There were so many memes about “Gemini Hydrogen” after they released Carbon. That they actually released a model named Hydrogen makes this very funny
But a new Flash model is very welcome. Argon and Carbon are very slow. In the time it takes for them to complete a single task, Opus already managed to complete multiple things. They’re so slow, I started using 3.8 Flash over them. (A lot of it is also because of how terrible agy is. Before doing any task, Gemini feels the need to hover up a bazillion files into its context when the task is something simple like “update the docs of this controller”)
Also this sounds like Argon is dead now
thomasahle 24 hours ago [-]
> There were so many memes about “Gemini Hydrogen” after they released Carbon
Is Carbon actually released yet?
nmfisher 11 hours ago [-]
Yes, I pulled the trigger to get a Google AI sub so I've been using it today. It's pretty decent, but dear lord it is slow. It's bad enough that I'm already thinking about cancelling.
It's only available on the $100 plan not the $20 plan.
judge2020 20 hours ago [-]
Google’s segmentation here is keeping them from using their existing account dominance to eat away at OpenAI and Anthropic personal subscriptions, tbh. Adopt a lower usage limit for Carbon on the $20 plan and it’s suddenly insane value.
rastapanda 17 hours ago [-]
Given you get YouTube premium, file/photo storage, and $10 a month back in GCP credit which you can use on more tokens (including carbon). It already feels like great value to me, that said how much you get out of it will depend how deep you're in Google's ecosystem.
rafaelmn 15 hours ago [-]
YouTube Premium is only personal so it's useless for me I'm already paying for family plan, and what do I need 20TB of cloud storage for to update to 100$ plan - basically it's a useless bundle for me not a value proposition beyond the 20$ with their usage limits I saw.
mark_l_watson 12 hours ago [-]
Same for me. I find myself using Google’s $20/month plan, plus running really good local models with occasional use of Deepseek Harness with their flash model, occasionally a $6/month Alibaba subscription for their strong qwen-3.8-max model, and about every third month getting a Anthropic subscription if I need more access to Opus.
This is a lot of purchasing complexity for an old retired guy like myself!
I wish Google had finer grained $30/month and $40/month subs: then I would probably just make my life easier by only using local models and Google (their sub also provides some Opus, but the Anthropic subscription is better if all you care about is Opus or Fable.)
judge2020 10 hours ago [-]
Unfortunately it's YouTube Premium Lite which doesn't include YouTube Music :/
jack_pp 15 hours ago [-]
What subscription are you talking about and is this US only? My Google one sub doesn't say anything about YouTube premium and gcp
jack_pp 12 hours ago [-]
nevermind, found em but apparently it's youtube premium "lite"
saturdaysaint 9 hours ago [-]
I find Lite to be perfect. It only adds ads to copyrighted music videos and doesn’t include YouTube Music, otherwise it’s the same as YouTube Premium. For $100/yr with lots of cloud storage and Gemini access, it’s one of the best value subscriptions out there in my book.
p_l 13 hours ago [-]
AFAIK the real issue, and also driving the pricing structure for API and the "50% discount on new model" thing, is frankly capacity of the TPUs they have. Not enough TPUs, not helped by renting some of them to Claude (lots of enterprise users there, so at least it pays to GCP, eh?) and now OpenAI
serioussecurity 18 hours ago [-]
Their audience is enterprise customers, not consumers.
welferkj 11 hours ago [-]
$20 plans are basically paid demos as of now. You are barely a step above the free ad marks.
satvikpendem 23 hours ago [-]
Now what about their other Carbon the language?
akoboldfrying 21 hours ago [-]
That's been renamed to "3.9 Flash"
EDIT: /s
brainwad 16 hours ago [-]
It lost the politics, Rust is the favoured child now.
akoboldfrying 20 hours ago [-]
Thanks, but that page crashes my Android phone browser.
