, having been a IBM baby and witnessing first hand their fall from exceptionalism.
wyldberry | 6 hours ago
catigula | 6 hours ago
cmrdporcupine | 6 hours ago
And took similar companies that were quality engineering focused -- like DEC or Palm -- down with them through acquisition.
kridsdale1 | 5 hours ago
cmrdporcupine | 5 hours ago
mistic92 | 6 hours ago
xbmcuser | 6 hours ago
w4yai | 6 hours ago
fridder | 6 hours ago
ano-ther | 6 hours ago
PorciiVorbesc | 6 hours ago
PorciiVorbesc | 3 hours ago
moecables | 6 hours ago
niek_pas | 3 hours ago
This is in the Gemini app on macOS.
wslh | 5 hours ago
Gallows4574 | 5 hours ago
edit: It failed on the second prompt and they disabled it now.
melasadra | 5 hours ago
EDIT:
Apparently Ultra subscribers gets Argon everywhere including in Google Antigravity
Pro subscribers only get them in Gemini app and Search
jonesy827 | 5 hours ago
https://antigravity.google/blog/gemini-4-argon-in-google-ant...
niek_pas | 4 hours ago
> Gemini 4 Argon is available today for Google AI Pro and Ultra subscribers
ehsankia | 2 hours ago
1. It's available to Pro in Gemini app, but NOT antigravity (for coding)
2. It's a phased rollout and Ultra got it first, Pro is coming later
The latter blog post is specifically "Argon in Antigravity" versus the other blog post is about Argon in general, so seems like #1 is more likely.
efficax | 5 hours ago
copperx | 4 hours ago
caminanteblanco | 5 hours ago
https://one.google.com/about/google-ai-plans/?icid=microsite...
freakynit | 5 hours ago
It seems to be rolling out gradually.. not available at once to everyone.
ChadNauseam | 5 hours ago
It's crazy to me how care there is in most of these vibe-coded vibe-coding harnesses. I don't like oai's models much but I have to say their UI has by far the best attention to detail of any major player.
SwellJoe | 2 hours ago
yegle | 5 hours ago
It doesn't show in the desktop UI.
rahimnathwani | 5 hours ago
frangonf | 5 hours ago
> Gemini 4 Argon (Medium)
ehsankia | 2 hours ago
schleck8 | 5 hours ago
hnfong | 5 hours ago
bretpiatt | 4 hours ago
gandreani | 3 hours ago
vegnus | 6 hours ago
bla3 | 6 hours ago
zf00002 | 6 hours ago
mridulmalpani | 6 hours ago
jacquesm | 4 hours ago
aliljet | 6 hours ago
Now, I happen to believe that's an excellent strategy. I bet they actually resolve more LLM requests than any other company at this point. The lay person still uses Google exclusively.
nateb2022 | 6 hours ago
hersko | 5 hours ago
acmotifs | 5 hours ago
paimapi | 5 hours ago
I use the hell out of both. Kind of sad that they took Spark out of beta-access, being able to orchestrate via your phone on something that has direct access to your Drive meant I was authoring skills and other functionality on a schedule with spreadsheets serving as databases, deterministic tests, etc.
Hope they roll it out to a full feature soon
ASalazarMX | 5 hours ago
paimapi | 5 hours ago
freecodeio | 5 hours ago
if they throw in youtube premium in that package then I might reconisder
crossroadsguy | 3 hours ago
lanthissa | 3 hours ago
they gave away so much pro that they need to have smaller usage levels than competitors or they'll lose a ton of money. $20 was already a loss for users actually using their quota. the majority of pro users are paying far less than that.
so they'll lose their paying users, and keep their free or subsudized, which will make the economics even worse.
sroussey | 6 hours ago
cubefox | 5 hours ago
sroussey | 5 hours ago
dbuser99 | 6 hours ago
tireonfire | 6 hours ago
verdverm | 5 hours ago
steego | 5 hours ago
More specifically, who are they targeting with Argon and why is it behind the Ultra plan? Who is paying $99/month if not developers?
fschuett | 5 hours ago
Corporate companies. Bog-standard office workers don't need top-of-the-line Mythos intelligence, just something to add to Google Workspace. I personally doubt developers use Gemini for coding beyond marketing materials.
alephnerd | 5 hours ago
verdverm | 3 hours ago
There is another subset in the Google Workspace for enterprise clients.
steego | 5 hours ago
Because if it’s not, and it’s not available to all paying users (Right now, it’s only available to Ultra users), then they are behind the curve if they’re treating it like Fable.
It’s tone deaf.
copperx | 4 hours ago
steego | 2 hours ago
epihelix | 56 minutes ago
Whether it's actually better than OAI/Anthropic offerings, probably not, but if Google has managed to get back to parity, that's good for competition, prices, and increased model performance in the future. Three strong western competitors is better than two.
I_am_tiberius | 6 hours ago
w4yai | 5 hours ago
redox99 | 5 hours ago
Unique users, maybe. But a simple query that's answered in a paragraph is negligible compared to devs running agents continuously for tens of hours.
freecodeio | 5 hours ago
redox99 | 4 hours ago
When I see non technical people use that Google reply I'd be surprised if it's more than 1k output tokens, and with a tiny model. So a 3000x in output tokens, on a model at least 10x as expensive, I wouldn't be surprised if hardware usage is 30.000x for a dev that uses coding subs vs someone who uses the Google AI overview a couple of times a day.
And that's not counting the absurd difference in cache reads.
sva_ | 6 hours ago
That was a long wait.
algoth1 | 6 hours ago
spwa4 | 5 hours ago
matt123456789 | 4 hours ago
spwa4 | 3 hours ago
timpera | 6 hours ago
verdverm | 6 hours ago
postalcoder | 6 hours ago
I've been trying it out via the API and the model has been a delight so far. Clear in the head, not RL-fried, distinct writing style, and big model smell. That said, the em-dash is back w/ this model.
That said, I would be so frustrated with Sundar Pichai if I was on the Google team. The botched rollout of this model seems to be entirely a matter of capacity, and Pichai has been more than happy to give it to anybody but his own team.
algoth1 | 6 hours ago
thmorriss | 2 hours ago
kypro | 2 hours ago
I think there was a lot of misplaced hate of the em-dash due to all the low-qualify AI slop people were trying to pass off as their own for a while.
algoth1 | an hour ago
leoooodias | 2 hours ago
johnisgood | 2 hours ago
gfody | 52 minutes ago
Quarrel | 2 hours ago
If you just want good llm text, it’s great.
postexitus | 5 hours ago
postalcoder | 5 hours ago
At the same time, OpenAI had a disastrous dev day that led a lot of users to jump ship to Claude.
Couple weeks later, Gemini-4-argon is still unavailable on anything less than the ultra tier, which means there's no natural funnel to get ppl to pay for the more expensive ultra plan other than "trust us the model is good".
If Google had argon broadly available earlier this month they would have picked up a ton of new users.
kranke155 | 4 hours ago
Narrating this as if it’s the game of thrones is a fun exercise, but it’s just becoming commonplace now that models jump ahead of each other on a weekly to Monthly basis.
postalcoder | 4 hours ago
Do you really think people in google are happy about how long it took to release this model?
rebolek | 2 hours ago
nomel | 4 hours ago
This was part of the issue, as stated in their comment. We couldn't jump around to try it for the reason that is wasn't made available to, as you say, "all the power users".
msabalau | 4 hours ago
I mean, I heard rumors too that it would be ultra only, but that doesn't seem to be the case, unless you are specifically talking about antigravity?
