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
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 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.
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.
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/videos as a proxy for model capability.
I reckon most people have stopped caring about the quality of well written things, and that's always been the hallmark of google models.
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, and a distinct writing style.
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. Hype died down and Muse came out with a similarly capable model.
In the meanwhile, OpenAI had a disastrous dev day where a ton of users jumped ship to go to Claude. If Google had argon 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".
I mean, I heard rumors too that it would be ultra only, but that doesn't seem to be the case.
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.
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 think google makes great models, my favorite models have been google models. My critisisms are with the infrastructure around the models (or lack of them),things like billing, access, changes to terms and limits, pricing etc. All of these have shown either inconsistency, lack of care, sometimes confusing offerings, and things that felt like rug pulls.
Please google, just make it easy for me to give you money and get what I paid for.
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.
: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.
This product has made my life substantially easier. I have no affiliation with OpenAI.
Claude refuses to help you build your own harness off a subscription, and OpenAI actively encourages it with Codex App Server. So you’re just in an AI IDE customized to your job and specific needs ALL THE TIME. You know that good feeling you got when your CI pipeline was finally working, back when that involved speed reading documentation and guessing, or staying at work until 10PM? You just get that all the time because life is constantly improving. And your tools are beautiful and riddled with Easter eggs you put in them. There’s so much more time to test and talk to stakeholders because you are able to distribute the thing you are actually good at -solving people’s difficult problems- while following best practices. You used to have to weigh those two every day and it was terrible. And everything was always late. You had to cut so many corners you were delivering circles.
Now life is fun and I’m over-delivering. Constantly. With super high code quality, better test coverage, easier audit prep, and I just explain what I want (technically) at a high level to AI. I still have to code review, and it sucks. Not because the AI needs it, but because auditors need it. I think I can make it faster and easier in the near future with another custom tool.
I actually have time to make architecture diagrams. I have never had enough time to build that level of documentation.
With Fable, I felt the promise of this coming. With Astra, I feel like we finally had the resources to fully professionalize and supply our software team.
We actually need to hire more people next quarter.
I am with the creator of Rails on this. It is a time of joy. Now is the time to become more ambitious.
I'm a bit confused by this comment. I thought Enterprise customers didn't have access to fixed price plans like the $500/month personal tier and instead paid per token? If that's available to businesses, Astra seems like a no-brainer. But at least the regular Business plans only show me the $25 and $125/month options and the latter is a very recent addition.
They are all very slow at the moment. Some tasks are taking hours to even days. These are DevOps related tasks in which I create hundreds of servers in an agentic way. It works. But it's slow. That's still annoying.
Pulled astra 6.1 at the last moment (allegedly) and only released a dirty looper sol 6.1. Also released dots which are unavailable in EU. There may have been more but no one cared.
"Disastrous" is obviously a loaded term, and it can be debated, but from what I collect, the reasons are
- Dots. People don't understand it. Their presentation didn't explain it properly at all. Additionally, many people thought it's stupid, and that the cutesy mascots are dystopian.
- Voice mode didn't work in their presentation. The demo failed.
- 200$ 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 went from using GPT exclusively to cancelling all my subscriptions with OpenAI.
'backlash' is underwhelming. They single handedly murdered 5.3 codex which was great by making it slooow and duuumb, and pushed people over to their new ones. 5.6 was a decent candidate but it was so slooooow.
And then double or triple the cost for Plus and Pro by nerfing their effective power? I never looked for an alternative faster. They really screwed the pooch.
Been quite happy with deepseek v4.1 flash, muse 1.3 and haiku 5.5.
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.
Interesting. My favorite LLM output ever was the reasoning traces in gemini 2.5 pro. I found them much easier to understand than the "final output", because they were very structured and concise. Of course, they ended up hiding the reasoning, not long after that, like everyone else... sad!
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.
Like many other LLM tropes they were heavily overused which attracted attention. Normal English writing doesn't average 1 em dash per 2-3 sentences like I would frequently see during Peak Em Dash.
They aren't a complete rarity by any means but still relatively uncommon compared to the typical punctuation one sees in routine usage.
I loved em dashes back in high school and my English teacher would have definitely returned an assignment with a lot of red marks if I used em dashes as frequently as an LLM (speaking from experience).
See, the problem is when em-dashes are used like you just did, they are fine and even expected. But LLMs use them differently. Here is a fresh example, from today:
"Binds the downstream RF port template—which we configured earlier—to this RPD profile, applying all global DS settings and channel structures to the node's downstream hardware."
Do you see the problem in comparison? The LLM text is assuredly not how humans write. Well, maybe you would find similar examples in the classic literature, but definitely not in a common internet texting or simple articles and posts.
> 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.
can confirm this. I didn't have high expectations for AI writing good long-form content in Indonesian. However, I recently tested it on some of my Indonesian writings and asked Argo to rewrite them while maintaining the original tone—and it absolutely nailed it.
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".
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".
the etymology can be broken down even more, its the prefix a - meaning without, opposite, no. and ergon, meaning work, visible in words like ergonomics, or the ergosphere
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.
> 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?
> 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).
Modern tech marketing is a clown car of incompetence.