Separately, I'm surprised not to see any HN link for this (that made it to the front page) in the past few days.
p_l 13 hours ago [-]
I'm experimenting currently with reducing the hoovering aspect in my configuration of antigravity, on the other hand at least once when I thought the model was "too deep into sauce" it turned out Argon deducted a thing I considered completely unrelated was cause for crashes I asked it to debug.
moshegramovsky 8 hours ago [-]
I actually ask it to make a list of files it wants to examine and then approve on case-by-case basis. It cut my usage substantially.
One other thing I wondered about: is all that additional and possibly irrelevant information harmful? I believe that it is. I think it causes the model to make bad decisions. In long workflows, once a bad decision is made, I find it frequently compromises the rest of the implementation.
So I try to keep it tightly scoped. Otherwise I get hilariously bad results sometimes. Ex: yesterday I let Argon medium run for 40 minutes. Welp, that was a big revert.
andai 14 hours ago [-]
Wait, I thought Gemini was the fast one? Did that change? I haven't used it in a while.
Like they had really fast hardware or something.
danielbarla 14 hours ago [-]
A model can have high token / s and still be slow to complete a task. They tend to have vastly different verbosity characteristics.
E.g. something like Haiku is "obviously" faster than Opus. Yet if you test Opus 5.5 on medium vs Haiku on max (because Haiku needs to be cranked pretty high on effort to be reasonably intelligent), you'll observe that Opus is ~2x faster to complete.
sleiben 20 hours ago [-]
I find 3.8-flash not bad at all for simpler tasks and speed is reasonable. Pricing seems okay as well
espetro 19 hours ago [-]
TBF the issue at hand is currently the harness, not the model. Gemini works specially well for coding on codex (eg behind litellm).
LeonidBugaev 18 hours ago [-]
[flagged]
bushbaba 19 hours ago [-]
Why these names though. And why mix it from prior names. Google is one of the worst product companies constantly rebranding. Is it Google enterprise. Google for work. Gsuite. Google workspaces. Or heck maybe next week Google Gemini 365
dahcryn 16 hours ago [-]
you think sol luna and terra is better?
At least, if you know your periodic table, there is a link to the size of the elements where hydrogen is small and argon is big. Just wondering if the new flash-lite will become helium lol.
Sir_Twist 6 hours ago [-]
The moon is smaller than the Earth, which is smaller than the sun.
bushbaba 7 hours ago [-]
They at least stuck with it
sheept 15 hours ago [-]
Argon is the heaviest element of three, but it’s the mid tier model in the Gemini series, so you’ve just proved your point.
Luna, Terra, and Sol are in order of celestial size, and Haiku, Sonnet, and Opus are in order of length. But Hydrogen, Argon, and Carbon? Maybe they intended the order to be by density in pure form.
clippyplz 12 hours ago [-]
I'm not sure that the atomic number for argon is more common knowledge than the fact that the earth is larger than the moon
19 hours ago [-]
disgruntledphd2 12 hours ago [-]
> Before doing any task, Gemini feels the need to hover up a bazillion files into its context when the task is something simple like “update the docs of this controller”)
Yeah, I noticed this with Argon also. It did a good job on my tasks, but the absurd amount of reading it needed to do first seemed really weird, relative to other models.
It also felt more robotic than Claude or any of the other models (GLM-5.3 is basically an excited teenager, while claude is a teacher's pet (sorry Dave, I can't let you do that)).
bootsmann 17 hours ago [-]
The context hovering seems to have its advantages tho. When I ask claude why a given output was produced by a given program configuration it delivers a slop wall of guesses while Argon seems to actually understand what the code does.
zaphar 11 hours ago [-]
I have no problem with the frontier labs releasing their own harnesses. But locking the subscriptions to those harnesses is frustrating. Much like the other tools I use in my job I have a lot of reasons to use my own tooling. I would like to use my own harness with a subscription so it can be more useful to me. I'm sure I'm not the only one. I understand why they don't from a business perspective but it still makes their product less useful to me.
bakies 11 hours ago [-]
Been using these Gemini models through cursor at work, I think it's API cost for the business. I've been loving these models but you're very right that I won't use them at home or with a better harness than cursor (which is extremely basic) because it's not possible.