Realistically, market adoption isn't going to be the result of terminally online people (like me, I confess) following things way too closely on social.
mrybczyn | 4 hours ago
topspin | 3 hours ago
reportingsjr | 2 hours ago
doodlesdev | 4 hours ago
edit: just a few hours after this comment I got access to Gemini 4 on the Gemini app. Yayy! :)
Ternari | an hour ago
https://blog.google/innovation-and-ai/models-and-research/ge...
doodlesdev | 12 minutes ago
asdfman123 | 4 hours ago
Models move so fast now and Google is very cautious about releasing them.
justinhj | 3 hours ago
varispeed | 3 hours ago
Then basic mistakes (inferring wrong information from the given text, hallucinations...). Gemini is okay for some absolute basics and the rest of the work goes to actual frontier models.
jimjimjim | 2 hours ago
BoorishBears | 3 hours ago
asdfman123 | 2 hours ago
user_7832 | an hour ago
Ofc I know this isn't your fault in person, but I really wish Google would get its shit together.
...As a long time tech enthusiast I should probably stop being so delusional. Heh (cries internally)
1: lol I know who cheers for a trillion dollar company but I'd rather not cheer for OpenAI
vardump | an hour ago
asdfman123 | 52 minutes ago
As a Google employee my defense is it's hard for a company this big to move fast, but I can understand how Google customers would be annoyed.
BoorishBears | 9 minutes ago
The top level comment blamed cheerleading but let's apply critical thinking for a second as product people and look at the funnel:
1. Potential users sees new release 2. Potential user takes time to install and set up Google harness (you already lost 90% of people here, the funnel better close quick!) 3. Potential user cannot use new model.
Then what? You hope they developed good will towards your model through this experience?
You stuck a two week wait in your funnel? Is that the definition of not having your act together or what?
We're on HN, how many of us have heard from Google staff this kind of stuff is a result of them growing so big that AI Cloud has to compete with Vertex Cloud, and AI cloud exists because Vertex Cloud needed 2 years to get OAI/Ant API keys working and they were losing dev mindshare in the meantime?
BoorishBears | 17 minutes ago
vessenes | 2 hours ago
What sucks, hard, is googles ability to deploy direct to devs and customers at scale when the deployment is not a longstanding Google project.
Case in point: I’m an ultra subscriber and see in my app right now an ad to try Gemini 4; meanwhile the only models I have available are 3.1 pro,3.6 flash, and 3.8 thinking.
Clicking the try gemini 4 link takes me to a demo prompt that loads 3.6 flash. Srsly
I won’t even start telling you what getting api key based access together was like a year ago.
iforgotmypasswo | 4 hours ago
We’re all running on Astra medium the whole week and loving it.
I’m curious what I missed.
alex0015 | 3 hours ago
bitexploder | 3 hours ago
iforgotmypasswo | 2 hours ago
$500/month for 40+ hours a week of Astra usage, with ultrafast mode available when you’re near the weekly reset has made our jobs so much easier. Our product has some sciencey bits as well, ands Astra kills it as a rubber duck in this area.
As a consumer whose 20x account got downgraded, I am a bit sad. I can’t justify $500 a month on personal AI spend. As an engineering manager, I could not be happier with OpenAI’s services. Also, Codex App Server is amazing.
discreteevent | an hour ago
Hey, account created 39 days ago. Did you really have to tag that on after all the other stuff? Could you make it any more obvious?
That said this thread is hilarious because it's just an open ai sales manual debating with an anthropic sales manual. It's funny, but it's not, because the truth is that you people are just shitting all over the commons. Someone needs to kick you out but that's not going to happen here.
bitexploder | 59 minutes ago
holoduke | 39 minutes ago
motoboi | 3 hours ago
Can you elaborate on this?
baq | 2 hours ago
simonw | 2 hours ago
Reddit thread with 247 comments here: https://www.reddit.com/r/codex/comments/1wtgv3z/dev_day_l/
Aside from that I'm not sure what was "disastrous" - maybe the lack of a new model release to compete with the just-released Claude Opus 5.5?
AspireOne | an hour ago
- Dots. People don't understand it. Their presentation didn't explain it properly at all. Additionally, many people thought it's stupid, and that the cutesy mascots are dystopian.
- Voice mode didn't work in their presentation. The demo failed.
- 200$ plan goes 20x -> 10x usage. 500$ plan introduced, 25x usage. The contrast is stark.
- "Ultrafast": 8x pricing on subscription plan (6x API). That's 80$ input, 400$ output, 100$ cache write. Hello?! Additionally, since it generates 8x faster, it consumes your quota 8x faster. Per wall-clock minute, it's 64x more usage spend per minute of generating. People report that on the 500$ plan, their weekly usage is gone in 40-100 minutes.
- People believe gpt-6.1-sol was planned to be released as astra-minor, but OpenAI renamed it at the last possible time, because gpt-6-sol is a disaster (this I can get behind)
topspin | 3 hours ago
Oh yeah. Completely forgot about that. Big headlines and big claims, but no one could actually use it and report on it.
Does seem like they don't quite grasp how the hype train operates. Or maybe they don't care as much.
Al-Khwarizmi | an hour ago
polynomial | 5 hours ago
Given FelonyBench, do we also have a FantasyBench?
jstummbillig | 4 hours ago
noooooooo
asdfman123 | 4 hours ago
petesergeant | 4 hours ago
asdfman123 | 3 hours ago
I know it's a matter of personal taste but it reminds me of a grad student that tries to sound smarter than he is by being dismissive and opaque.
glhaynes | 3 hours ago
mkoryak | 2 hours ago
rad-b | 2 hours ago
mattlondon | 2 hours ago
IndySun | an hour ago
Strange. I wonder why? Have you adjusted 'roles', added 'ask clarifying questions'? This is most peculiar.
geertj | an hour ago
> You gave me a long answer but it didn’t answer my question: can we safely remove $X
flockonus | an hour ago
Great model to architect and resolve eng. problems in a harness loop tho. Poor handoff.
bitexploder | 3 hours ago
baq | 2 hours ago
cluckindan | 2 hours ago
bitshiftfaced | 2 hours ago
xd1936 | 2 hours ago
lackoftactics | an hour ago
Em dashes ended up as one of the first victims of llm age
TeMPOraL | 49 minutes ago
In other words, since the very start of computer era, the use of em dashes was always a signal.
TeMPOraL | an hour ago
So obviously, government documents, top publications from liberal arts scholars and STEM > Wikipedia > Reddit (and within, r/AskHistorians > r/all, etc.). The first group is the one most likely to (over)use correct / fancy typography.
I have a related pet theory: the telltale sign of AI writing is being too good for the context it's found in, in terms of vocabulary and style as well as structure.
What is jarring about this is precisely the quality - we associate certain styles with important (or self-important) venues, so it's uncanny to suddenly see random shitposts, copywriting spam, or regular chat replies look like work of NYT bestselling authors or legal scholars - it feels wrong in places we expect basic language, grug-brain reasoning, and lots of typos.
Also, what makes the above much more noticeable, is that AI systems don't have cross-session stylistic memory. From the POV of an LLM, that perfectly fitting, masterfully crafted starter is the first and only time it used it. From the user's POV, it's the tenth time they're seeing it in the span of an hour.
astrange | an hour ago
TeMPOraL | 55 minutes ago
Doesn't change my point anyway - even if post-training, labs naturally want the LLM to come off as smart (well, except for Grok). Post-training is where they "untrained" em-dashes and such, due to complaints of users.
epihelix | 2 hours ago
knollimar | 49 minutes ago
epihelix | 30 minutes ago
I don't ever recall seeing an LLM using them incorrectly, as opposed to simply at high frequency but correctly (although I'm sure some low param or early models must have done so at some point).
dalemhurley | an hour ago
mikestorrent | an hour ago
nostromo | 50 minutes ago
Way too many bullets -> way too many emojis -> way too many em dashes
holoduke | 41 minutes ago
xandrius | 36 minutes ago
pkulak | 2 hours ago
dsco | an hour ago
The results are a bit disappointing given Googles scale and training data.