I mean its also been generated by a bunch of PM that want to get promoted but have little idea of what they're talking about..however nobody has been fired YET for using too much vague AI words.
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.
I'm surprised no one's complaining about it randomly switching to mandarin. It seems like no matter what I do once every few days it'll go back to mandarin mid thinking trace and then stays in mandarin until I remind it to use English.
775 comments
[ 1.7 ms ] story [ 112 ms ] threadThe 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
Like a working scroll on a webpage.
God damn this is impossible to use of safari mobile.
Argon is trying to solve the "hard" problems like those.
This is in the Gemini app on macOS.
EDIT:
Apparently Ultra subscribers gets Argon everywhere including in Google Antigravity
Pro subscribers only get them in Gemini app and Search
https://antigravity.google/blog/gemini-4-argon-in-google-ant...
> Gemini 4 Argon is available today for Google AI Pro and Ultra subscribers
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.
https://one.google.com/about/google-ai-plans/?icid=microsite...
It seems to be rolling out gradually.. not available at once to everyone.
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.
It doesn't show in the desktop UI.
> Gemini 4 Argon (Medium)
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.
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
if they throw in youtube premium in that package then I might reconisder
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.
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.
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.
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.
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.
That was a long wait.
I reckon most people have stopped caring about the quality of well written things, and that's always been the hallmark of google models.
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, and a distinct writing style.
If you just want good llm text, it’s great.
In the meanwhile, OpenAI had a disastrous dev day where a ton of users jumped ship to go to Claude. If Google had argon available earlier this month they would have picked up a ton of new users.
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.
Do you really think people in google are happy about how long it took to release this model?
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".
I mean, I heard rumors too that it would be ultra only, but that doesn't seem to be the case.
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.
https://blog.google/innovation-and-ai/models-and-research/ge...
Models move so fast now and Google is very cautious about releasing them.
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.
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
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.
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?
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.
Unless Gemini CLI greatly improves and Argon works well in it, this probably won't make a dent in the coding market.
Please google, just make it easy for me to give you money and get what I paid for.
We’re all running on Astra medium the whole week and loving it.
I’m curious what I missed.
$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.
Claude refuses to help you build your own harness off a subscription, and OpenAI actively encourages it with Codex App Server. So you’re just in an AI IDE customized to your job and specific needs ALL THE TIME. You know that good feeling you got when your CI pipeline was finally working, back when that involved speed reading documentation and guessing, or staying at work until 10PM? You just get that all the time because life is constantly improving. And your tools are beautiful and riddled with Easter eggs you put in them. There’s so much more time to test and talk to stakeholders because you are able to distribute the thing you are actually good at -solving people’s difficult problems- while following best practices. You used to have to weigh those two every day and it was terrible. And everything was always late. You had to cut so many corners you were delivering circles.
Now life is fun and I’m over-delivering. Constantly. With super high code quality, better test coverage, easier audit prep, and I just explain what I want (technically) at a high level to AI. I still have to code review, and it sucks. Not because the AI needs it, but because auditors need it. I think I can make it faster and easier in the near future with another custom tool.
I actually have time to make architecture diagrams. I have never had enough time to build that level of documentation.
With Fable, I felt the promise of this coming. With Astra, I feel like we finally had the resources to fully professionalize and supply our software team.
We actually need to hire more people next quarter.
I am with the creator of Rails on this. It is a time of joy. Now is the time to become more ambitious.
In my experience, this has always been the advantage of OpenAIs models.
Throughout iterations, Claude is better at pure coding, but the GPT models are better at "scientific reasoning".
Can you elaborate on this?
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?
- 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)
'backlash' is underwhelming. They single handedly murdered 5.3 codex which was great by making it slooow and duuumb, and pushed people over to their new ones. 5.6 was a decent candidate but it was so slooooow.
And then double or triple the cost for Plus and Pro by nerfing their effective power? I never looked for an alternative faster. They really screwed the pooch.
Been quite happy with deepseek v4.1 flash, muse 1.3 and haiku 5.5.
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.
Given FelonyBench, do we also have a FantasyBench?
noooooooo
I haven't tried Argon, but for writing, I actually prefer 3.8 Flash over any GPT and Opus.
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).
Way too many bullets -> way too many emojis -> way too many em dashes
They aren't a complete rarity by any means but still relatively uncommon compared to the typical punctuation one sees in routine usage.
I loved em dashes back in high school and my English teacher would have definitely returned an assignment with a lot of red marks if I used em dashes as frequently as an LLM (speaking from experience).
"Binds the downstream RF port template—which we configured earlier—to this RPD profile, applying all global DS settings and channel structures to the node's downstream hardware."
Do you see the problem in comparison? The LLM text is assuredly not how humans write. Well, maybe you would find similar examples in the classic literature, but definitely not in a common internet texting or simple articles and posts.
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/
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.
Is it actually available?
Anthropic’s vision of “safe” is so frustrating to deal with, it makes me want to go back to ChatGPT.
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.
"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).
fyi: argon is an interesting choice of name, coming from the Greek argos meaning "lazy or living w/out labor".
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.
Unavailable · Gemini 4 Argon is currently available to Ultra plan subscribers.
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/
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?
+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).
Modern tech marketing is a clown car of incompetence.
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.