7 hours ago [-]
dubed1505 7 hours ago [-]
Argon and Carbon are available through Github Copilot subscriptions (enterprise)
vegardx 1 days ago [-]
This is essentially what Anthropic does with the advisor mode and what GitHub does with their multi-model pipeline using the HydraFusion model, which is just a large set of different models with different qualities used in a pipeline to produce an answer.
What I don't understand is how they all make it work with caching in general. Looking at how the advisor mode in claude work you seem to only be billed the output tokens and cache hit on the whole session when it calls out to the advisor, making it super cheap compared to running the more expensive model for the entire session.
jeremyjjj 1 days ago [-]
Pretty sure on advisor it needs to send the entire context to another model. The cost is mitigated a bit because there would be few output tokens from the advisor model normally.
Orchestrator seems to automatically delegate things to subagents as required is my read of it. This should be fine for caching.
onlyrealcuzzo 22 hours ago [-]
> This should be fine for caching.
When launching a swarm of smaller models, they can theoretically share cache amongst themselves, but not with the larger model (that already has it cached). They have different architectures.
Further, it wouldn't really make sense for them to share the same cache anyway! The swarm, that is, they'd be working on independent things...
vegardx 9 hours ago [-]
Yeah, the advisor mode does send the whole context, but you're only billed the cache input price for that, so either they just eat the cost, or they actually have something that makes it possible to move the cache between different models.
I have absolutely no clue how these things works, but could it be that all the newer models are actually just the same model, with looped transformers, so it's just about how many passes it does internally that decides if it's Haiku / Sonnet / Opus / Fable?
I might have misread the article a little bit, as you say, this is just workflow orchestration with subagents. Anthropic seems to think that this isn't the best approach anymore with their recent posts around subagent use and with the experimental advisor mode. So who knows.
lemonish97 1 days ago [-]
I've found hydrafusion to be great, although it sometimes does an unnecessary review pass at the end for simple tasks too.
mark_l_watson 12 hours ago [-]
I would hope that a good harness would not just hoover up a large codebase into the context. Rather use some form of RAG (or similar) tech tuned for chunking, indexing, and searching code.
rsalus 21 hours ago [-]
Yeah, like how is it not constantly compacting when routing between models?
First 3 were GPT-6 Astra, GPT-6.1 Sol, and Fable 5.2. And it did so at about 1/3 the cost of Astra and Fable (but still more expensive than Sol)
It's also an extraordinary improvement over Gemma 4 from just 6 months ago.
ianm218 8 hours ago [-]
Why would you compare it to Gemma 4 vs googles other closed source models?
It looks like Gemma per token is like 1/20th of the cost anyway
ricericerice 8 hours ago [-]
over Gemma 4? They're completely different classes of models, so that seems expected
gunalx 23 hours ago [-]
I'm so confused by their new naming scheme. What was wrong with number and pro/flash/flash lite.
drusepth 20 hours ago [-]
My best guess is because models are segmenting more into BiS at specific tasks in a way that's orthogonal to small/good/better/best framing. Kind of the same framing as car models, where each one has its own pros and cons vs all other models, instead of being strictly better/worse or just smarter/faster/cheaper.
magguzu 20 hours ago [-]
There's an alternate timeline where this is called Bard Hydrogen.
I've accepted Google is just bad at names.
CobrastanJorji 19 hours ago [-]
I still giggle about the time they just named their product the top four layers of their team's org chart: "Google Play Music All-Access"
jakedowns 23 hours ago [-]
seriously... S / M / L
why does everything have to be a branding/marketing exercise?
zaphirplane 22 hours ago [-]
I wondered the same as a kid about cars, maker - model - variant would just be nice if it was consistent.