The results are on par with cheaper Chinese open source models to be frank. https://cliphou.se/benchmark/
andybak | 14 minutes ago
I'm not entirely sure you're correct. Your claim boils down to "Writing natural human prose" vs "Broad use of complex software and spatial awareness". My gut feeling is that there's more untapped and fruitful applications in the second group than the first - at least in the short term.
axblount | 6 hours ago
Is it actually available?
robotmay | 5 hours ago
chpatrick | 5 hours ago
hiq | an hour ago
I'd be curious to see if people have managed to just add custom instructions to make the outputs more standardized and less annoying. I never have such annoying cases, whatever the model, it's just too verbose, but in this case I ask it to be more concise and it's usually fine.
IshKebab | an hour ago
artdigital | an hour ago
Anthropic’s vision of “safe” is so frustrating to deal with, it makes me want to go back to ChatGPT.
alex1138 | 5 hours ago
copperx | 4 hours ago
alex1138 | 3 hours ago
copperx | 3 hours ago
kridsdale1 | 2 hours ago
demibabs | 2 hours ago
dizhn | 3 hours ago
jordemort | 6 hours ago
"Hans, we're doing a new point release! What isn't crossed out on the periodic table yet?"
brainwad | 3 hours ago
GodelNumbering | 6 hours ago
e.g.
The first two prompts I tested in AI Studio does the same, unfortunately.Another quite unpleasant tick was that if you specify a peculiar term in your prompt as a conversational shortcut, it would keep repeating that throughout the conversation. e.g. "...What is a bitter lesson pilled way to do this?", then you'd see it will quote "bitter lesson pilled" at like 7 places in its response. This one seems to have eased off a little.
Corence | 6 hours ago
Insanity | 6 hours ago
"Across Google", wonder how much that is because of an effort by Google to curb usage of Anthropic models. MSFT and Meta similarly are pushing for in-house models. It doesn't mean the models are better when you push your engineers to dogfood and restrict access to other LLMs.
(Not that I know for sure this is the case, it's more of a hypothesis).
melasadra | 5 hours ago
nkg | 4 hours ago
rw2 | 6 hours ago
yoz-y | 6 hours ago
UltraSane | 4 hours ago
DataDaoDe | 6 hours ago
fyi: argon is an interesting choice of name, coming from the Greek argos meaning "lazy or living w/out labor".
aleksiy123 | 6 hours ago
DataDaoDe | 5 hours ago
ralusek | 6 hours ago
I never touch 3.8, it's awful. Curious to try this, but I've yet to use any Gemini that is good for agentic work.
Also, unrelated but this made me look at Artificial Analysis to see where it lands on Cost per Task, and it ranks Opus 5.5 at almost double Astra 6. That does not align with my experience.
bezko | 6 hours ago
Unavailable · Gemini 4 Argon is currently available to Ultra plan subscribers.
staticman2 | 5 hours ago
redox99 | 6 hours ago
theplumber | 5 hours ago
nateb2022 | 5 hours ago
Source? Their documentation says it's available on the $20 plan and I can confirm firsthand.
https://one.google.com/intl/en_us/about/google-ai-plans/
redox99 | 5 hours ago
https://x.com/OfficialLoganK/status/2110038940841545827
upcoming-sesame | 4 hours ago
it needs MCP asap
nateb2022 | 4 hours ago
upcoming-sesame | 3 hours ago
damsta | 6 hours ago
Couldn't you just say what the price will be after the introductory period and when it'll take effect? Do they have some SKILL.md for these blog posts that requires the most important information to always be buried ten levels deep and hidden behind a login page?
nananana9 | 6 hours ago
dyauspitr | 5 hours ago
staticman2 | 5 hours ago
dyauspitr | 5 hours ago
brainwad | 4 hours ago
stymaar | 3 hours ago
It was the case a year ago, but it's less clear cut nowadays, I've seen non-tech people using claude on their phone in the train, and many tech people seem to have switched from Claude Code + Opus to Codex + Sol over the past few month.
vikramkr | 3 hours ago
andriy_koval | 2 hours ago
simonw | 6 hours ago
$2/million input and $10/million output today. $4/$20 after December 1st.
logicchains | 5 hours ago
Is Elon Musk doing their pricing?
square_usual | 5 hours ago
eptcyka | 5 hours ago
LeBit | 5 hours ago
WhereIsTheTruth | 4 hours ago
It is price fixing, nothing else
ac29 | 4 hours ago
simonw | 4 hours ago
girvo | 2 hours ago
It’s still damned capable though, I’ve done a crazy amount of good work with 5.3 Flash.
wasfgwp | 3 hours ago
I think at this point comparing raw token pricing is often apples to oranges.
vikramkr | 3 hours ago
nateb2022 | 5 hours ago
vineyardmike | 5 hours ago
squidbeak | 5 hours ago
gcanyon | 4 hours ago
heaney-555 | 4 hours ago
mlmonkey | 4 hours ago
vikramkr | 3 hours ago
mufufu | 3 hours ago
damsta | 5 hours ago
fancyfredbot | 2 hours ago
It's perhaps a face saving thing to pretend you'll charge the same. Let's see if it actually happens.
jklinger410 | 5 hours ago
mattmaroon | 4 hours ago
mrandish | 4 hours ago
+1. FWIW, I didn't even get far enough to wonder about the price.
The lead (and only) sentence states "Our next era of frontier intelligence, built to solve your hardest problems" a statement equally true of any new Google or competitor model, hence completely devoid of useful meaning. I then kept scrolling down... and down... and down, giving up after a half dozen screens of big images, huge videos and some customer stories. The first sentence of every text block was equally vague or meaningless so... tv;dr (Too vague, didn't read).
Even the Gemini sub-reddit is laughing: https://www.reddit.com/r/GeminiAI/comments/1x2dr47/the_lates...
apatheticonion | 59 minutes ago
It might not be as smart, though my employer gives me access to Claude, so I tried giving the same task to Opus 5.5. Both DS4.1 Flash and Opus5.5 produced nearly identical outputs.
After that, my company switched the entire engineering department to Azure hosted DeepSeek4.1 and costs were cut by 3/4. So far, no one has really noticed the change.
simonw | 6 hours ago
Here's low, medium, high. Even low is better than pelicans from any other lab: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
low cost 10.185 cents, medium was 11.098 cents, high was 17.166 cents.
The costs are similar because it used more output tokens than reasoning tokens for all three pelicans, even for high.
zzulanas | 6 hours ago
simonw | 6 hours ago
32297 | 6 hours ago
hyperparticles | 5 hours ago
anthonyrstevens | 4 hours ago
boo_you | an hour ago
129751 | 6 hours ago
algoth1 | 6 hours ago
HelloMcFly | 6 hours ago
soperj | 6 hours ago
Medium and high are fixies apparently, (or they have a worm gear, although the hub doesn't look big enough for that), since neither has a derailleur. That would also explain the lack of brakes at least.
Low is still obviously failing the "test". It's pedals are not actually attached to the bike either.
Medium has a handlebar that goes through the pelican's beak. So I'd say also failing.
For the high, the only nitpick would be that the bell isn't quite on the handlebars and the stripes on his scarf don't line up correctly.
staticman2 | 5 hours ago
rdtsc | 6 hours ago
> If it's on HN and is a meme at this point, it will end up in the training set.
> It's kind of fun to imagine that there is an intern in every AI company furiously trying to get nice looking svg pelicans on bicycles.
Google listened and assigned a few interns, I guess, for the task
eli | 6 hours ago
PorciiVorbesc | 5 hours ago
gh0stcat | 5 hours ago
PorciiVorbesc | 5 hours ago
Figure of speech.
>Why not just generate svgs with any editing software?
How do you do that from the whiteboard/notebook?
eli | 5 hours ago
PorciiVorbesc | 5 hours ago
TeMPOraL | 3 hours ago
PorciiVorbesc | 2 hours ago
Everyone says that until ms, apple, google, etc introduces this polished feature as part of their tablet imaging editing/document collaboration office suite. Then everyone can;t get enough of it.