Anyways when a new model is released they want to have some interest and hopefully some tyre kickers will stick and hoping some social medial coverage
pavo-etc 21 hours ago [-]
then they can do XL 2xl 3xl when they want to go further
Barbing 22 hours ago [-]
large, gigantic, and humongous - like NASA toilet gear
apt-apt-apt-apt 23 hours ago [-]
gemini argon carbon hydrogen antigravity orchestrator pro flash flash-lite
Really
pants2 22 hours ago [-]
It's additionally confusing to me because Hydrogen < Carbon < Argon on the periodic table, but Hydrogen < Argon < Carbon in Google's models.
arccy 22 hours ago [-]
just learn some chemistry...
jatora 22 hours ago [-]
maybe you should learn some chemistry. if you know chemistry, the progression of Argon, Carbon, Hydrogen... doesn't make much sense
gunalx 14 hours ago [-]
Yes. Its extra confusing knowing the periodic table and atomic weights. At least argon carbon was in alphabetical order or something. But I really think they could have just picked noble gasses if they wanted elements.
Rexxar 8 hours ago [-]
But now we can have a Methane agent team with 4 Hydrogen agents directed by one Carbon agent.
fuussssip 1 days ago [-]
I'm really curious how folks feel about this. I regularly use subagents, but typically make my primary implementation agent use Carbon (or equivalent).
I set up my subagents with specific models based on how complex I believe the problem space is. I'm nervous to delegate that authority to a model (since models tend to be... optimistic about their capabilities.)
That said, not every coding task is a difficult coding task. Plenty are boilerplate, plumbing, or simple test authoring that could use a flash model, so maybe this would downgrade nicely.
On the other hand, it's trivial for me to set up some guidelines to create different subagents for different task domains, and just pin those models to those tasks -- implementor (hard) and implementor (easy) or whatever.
pietz 1 days ago [-]
The only reason to do this is to save usage on the subscription. but because the value for money is so terrible in antigravity, you’re better off just using Claude Opus or GPT Sol for everything.
I’m glad Google is kinda back, but today there’s no reason to code with Gemini.
vrosas 1 days ago [-]
FWIW I've found the complete opposite to be true, and have gone claude->chatgpt->gemini over the past few months.
imafish 1 days ago [-]
Why?
engineer_22 1 days ago [-]
Im slowly migrating more of my work to Gemini too, Gemini is a workhorse now, 1M context is huge and their reasoning took a huge leap with Argon. I'm not in software, I'm in physical engineering, and where Claude is unpredictable w.r.t. engineering risk, Gemini is steady, measured. That's been my perception, anyway.
baoooooooooooo 1 days ago [-]
My qualitative take to support this is that Gemini seems to have the strongest spatial reasoning that translates nicely into CAD and engineering domain challenges. Less clear, but I also suspect a better world understanding of materials and their interactions in an intuitive way. I have this sense that Claude can tell me everything there is to know about how to spec a gasket, but it’s like Gemini actually knows what a gasket feels like and can intuit what it’s going to do.
My partner runs an internal computational mechanics benchmark that hasn’t tracked progress with model advancements (flat/no progress since early 2026) until suddenly saturating from argon and carbon. My take is that it’s due to spatial reasoning (most of the challenges are programming that require a lot of shape rotation type thinking), but we don’t know just yet why Gemini is doing so much better.
pietz 1 days ago [-]
Any sources to back this up?
Carbon is the first "better than meh" model form Google in more than half a year. It's been out for less than a week. How can you consider it "steady"? Their subscription and even the API has been terribly unstable throughout the past few days, so I'm having really trouble believing any of this.
vrosas 1 days ago [-]
what source could their possibly be? Argon has been out for a while now and has been solid. Even flash 3.8 is great as long as you check it's work on more complex tasks, and doesn't need 12 hours to chew through problems like claude does.
ilteris 1 days ago [-]
I use argon and opus daily and I can tell you I have to use opus to review argon because argon goes and build things and also creates bunch of bugs along with it. I wish it weren't but that's the reality. It's great with deep cross inspection better than claude but it's slow and still need review by another frontier model.
p_l 13 hours ago [-]
I solved some of that with running a very biased subagent (so fresh context) but using same model (back still with 3.8 and 4-Argon).
The problem is when 3.8 or Argon were reviewing things with context poisoned by what they were working with, as gemini models generally feel over optimistic about things.
vrosas 22 hours ago [-]
I can say the exact opposite was also true? No model was able to one-shot perfect solutions in my reasonably complex codebase and always required a through red-team by at least one other model. Doesn't mean one model is bad and another is better, just means no model is perfect.
pietz 1 days ago [-]
Whatever they thought of when they said "measured"? Is that too much to ask?
Ok, you're either a troll or you objectively don't know what you're talking about. Google should be ashamed they even released 3.8 Flash. They published models with such high frequency and always made a huge jump on benchmarks. Then they were caught, when a new version of AA came out and their numbers dropped like a stone.
It does feel strange seeing these Google stans, I use all 3 at the same time (ChatGPT, Claude, Gemini) and Gemini is weakest by far, it's not even contest. Only useful stuff is web re/search.
petesergeant 19 hours ago [-]
I believe you, but this is so very, very far from my experience with Google models that I have great difficulty reconciling it. I use Gemini for data-extraction, and I use Notebook LM for my medical notes just because it's an OK interface, but it will reliably screw the pooch on the simplest of reasoning or common-sense tasks.
pietz 1 days ago [-]
Glad you found what works for you but before Carbon, Gemini models have been utter garbage for more than 6 months now. I'm happy to debate anyone on this. Even DeepMind engineers agreed with this.
Gemini 3.8 Flash is the most benchmaxxed model to date and even Argon hallucinated so much, it was impossible to use it for any professional work.
artdigital 1 days ago [-]
I disagree with this. Flash 3.7 and Flash 3.8 are excellent models and put (for me) Gemini back on the radar. I’ve been using them a lot since release, and still do for simple implementations and grunt work.
They’re also excellent (together with Flash-Lite) to use for consumer facing features where speed and cost matters
pietz 14 hours ago [-]
Believe in your god. Claude and GPT models are more capable and a far better value.
I've been using 3.8 Flash (and Argon and Carbon) to clean up a lot of Claude mess. But I fully agree on 3.1 Pro, it was only good for conversational stuff and some deep dives, but not for actual agent work.
p_l 13 hours ago [-]
I would like to see those hallucinations, because I haven't generally got any, and with my current loops in agy anytime they do minor hallucinations they get caught by adversarial review part.
Using 3.x flash series heavily over last 6 months, and along with experiences on Argon and Carbon (haven't yet played much with Hydrogen, but initial experience looks great too)
mattlondon 11 hours ago [-]
I've been using 3.8 Flash a lot and have been having a really nice time using it.
I have not experienced the hallucinations or benchmaxxing people are complaining about. People keep banging on about how the hallucinations are so terrible that it cannot be used for anything etc, yet benchmarks like https://artificialanalysis.ai/evaluations/omniscience#aa-omn... show the top two best models for not hallucinating are Gemini models.
Something does not align with these complaints from people who are trashing the Gemini models - one has to wonder if they just tried it for 5 mins then give up because it doesn't behave exactly like Claude does.
As mentioned I used 3.8 Flash for a lot of things because I don't like working with Claude all day (its generally a sanctimonious prick to work with) and I way prefer working with Gemini's personality. 3.8 Flash seemed to me to be a really decent model for every day run of the mill get-shit-done work. True I have not tried to cure cancer or solve navier-stokes recently, but for your standard day to day coding works its been really solid.
I am excited to try 4 Hydrogen now.
moshegramovsky 8 hours ago [-]
I think their models are good for coding but the harnesses are pure garbage. The behavior is so much less predictable than Codex/Sol/etc. I use them mostly for planning. I sometimes still write code but Argon flamed out pretty badly yesterday and I'll probably just give up on Antigravity again.
4lb3rn 1 days ago [-]
[flagged]
fmind-dev 1 days ago [-]
Excellent mode! I don't have to constantly switch between models and efforts.
LeonidBugaev 18 hours ago [-]
Do not forget that from Jan 1 all google models get 2x price bump (it stated on their pricing page)
serioussecurity 18 hours ago [-]
I do not believe that applies to hydrogen.