> It's a small task whose result is an input to something else - ideal for a tool for LLM (or script)
Have you actually tried this? If it's a small task then why can't LLMs actually do it? Kind of like the pelican test. Every LLM can do a SVG pelican but most of the results are unusable in practice for production/productivity purposes.
Every LLm can extract some half-broken SVG hallucination of your jots, but I'm asking for an app that's polished and works accurately 99% of the time, which means a dedicated app/model tuned specifically for this task, and nobody makes this yet.
TeMPOraL | an hour ago
I don't feel like I'm a representative sample of general userbase, so I won't dispute this too hard. For me, it's rare but it does happen. Still, 90% of my mobile experience is "how is this so broken, why is it missing the obvious follow-up feature that completes a workflow, and why, again, am I not using a laptop for this?".
> If it's a small task then why can't LLMs actually do it?
What if they actually can?
This is exactly what Karpathy was talking about the other day[0]. If your only LLM experience is the default chat app in chat mode, then this doesn't make sense. If your experience includes using agentic harness like Claude Code/Cowork / Codex/ChatGPT Work, then it's obvious.
The LLM app in "chat mode" will just zero-shot you a pelican, or digitize your notes into SVG, and maybe improve on it a bit if you complain about the result. The same app[1] in "agentic mode" will digitize your notes, refine the SVG against the original image, reduce it to probable strokes based on high-frequency patterns in the photo and knowledge of how people write, OCR it, save both the text and SVG to your library, then extract parts you wanted and insert them into a document, typeset the rest of it, and print it on your printer - all in response to a single prompt.
LLMs in agentic mode are very good at stringing long and advanced workflows; today, if you give them shell access or computer use, they will use regular apps for you if that's the easiest way to accomplish the goal.
> Have you actually tried this?
Yes![2].
That's why I can confidently say: there is no limit to this pattern. LLMs can handle apps just fine; giving them tools just saves time and tokens.
Another example: I'm currently resurrecting a 30 year old game, and the other day I asked Claude to hack on a way to run it headlessly, so I can use my computer while it plays with it. It did, and then immediately leveraged it to just causally run several instances of the game in parallel, entirely in the background, whenever it needed to playtest something.
--
[0] - https://news.ycombinator.com/item?id=50047422 - was on the frontpage two days ago.
[1] - Claude and ChatGPT now have both modes in their mobile, web and desktop apps. I personally use Claude Code a lot, but exclusively through these surfaces (I can't be arsed to deal with TUI at home anymore). IMO, these tools are already within reach of regular users - the users just didn't notice it yet.
[2] - Not with SVGs, but equivalent with voice recordings, and yes, Claude Code set up and is managing the whole local processing pipeline. Recordings go in, Markdown (or more advanced signal processing) comes out, and in itself, it's not a task, but merely a step.
xnx | 4 hours ago
matsemann | 4 hours ago
CuriouslyC | 5 hours ago
slyrus | 4 hours ago
sulam | 5 hours ago
afavour | 5 hours ago
compiler-guy | 5 hours ago
DoctorOW | 4 hours ago
gcanyon | 5 hours ago
They look remarkably good, sure -- but not perfect.
orbital-decay | 5 hours ago
nomel | 4 hours ago
orbital-decay | 3 hours ago
pwython | 5 hours ago
> How many pelican riding bicycle SVGs were there before this test existed? What if the training data is being polluted with all these wonky results...
But Simon has demonstrated before that asking for any animal doing something silly will still get similar results from the same model.
simonw | 3 hours ago
thinkingemote | 3 hours ago
simonw | 11 minutes ago
dominotw | 5 hours ago
JoshTriplett | 4 hours ago
ngruhn | 4 hours ago
NoDodgeQuestion | 4 hours ago
rubyn00bie | 4 hours ago
gedy | 3 hours ago
codethief | an hour ago
mlmonkey | 4 hours ago
Expect Google models to be benchmaxxed as much as possible, but don't expect commensurate performance on real-world tasks.
anthonyrstevens | 4 hours ago
This is not true. It is needless negative hyperbole that IMHO doesn't belong on HN.
mlmonkey | 4 hours ago
agar | 3 hours ago
If what you say is true, then the next set of benchmarks will be written to illuminate the true reflection of real-world tasks. Then those get benchmaxxed so managers can show "numbers go up."
Repeat enough times, and you get materially and genuinely improved products.
The burden is on the press, outside researchers, and general tech industry to both write and care about the metrics that matter.
kalcode | 3 hours ago
bilsbie | 6 hours ago
Modern models can make nearly photorealistic games in threejs. So why do they struggle with these pelicans?
simonw | 6 hours ago
The test is always going to be hard though, because it's an absurd image to ask for.
UPDATE: I like this theory about using an agentic harness that can render and iterate better: https://news.ycombinator.com/item?id=50073879#50074395
boo_you | an hour ago
this is a really profound insight
jephs | 5 hours ago
The pretty 3d stuff you see are agents controlling a Blender MCP in a loop where they look at the scene, think, adjust the scene, repeat.
simonw | 5 hours ago
vineyardmike | 5 hours ago
AspireOne | 4 hours ago
agar | 2 hours ago
(As I said in a separate comment above, results are all bikini-clad and not revealing. However, whether it is NSFW is up to you/your work policies.)
epihelix | an hour ago
Perz1val | 5 hours ago
sobiolite | 5 hours ago
TeMPOraL | 5 hours ago
charcircuit | 5 hours ago
duckmysick | 5 hours ago
https://www.gianlucagimini.it/portfolio-item/velocipedia/
HN discussion: https://news.ycombinator.com/item?id=17699017
mason55 | 5 hours ago
https://www.wired.com/2016/04/can-draw-bikes-memory-definite...
ben_w | 3 hours ago
Are you sure they're not fetching free asset packs for that?
agar | 2 hours ago
However, result quality really drops off once you get out of the top 5 or so.
(NSFW note: all buttocks are covered by fairly conservative bikini bottoms and show no genitals, bulges, etc.)
postalcoder | 6 hours ago
kart23 | 6 hours ago
squidbeak | 5 hours ago
huseyinkeles | 5 hours ago
MrAssisted | 2 hours ago
Fraterkes | 5 hours ago
perardi | 5 hours ago
Subtle highlights on the metal frame, sweat beads, jaunty little hat…it has style. At least compared to the rather literal ChatGPT outputs. https://static.simonwillison.net/static/2026/gpt-pelicans-gr...
jameshart | 5 hours ago
Is the prompt context telling the models what their effort level is, and the ambient presence of that concept of ‘high effort’ in the context window is leaking through and affecting the portrayal?
simonw | 5 hours ago
https://huggingface.co/Qwen/Qwen3.8-27B/blob/main/chat_templ...
xhigh: "Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer."
low: "Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration."
LarsDu88 | 5 hours ago
It's a simple manner of prompt...generate concept art with nanobanana, measure, llm creates svg with text, measure the distance between rasterized svg embedding to nanobanana art....do post-training RL on a 3 million such images and matching embeddings.
I swear this will be a canonical example of Goodhardt's Law in action.
You have to switch to a new benchmark that isn't so easy to run a verifiable rewards pipeline on...Perhaps a longer horizon task where it's easy to mess up midway.
jameshart | 5 hours ago
Yes, Simon has made pelicans a benchmark and now models have grown very good at rendering them. Is there a reason to believe that this isn’t manifesting as useful skill in general in SVG generation?
wasfgwp | 2 hours ago
It would perhaps be slightly interesting if the prompt was run 100 times for each model. I doubt the pelicans would look identical.
whoamii | 5 hours ago
mceachen | 5 hours ago
yuhmahp | 5 hours ago
simonw | 5 hours ago
Here's 'Generate an SVG of an armadillo in fishnet tights jaywalking on Mars' for Gemini 4 Argon: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Some other models for comparison: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
make3 | 5 hours ago
dyauspitr | 5 hours ago
gcanyon | 5 hours ago
As one point, the high pelican's arm is see-through/messed up.