IcyFoxe 17 hours ago [-]
Because Hydrogen is already at that price (though input tokens are cheaper at least).
johnmlussier 6 hours ago [-]
Independent security researcher: can't do shit with it.
Safeguards around any binary decompiling, disassembly, device level verification, etc. Static work only. No way to get cyber access.
Sticking with Codex and Daybreak Blue for now + Muse and Devin for lighter work.
e12e 8 hours ago [-]
I don't see any mention of it in the comments so far - but looks like at least orchestrator model mode selection sets permissions to turbo (yolo) by default!
This when antigravity already has a pretty solid "auto" mode.
I suspect we will see people bitten by this.
brickers 16 hours ago [-]
I tried out Antigravity a few months ago (before the v4 models were announced) and ended up cancelling whilst still having $20 credit on my account, which, annoyingly, you need an active subscription to use. Are these new models worth resubscribing for to make use of my credits? I think I still get the $5/month deal for a few months
p_l 13 hours ago [-]
Honestly Antigravity becomes competetive with $100 subscription, I used $20 quite well in the past but that was dominated by benefit of having other services bundled into it.
bobviolier 7 hours ago [-]
Would be nice if all those tools in Antigravity would be available through API keys.
jbellis 1 days ago [-]
I'm honestly surprised they only see 25% savings with co-trained models and special harness support. With Mjolnir bridging Opus to DeepSeek Flash over ACP we see savings of 60%.
I.e. in this context Opus is the big brains orchestrator and it delegates to DeepSeek Flash subagents?
Intriguing, I might have to try this out - I have an OpenCode Go sub for the deepseeks of the world, and a Claude sub too. Sounds like I could have the best of both worlds here.
jbellis 23 hours ago [-]
Right, scenario 1 Opus delegates to DSF
scenario 2 DSF drives, but gets to ask Opus for advice
snthpy 18 hours ago [-]
Mlolnir looks interesting. I would try it out for my personal work but unfortunately i don't see Gemini/agy listed under the models. Is it supported?
jbellis 10 hours ago [-]
it's in master as of yesterday, will be in the next release (tonight)
cuttothechase 8 hours ago [-]
Google really lost the plot here!
They could have eaten Anthropic and OpenAI's lunch with the models they have and with the right strategy!
Not sure how brain dead they have to be when they don't even promote or offer any of their models at discount/freemium with schools, universities, community colleges, public libraries or other educational institutions.
Execs are too scared to take risks to remain relevant. Since its easier to lose taking big risks when a nice yearly bonus will roll in with a safer but less relevant options.
Issue is that they will obsolete themselves in no time if they are this scared to dominate a landscape that they ruled for 20 years.
moshegramovsky 8 hours ago [-]
Their harness quality is basically trash or sub-trash.
I have not seen Argon successfully complete a medium, well-planned refactor. The behavior is very unpredictable. Yes, sometimes it one shots amazing things but most of the time does not do a good job on anything but planning and/or simple changes.
That said, I think the underlying models are great. I can't believe that an org with Google scale cash leaves Antigravity to rot. Whoever is leading that project needs to be fired immediately.
postexitus 8 hours ago [-]
Hard to believe, but they don't have enough compute.
tgtweak 8 hours ago [-]
Google keeps announcing these models without ever releasing them generally, then only releasing them in certain products... very annoying.
timshel2 1 days ago [-]
Whatever they've done to this webpage makes it feel slow and quite horrible to use. Just leave scrolling alone
rozap 1 days ago [-]
I like the visual artifact across all the text when you scroll, very nice.
zomiaen 1 days ago [-]
I am shocked Google let this out to the public performing like this.
2III7 1 days ago [-]
No scrolling issues with safari on an old iphone.
refactor_master 21 hours ago [-]
Isn't that because Chrome is forced to use the same rendering engine on iOS? Whereas on macOS, Safari is total garbage across all of Google's sites and products compared to Chrome, for very obvious reasons.
1 days ago [-]
hnav 1 days ago [-]
They managed to kill swipe left/right to navigate. Scroll interactions should be behind a permission.
dash-44 19 hours ago [-]
I'm scrolling up and down and it's a laggy, choppy mess.