They do look worlds better than previously, to be fair.
YZF | 5 hours ago
https://en.wikipedia.org/wiki/Pelican#/media/File:Pelikan_Wa...
ASalazarMX | 5 hours ago
ameliaquining | 5 hours ago
matt123456789 | 4 hours ago
diseasedyak | 4 hours ago
saaaaaam | 3 hours ago
CamperBob2 | 2 hours ago
geniium | 5 hours ago
petra | 4 hours ago
I've noticed that chatgpt is working harder. But still I prefer Claude, it just feels nicer to me.
mroset | 5 hours ago
juleiie | 4 hours ago
Give me reverse engineering bench and agentic coding.
Leave making visuals to humans who actually have aesthetic sense unlike whatever made this mess
ionwake | 2 hours ago
gordon_freeman | 4 hours ago
tyre | 4 hours ago
philipwhiuk | 4 hours ago
bigcat12345678 | 4 hours ago
mt_ | 4 hours ago
travbrack | 4 hours ago
tintor | 4 hours ago
epihelix | an hour ago
However, how the front fork rake affect stability is I believe a little complex. I doubt this old article is the last word on the subject, but it's a great read nonetheless, and note especially the ultra-stability of the reversed fork bike!
https://physicstoday.aip.org/features/from-the-archives-the-...
rich_sasha | 4 hours ago
I note that even these bikes are not actually rideable. For a bike to be stable, the front wheel axle needs to extend forward a little ahead of the fork - the fork must ”bend forwards”. This is what actually keeps the bike upright, not gyroscopic effects or some such. Given LLMs are generally good at basic maths, im surprised they get this wrong.
Maybe a bit less so in this case though. As per the announcements, the model was actually trained for this prompt, so was fed some training data. I can well imagine the data there was just not so good.
jonas21 | 4 hours ago
https://www.walmart.com/ip/Huffy-26-inch-Rock-Creek-Men-s-Mo...
(apologies if I'm misunderstanding).
sokka_h2otribe | 4 hours ago
jonas21 | 4 hours ago
IsTom | 3 hours ago
matsemann | 4 hours ago
People drawing bikes, scroll down to see they having made renders of all the drawings. Hilarious
saberience | 4 hours ago
You're nit-picking on a detail no one actually cares about.
kevmo314 | 4 hours ago
You can also ride a negative rake fork. They are less stable, yes, but a far cry from not actually rideable, cf https://www.instagram.com/yourforkisonbackwards/
Enginerrrd | 3 hours ago
Bedon292 | 3 hours ago
I'll also note that, using a piece of paper as a straight edge against my screen, there is a very slight forward curve on the low and a bit more on the high responses. Medium does appear to be perfectly straight.
NooneAtAll3 | 4 hours ago
wasn't the whole point of pelicans is that labs *wouldn't* train for that?
so now the benchmark is ruined
motoboi | 4 hours ago
Also, that first tweet contains a commentary that, for me, explain a lot about the public misconception about how current AI works:
> wait, does this mean you guys are actively training svg generation? i was mostly amazed by it thinking the models doing better at it by itself due to becoming better at reasoning.
No, it's not better reasoning that drives current AI, it's better examples we have been giving them. Whole army of people generating content for the frontier labs.
Also, reasoning improving the out of distribution part, like computer use, tool use etc.
TeMPOraL | 3 hours ago
Another case where allowing oneself to anthropomorphise LLMs a little yields better intuitions.
People don't get more skilled by raw reasoning, either. They improve their skills with better textbooks (pre-training data), more practice exercises (RL data), and generally goofing around (self-play).
boutell | 4 hours ago
w29UiIm2Xz | 3 hours ago
KeplerBoy | 3 hours ago
kmod | 3 hours ago
<https://tools.simonwillison.net/svg-render#%3Csvg%20font-fam...> <https://tools.simonwillison.net/svg-render#%3Csvg%20font-fam...>
- I was having trouble embedding the SVGs as links, and ChatGPT recommended Simon Willison's SVG Renderer as a workaround.
Just my 2 cents on the pelicans benchmark: I think it might help if you were a bit more explicit about not taking this one benchmark too seriously. I know you say that at times, but at other times (such as the comment I'm replying to) you elide it which can read as a seriousness about the benchmark.
thefourthchime | 3 hours ago
Argon: https://jonclegg.github.io/pacman-bakeoff/dev/#gemini-4-argo...
Opus 5.5 https://jonclegg.github.io/pacman-bakeoff/dev/#claude-opus-5...
vessenes | 2 hours ago
osiris970 | 6 hours ago
What’s the point lol. I’m not subbing to ultra to have it
rcr-anti | 6 hours ago
Edit: noble gases not noble taxes, though the latter would be a funnier naming scheme.
mistic92 | 6 hours ago
robotmay | 5 hours ago
skerit | 5 hours ago
robotmay | 5 hours ago
metalliqaz | 3 hours ago
olafura | 2 hours ago
Which is even weirder given that the api costs are less than for the other providers
Maybe they don't really care about antigravity users. Also, monitoring usage is horrible.
Trusteando | 6 hours ago
yoz-y | 6 hours ago
freakynit | 6 hours ago
This is crazy if it can work accurately.
ArashEdalat | 5 hours ago
verdverm | 5 hours ago
kridsdale1 | 2 hours ago
34679 | 2 hours ago
129751 | 6 hours ago
Even after using the free model in Google search talking to Anthropic or OpenAI models feels like talking to an ox.
david-gpu | 6 hours ago
Havoc | 6 hours ago
God knows why the server different things to the same people on different interfaces
pietz | 6 hours ago
swaptr | 5 hours ago
sureglymop | 6 hours ago
Pretty misleading.
ezfe | 6 hours ago
verdverm | 5 hours ago
peheje | 4 hours ago
verdverm | 3 hours ago
tireonfire | 6 hours ago
protoman3000 | 6 hours ago
The code is bad though.
jug | 5 hours ago
TomGarden | 5 hours ago
gradus_ad | 5 hours ago
mavamaarten | 4 hours ago
copperx | 4 hours ago
bahmboo | 4 hours ago
yipinwong | 3 hours ago
Or else it say, here is the result. (but no it didn't do no research, and tells me, sorry I forgot to search).
It's got balls to lie straight at my face.
SwellJoe | 3 hours ago
They all ramble, they're all allergic to getting to the point. But, Gemini historically has pretty good prose. Even the self-hosted Gemma models have pretty nice, inoffensive prose. I wouldn't want to read a novel written by any of them, but I tend to ask Gemini questions in chat more often than Claude or GPT, because it has good prose and is good at using the web to research.
thisisauserid | 6 hours ago
meerita | 5 hours ago
ainch | 5 hours ago
nateb2022 | 5 hours ago
d2kx | 5 hours ago
babelfish | 5 hours ago
d2kx | 5 hours ago
mattmanser | 5 hours ago
Eyes glazed over again.
Did you even read your own site before you posted it?
One of the first pages I opened:
> Smoking-gun proof of plant-label ingestion: in Row 2, the central cut root is labeled okol (f88r.15), and directly underneath it on Line 2 (f88r.19) the recipe writes...chokol daiin qoekol qoekol qockhol okol cheol...!
It's just gibberish.
case540 | 5 hours ago
HenryMulligan | 4 hours ago
swingboy | 18 minutes ago
shawabawa3 | 4 hours ago
It looks like you've managed to decode it? Is that legit?
yipinwong | 3 hours ago
What kind of progress was made with Argon with the Voynich?
jdthedisciple | 3 hours ago
kzrdude | an hour ago
But id the progress of decoding it is legit, you should write something properly about it!
scotty79 | 5 hours ago
simonw | 5 hours ago
But on December 1st Argon doubles in price - so it will be the same price as Opus 5.5.
mdasen | 4 hours ago
Likewise, you look at Artificial Analysis' general index and it cost $8,708 to run with Opus and $2,407 to run with Argon so even if Argon's token price doubles, it won't be the same price as Opus.
Sonnet is cheaper than Opus per-token, but in their coding tests Sonnet burns through enough tokens that it's 7.5% more expensive.
So much depends on how token efficient something is and whether it gets you a good result or not, right?
Plus, if one is using a plan instead of paying token rates, what does my $200 get me from OpenAI, Anthropic, or Google?
It just feels very hard to compare pricing given that the number of tokens used can vary so much. In Artificial Analysis' coding tests, Sonnet used 7.1x more tokens than Sol. Sonnet and Sol might have the same per-token pricing, but there's a huge difference in the number of tokens used.
simonw | 4 hours ago
This was hardly a consideration a year ago, when many model tasks could be tested using a single prompt and it was hard to spend more than a dollar.
isityettime | 5 hours ago
Me: Gemini, navigate to nearest McDonalds.
Gemini: [Lists 10 McDonalds locations wnd asks which I want.]
Me: What were the priginal instructions just now?
Gemini: [Recites imperatives about tone and content from its memory system.]
Me: No. I told you to navigate to the NEAREST McDonalds. There's only one NEAREST McDonalds. Do that one.
Gemini: My mistake, navigating to the nearest McDonalds. [Opens Maps, navigating to a McDonalds across town.]
didibus | 5 hours ago
kingstnap | 5 hours ago
Flash lite is very noticeably more idiotic than 3.8 Flash. It's why the quick AI overview is often much worse than the AI mode one.
elxr | 4 hours ago
I also have had shockingly bad results with gemini on android. Ended up giving up on it after a few months. Silly silly google with their trademark UX polish and attention to usability.
Capricorn2481 | 3 hours ago
isityettime | 2 hours ago
Capricorn2481 | an hour ago
moffkalast | 5 hours ago
jabroni_salad | 4 hours ago
jeffbee | 5 hours ago
dyauspitr | 5 hours ago
compiler-guy | 5 hours ago
The only thing I can figure is that Google's consumer-facing free-to-use models are set to "reason as fast as possible with only the most basic plausibility checks." I have to correct them like this every single time.
sm-silversight | 4 hours ago
bornfreddy | 3 hours ago
compiler-guy | 3 hours ago
isityettime | an hour ago
Similarly, you can run local LLMs on your Google Pixel smartphone, but if you want them to be hardware accelerated using the chip that's included for that very purpose on your phone... it has to be Google's models via Google's apps. So you can't say "alright, a fast, local model which sounds great, but I want one that is trained to always run a search before answering, in a harness with good search tools for answering the kinds of practical questions I often ask", you're actually not free to put that together in a practicable way.
So there is indeed some competition here. But it's not really fair competition.
staticman2 | 5 hours ago
isityettime | an hour ago
LewisOrton | 5 hours ago
LewisOrton | 4 hours ago
i benchmarked 20+ models in real worlds and gemini families are the best (highest customer satisfaction)
foota | 5 hours ago
polynomial | 5 hours ago
ASalazarMX | 5 hours ago
gorbot | 5 hours ago
I think these companies have good models but expose them poorly like others have mentioned
RajuChacha108 | 5 hours ago
I tell it to "Play Let it go from frozen". It plays it on youtube music. 5 seconds later I tell it again 'Play let it go from frozen" it then just dies saying "I can't play videos in car".
dgunay | 3 hours ago
1. I ask it to list out all my old Keep notes that are just throwaway task lists, reminders, etc. to propose deleting them.
2. It comes up with like 4 of them (I know for a fact there are dozens, if not hundreds). I ask it for an exhaustive list.
3. I see its thinking trace briefly show "Refusing to produce an exhaustive list..." and then it says "Yes, that is all of them."
Not sure whether it's lack of intelligence, bad tools, or both, but that was extremely frustrating to see.
sva_ | 3 hours ago
If it had exact location access people would be crying that Gemini steals their location data.
eluusive | 5 hours ago
I have found that Gemini often claims it did something, but didn't actually complete the task.
I just had 3.8 Flash do a major refactor -- that never should have needed to be done in the first place -- and switched to Argon 4, and had it review it.
Almost everything had been stubbed out by 3.8, and none of it was properly integrated into the codebase. :facepalm:
bushbaba | 5 hours ago
copperx | 4 hours ago
karahime | 5 hours ago
anonova | 3 hours ago
staticman2 | 3 hours ago
jdw64 | 5 hours ago
robotmay | 5 hours ago
dmix | 5 hours ago
Every time I try to generate one it's like a slot machine, where a different part will be messed up after fixing the first.
TomGarden | 5 hours ago
ramoz | 5 hours ago
DrProtic | 5 hours ago
I told it to strip screenshots from our old basic explainer video to generate modern 3D video.
Pretty happy with the result. I told it to keep the audio and match the video and it did.
dmix | 4 hours ago
I previously tried with Seedance 2.5, Flux 3, Kling 3, Gemini Omni without much luck.
ChrisClark | an hour ago
jjcm | 5 hours ago
Argon build: https://html.non.io/lcars-argon/
GPT 6.1 sol: https://html.non.io/lcars-gpt-6.1-sol/
Opus 5.5 (currently SOTA for this): https://html.non.io/lcars-opus-5.5/
Original designs: https://diffui.ai/app/canvas/5093e689-1e74-4f26-b632-2a4500f...
jjcm | 5 hours ago
jadbox | 4 hours ago
sergiotapia | 5 hours ago
jjcm | 5 hours ago
capnjngl | 5 hours ago
bobviolier | 5 hours ago
(Chrome, also incognito)
MaxikCZ | 5 hours ago
jjcm | 5 hours ago
FWIW, I have literally the exact same configuration (M3 air, google chrome). Here's a recording on mine where I'm seeing 60fps: https://non.io/video/video-3587018401.mp4
Gallows4574 | 3 hours ago
Edit: The argon built site pins 1.3 cpu cores. The Sol 6.1 site uses 0.18 cores.
dr_kiszonka | 3 hours ago
hedgehog | 5 hours ago
piperswe | 3 hours ago
niek_pas | 4 hours ago
wireless6948 | 4 hours ago
daemonologist | 3 hours ago
jjcm | 2 hours ago
As soon as gpu acceleration is disabled, the webpage goes from 60fps across the three systems I tried to ~7-20fps when software rendering is forced.
I suspect if you go to chrome://gpu you'll find something different from what I have here: https://image.non.io/a47a1b03-1b87-4fd5-92a2-b39e62b1cfd9.we...
bobviolier | 2 hours ago
So that all being said, a normal website should work totally fine on low power mode, and this should definitely be a negative on the Opus implementation.
jjcm | an hour ago
I would disagree with this based on two things:
1. the prompt, which explicitly states to render the planets in the background in 3js (thus the gpu implementation).
2. the purpose of this, which is a test of its ability to convert an image design into a html/js/css implementation that matches it as closely as possible. I've talked about this before when it's come up[†]. The purpose is to be a good test, not a good design or website.
For reference, here's the full prompt used:
> Create a web page implementation from the following instructions: https://diffui.ai/build/Futuristic_Interior_UI_build.md?auth... dont reference any other folders that have similar builds. Focus on the flowing SVGs. Animate elements that make sense to be animated. For the starships that have planets in the background, ask for high quality images with the windows as a transparent background, and recreate the planets behind them in 3js. It should be one single page application that I can just open the index.html file to view.
[†] https://news.ycombinator.com/item?id=49997135
[‡] here's a copy of this since the diffui build instructions wont be accessible without an account: https://non.io/lcars-build-instructions
awkwardpotato | 4 hours ago
jjcm | 4 hours ago
Here's a vid of both opus and argon side by side, which might be more viewable on mobile: https://x.com/pwnies/status/2110058987462988152
jdthedisciple | 3 hours ago
demibabs | 2 hours ago
vessenes | 2 hours ago
lxgr | 5 hours ago
Gemini Live vs. Gemini Lite vs. Gemini Pro vs. Gemini Flash vs. Nano Banana Lite (that one apparently has no Gemini prefix?)... Please, just pick a metaphor and stick with it without wildly mixing reasoning modes, model sizes, and input/output modalities in the model name!
tonyhart7 | 5 hours ago
jawiggins | 5 hours ago
I wonder if any of the AI safety people will begin encouraging AI researchers to swap jobs to work at a failing lab in order to keep them all extremely competitive with one another.
FinnLobsien | 5 hours ago
At this point a lot of stuff happens at the product level.
OpenAI and anthropic have distribution and data advantages now that are hard to replicate.
jawiggins | 5 hours ago
derwiki | 5 hours ago
jawiggins | 5 hours ago
Trusteando | 5 hours ago
dyauspitr | 5 hours ago
mridulmalpani | 5 hours ago
https://arena.ai/leaderboard/agent/chat/pareto
For almost same intelligence (+15.56%, +15.18%), drastic difference in cost/task ($3.51 vs $0.41)
BrokenCogs | 4 hours ago
yipinwong | 3 hours ago
abeppu | 3 hours ago
kridsdale1 | 2 hours ago
ianm218 | 3 hours ago
jonas21 | an hour ago
seizethecheese | 16 minutes ago
vessenes | 2 hours ago
cheema33 | 2 hours ago
For chat, yes. But switch to code on the same page, and the picture changes. OpenAI takes the lead.
cwoolfe | 5 hours ago
npn | 5 hours ago
It still thinks Charlie Kirk is alive, though.
peter_d_sherman | 5 hours ago
Now that needed to be done for some time!
Regardless of if an AI helped or not, regardless of whether that was Google's or some other AI or not (though Argon does sound pretty cool!), regardless of whether an AI cut the time from months to weeks or not, refactoring Chrome -- decomposing it into individual clearly demarcated non-tightly coupled software parts with core webpage handling at the center -- that needed to be done for some time!
Now all of that being said, Gemini 4 Argon does sound pretty cool, and we congratulate both teams at Google -- the team that created Gemini 4 Argon, and the team that refactored Chrome with it!
But all of that being said, while the advancements made for Gemini 4 Argon are important and impressive (and they are!)... refactoring Chrome properly (IMHO) is slightly more important and impressive!
(You know, one man's humble opinion! That is, I am not the guy who is responsible for awarding performance-based bonuses at Google at the end of the year, so take everything I say with the proverbial "grain of salt"! :-) I am probably biased, one way or the other! :-) )
efficax | 5 hours ago
mchusma | 5 hours ago
ketzu | 5 hours ago
Okay, so I'll get Pro to try it.
I subscribe.
No gemini 4.
The most generous reading I have is that it's a mistake. But I also downloaded the PC app, and now I really wonder why I did that, it seems to offer nothing beyond the web experience and also doesn't even know its a local app. (When asked about its capabilities it always responded with reasons pertaining to it being a web app.)
llm_nerd | 2 hours ago
EDIT: Okay, the AI plans page claims under pro - "Expanded access to Gemini 4 Argon in Google Antigravity." So maybe it is just a matter of it rolling out. Though Google has a long history of serious confusing and misinformation on those tier descriptions.
EDIT2: And they changed it again, and now it is explicitly excluded from antigravity for Pro users.
dcchambers | 5 hours ago
Google...why. You keep getting so close but constantly fumble at the last moment. I can use Opus 5.5 and Sol/Astra on the $20 Anthropic and OpenAI plans.
You are already playing from behind. You need to GET YOUR MODELS INTO MORE PEOPLES HANDS by any means possible. Continuing to make it difficult to use your products DOES NOT HELP.
This model might be great but the majority aren't going to subscribe for $100/month just to try it.
WaltPurvis | 2 hours ago
dcchambers | an hour ago
Kuyawa | 5 hours ago
Which one is it?
brainwad | 4 hours ago
Zigurd | 4 hours ago
a11r | 4 hours ago
sidibe | 4 hours ago
mattmaroon | 4 hours ago
bitexploder | 2 hours ago
bionhoward | 4 hours ago
It feels so complicated and hard to know what we can use vs what hands them our codebases
SXX | 4 hours ago
Start preparing Gemma 5 release.
Macuyiko | 4 hours ago
eyalitki | 4 hours ago
arjie | 4 hours ago
amai | 4 hours ago
dandaka | 4 hours ago
deniska | 3 hours ago
karp773 | 3 hours ago
l0kihardt | 3 hours ago
grim_io | 2 hours ago
Related funny https://www.youtube.com/watch?v=DlTNN0gvkLM
Andrex | 26 minutes ago
?
I_am_tiberius | 4 hours ago
the_real_cher | 4 hours ago
Lucasoato | 3 hours ago
_s_a_m_ | 4 hours ago
They had gemini cli, what happened to that? Was fine
InsideOutSanta | 3 hours ago
AspireOne | 37 minutes ago
Lucasoato | 3 hours ago
Is there anybody in Google having a look at how bad and complicated their payment system is? In all the other AI providers you just sign in, pay, get a key, done. In other clouds like AWS, you add a card, pay little to verify the card the first time, monthly bill, done. In Google it looks like you have to fight them every time for the very thing they should make as easy as possible: opening your wallet.
dynm | 3 hours ago
CamperBob2 | 3 hours ago
rdtsc | 2 hours ago
deno | 3 hours ago
I would also advise against buying Gemini if you have any other Google services, because you get banned across board if they don't like something. To use Google it's best to first migrate off of Google.
Otherwise great product, I really like and would recommend Gemini. The usage is also very generous, at least Flash models.
serbuvlad | 2 hours ago
I recently had to verify my YouTube account with a phone number recently because it requires this in order to set a thumbnail.
Questions right off the bat:
1. Why do I need to verify to post a thumbnail that will take 1MB on their servers but not to post a video that will take 100MB on their servers and be public??
2. Why do I need to verify my phone number on YouTube when it's linked to my Google account which has a verified phone number and 2FA etc.?
In any case, it takes you to a CSS-less page that asks you to choose between getting an SMS or being called to get a code. I choose SMS and it doesn't work. It shows an error message with no description just "something went wrong". I try a few times and it keeps not working.
I then switch to the call, and guess what! I have tried "too many times" and will have to try again later. Call worked the next day, but geez, what a mess.
singingtoday | 3 hours ago
algoth1 | 3 hours ago
guybedo | 2 hours ago
i live in French Polynesia, a French territory, i'm a Google AI subscriber and i can't use Google AI Studio or antigravity cli because i'm in a geo restricted area ...
It seems Google has no issue laying out cables across the Pacific Ocean from/to Tahiti, they don't have an issue selling their services and plans there but i can't use AI Studio or antigravity cli because of geo restrictions ...
bluerooibos | 2 hours ago
- Try in Gemini
- Try in Google AI Studio
- Try in Google Antigravity
Will non users of Google products even know what these three things even are?
34679 | 2 hours ago
I have AI Pro, but AI Studio tells me I can "unlock" Argon by upgrading to Ultra.
vessenes | 2 hours ago
IanCal | 44 minutes ago
Classic Google.
malshe | 2 hours ago
irthomasthomas | 2 hours ago
ssernikk | an hour ago
DriverDaily | 2 hours ago
kccqzy | 2 hours ago
What you did isn’t wrong, but is unfortunately very similar to what real scammers do. The heuristics behind these anti-abuse efforts are always going to have false positives.
Xenoamorphous | 2 hours ago
codethief | an hour ago
For the lazy:
https://www.osnews.com/story/19921/Full-Text-an-Epic-Bill-Ga...
throwaway919233 | 2 hours ago
kristofferR | an hour ago
Ended up with Soniox instead, took minutes to get started.
0xbadcafebee | an hour ago
mrshadowgoose | an hour ago
They made using it so hard/unclear that myself and every other dev I knew gave up.
It's clear that they still haven't done any organizational self-reflection.
gpugreg | an hour ago
fsflover | an hour ago
randerson | an hour ago
They now ask for your mobile number during signup. And it wouldn't let me register any more accounts with my number. So frustrating.
mfkp | 31 minutes ago
"Unavailable · Gemini 4 Argon is currently available to Ultra plan subscribers."
talon8635 | 30 minutes ago
That said, asking Gemini.google.com to walk you through the steps seems to suffice. In fact, one of AIs big perks for me is walking my through kafkaesque systems like Google’s to cut the shit and get to the result
rumblefrog | 25 minutes ago
halyconWays | 4 hours ago
fraywing | 4 hours ago
tintor | 4 hours ago
XCSme | 4 hours ago
minraws | 3 hours ago
joejohnson | 3 hours ago
hollowturtle | 3 hours ago
On safari the page doesn't scroll very well on the first section
dhruvrrp | 3 hours ago
What about the Google One AI plans? Will they get it? That has a Pro AI plan as well.
kylecazar | 3 hours ago
fusslo | 3 hours ago
is it just 'Hire the right people'?
jacquesm | 3 hours ago
IncreasePosts | 3 hours ago
Perhaps one of their more successful chat clients, but that's all I can think of
jacquesm | 3 hours ago
The really annoying ones are the ones they buy, and then shutter because they can't make enough money on them fast enough.
serioussecurity | 3 hours ago
It's extremely inconsistent internally as well.
Look up the slime mold analogy for Google.
boelboel | 3 hours ago
Eridrus | 3 hours ago
Google did a very good job on things that required longer research times and compute scale, note that Transformers, BERT & Scaling Laws came out of Google (though the latter were also worked on at OpenAI).
Conversely, Google is horrible at product, and without OpenAI, it probably would have taken many years longer to take off. I know this because Google had demos of this internally, but absolutely no stomach to release it, and they didn't believe in the API use case at all.
Which is to say, I think if Google was smaller, we probably would have gotten more SaaS, not more breakthrough research.
ceejayoz | 3 hours ago
What if the answer is "they don't"?
arjie | 3 hours ago
estearum | 3 hours ago
Eridrus | 3 hours ago
It's also worth noting, Gemini 3.5 Pro never came out.
Having worked there (but only in a small part of it that eventually got absorbed into Gemini), it's some combination of:
* The eye of Sauron (management) can make specific spots (e.g. Gemini) push harder (and attract the motivated people at the company and be selective)
* They hire a lot better than average (Generally from the top 10%, hotter places in Google are more selective)
* They have a promo process that gives career motivated people a way to prove themselves (not always aligned with things being on the right track ofc, and not always non-political, but they definitely do something)
* Redundancy in teams causes them to compete (not necessarily productively)
Of course, there are other downsides not listed here (insane bureaucracy for launches, GDPR/BCID compliance, etc, etc), but a lot of what makes Google possible is the insane amounts of cash Search throws off.
hmokiguess | 3 hours ago
astlouis44 | 3 hours ago
https://playblueline.pages.dev/
BrokenCogs | 3 hours ago
sva_ | 3 hours ago
ariwilson | 3 hours ago
It thinks a ton, ~24k output tokens a run vs ~3k for Sonnet. It missed a solution by thinking its way into a 10 min timeoout.
Something to look out for - if you're using pi, it doesn't have Argon in its catalog yet and reports cost at Kimi's rates, about a third of what OpenRouter actually bills.
iharnoor | 3 hours ago
FranciscoCarlos | 2 hours ago
As of my knowledge cutoff, three of the top state-of-the-art large language models are Google's Gemini 2.5 Pro, OpenAI's o3 (and GPT-4.5), and Anthropic's Claude 3.7 Sonnet.
arbuge | 2 hours ago
FranciscoCarlos | 2 hours ago
jeffrallen | 2 hours ago
akbarian | 2 hours ago
svara | 2 hours ago
This is a clear step change, I'm genuinely amazed.
Its answers are to-the-point, logically structured, clearly written. Like a really well made mini essay on your question.
It also really likes to build little simulations / models that you can tweak the parameters on. Amazing to explore how different assumptions affect economic scenarios, for example.
It's also great at picking (sourced) illustrations.
I'll be using this for everything that isn't coding from now on.
A_D_E_P_T | 2 hours ago
halJordan | 2 hours ago
holaysuns | 2 hours ago
glouwbug | an hour ago
WillPostForFood | 44 minutes ago
taneq | 38 minutes ago
becquerel | 15 minutes ago
HSO | an hour ago
why? is it not so good on that? or is there something better performance, or better price for same performance?
A_D_E_P_T | 58 minutes ago
That said, I'm extremely impressed with Argon thus far. I take back everything bad I've ever said about their AI strategy. Argon is very good and very fast. It might be competitive at coding, but it's too early to say.
VirusNewbie | 53 minutes ago
jwpapi | 26 minutes ago
drob518 | 10 minutes ago
georyb | 2 hours ago
dom96 | 2 hours ago
Language info: https://killswitch-lang.org/
scirob | 2 hours ago
https://dach.peerbench.ai/compare?models=google%2Fgemini-4-a...
dmd | 2 hours ago
moecables | 2 hours ago
simedw | 2 hours ago
Gemini 3 Flash was around 0.403, 2.5 Pro was around 0.34.
ehsankia | 2 hours ago
RedCardRef | an hour ago
From what I saw online.
azan_ | 2 hours ago
iamheretowin | 2 hours ago
build this scene space station docking scene https://x.com/_satyam_ai/status/2110097633922662752?s=20
manlymuppet | 2 hours ago
- Natively multi-modality
- Enormous context windows
- Reliably cheap prices
It's like they don't release a model until it passes the above checklist.
Most providers have some mixture of these three occasionally, but with Google, every model is consistent. This kind of consistency is really nice to have.
imagetic | 2 hours ago
risphai | an hour ago
parallax_error | an hour ago
vinni2 | an hour ago
martythemaniak | an hour ago
pamir35 | an hour ago
pamir35 | an hour ago
tezza | an hour ago
Very fast.
Makes mistakes. Corrects the mistakes quickly with direction.
Google Argon 4: https://share.gemini.google/T9r6tr2dDaTE
I didn't have time to make it into a full blog post yet. Here is a previous one.
https://generative-ai.review/2026/07/kimi-k3-rush-test-vs-cl...
tezza | 42 minutes ago
Astra 5.6 is significantly better than Google Argon 4 and a lot better than Claude Fable
https://generative-ai.review/2026/10/catchup-openai-astra-5-...
le-mark | an hour ago
oblio | an hour ago
catfood | 59 minutes ago
ssernikk | 53 minutes ago
aetherspawn | 33 minutes ago
OpenAI release any time now
vidarh | 30 minutes ago
If they don't want to make it available even for small tests for free, that's fine, but then don't put a button suggesting I can try it without qualifying it...
EDIT: It's actually worse: The page then shows "Look what you can do with Gemini 4" and a "Let's go" button that leads to a bunch of links to examples, all with enticing pictures. Except if I click on them I get a box stat strongly suggests it'll run with Gemini 4, except the dropdown shows "Flash" and if you click on it, it shows as Gemini 3.6 again, and if you run it, the results unsurprisingly end up looking nothing like their pictures.
I don't know if that page was built by humans or AI, but clearly nobody tested it properly.
fudged71 | 13 minutes ago
alexmr | 17 minutes ago