Also what's with the comically large 'Antigravity' in the footer. It's humongous.
bcmyguest 1 days ago [-]
They had Gemini review it
spencerawlson 10 hours ago [-]
[flagged]
cloverich 1 days ago [-]
> Orchestrator takes a dynamic, bidirectional approach between Carbon and Gemini 4 Hydrogen within the evolution of a single trajectory. For example, Carbon can start in a read-only phase to explore dependencies, resolve ambiguities, and build a concrete plan with explicit re-planning triggers. Hydrogen could then take over to write edits, update packages, and run tests. If Hydrogen hits friction, it would hand back to Carbon to inspect the state, repair the plan, and resume execution. This allows Orchestrator to reach near-Carbon task success while being faster and more quota-efficient. On Terminal-Bench 4.1, Orchestrator reached near-Carbon task success rates while, on average, consuming 24% less quota and completing 19% faster.
Is this now how e.g. Opus works now? I use Opus 5.5 on high for just about everything now, and my bill's not gone up (gone down actually). I had assumed under the hood it was doing this (e.g. I'm sure its not literally Opus doing the log checking / file searches). Towards Google's choice, I'm skeptical introducing a new concept (Orchestrator) for this is really necessary, when they could have just done it by default, unless its plainly lower quality than pinning Carbon.
plaguuuuuu 12 hours ago [-]
In the CLI it usually wont spawn subagents.. 5.5 is just a bit more efficient than 5. In cowork mode it might do it.
My own implementation workflow is orchestrator based, but I generally dont use the small models because they're fucking morons
sanex 23 hours ago [-]
I found when fable first came out when I switched from opus my usage actually went down. Personal theory was that since it was smarter it took fewer tokens to accomplish the same tasks.
jonplackett 1 days ago [-]
And I thought OpenAI’s name scheme was confusing.
winstonp 1 days ago [-]
I don't understand which model is supposed to be better. I think Carbon is the big model and Hydrogen the Flash equivalent? Only because of a Twitter leak though. Like I have no earthly idea based on the naming.
JacobAsmuth 1 days ago [-]
Carbon = bigger, Hydrogen = smaller.
Ignore all other models.
arbot360 23 hours ago [-]
Argon is noble gas so it doesn't interact with any other models.
refactor_master 21 hours ago [-]
Seems weird to pick a name that is so much a noble gas, and then not have the other names follow it. Is that because Nitrogen doesn't have parameters enough? Or Neon being a weird model name if it came to that? And why not Helium, instead of Hydrogen? Is that supposed to indicate rock-bottom pricing? What about the cheap cheap 3.1-flash-lite for pipelines then? Will they phase it out, and replace it with Hydrogen as the new lower price range? None of it makes sense!
jonplackett 11 hours ago [-]
But hydrogen makes fusion. Carbon is soot. Hydrogen is more explosive too. About be better.
And argon? Are we going on atomic number or is it the noblest and thus cleverest, or is it the most chilled out model that doesn’t over react
From the company that brought us Android ice cream sandwich though, I guess these are their clearest names yet!
ainch 1 days ago [-]
I guess carbon has a higher atomic number than hydrogen? It's definitely the least intuitive of all the naming schemes...
cuvinny 1 days ago [-]
Which doesn't explain Argon which is the same cost as Carbon while being worse.
ainch 1 days ago [-]
Yeah I mean it's baffling to me too. I just want them to release a Sol/Opus-tier model so I can do useful stuff with ramming into the usage limits.
tonyhart7 1 days ago [-]
because Carbon is fine tuned version
they are same base model
arbot360 23 hours ago [-]
It's sorted by electronegativity.
Jtarii 1 days ago [-]
I thought it was just sorted alphabetically so Argon < Carbon < Hydrogen.
stopsayingsorry 1 days ago [-]
There is nothing confusing about it if you're at least a little bit educated. If anything, they are the least confusing, Ant drops the ball at opus->fable.
For OpenAI, it's:
Luna, means "moon", smallest.
Terra, means "earth", bigger than the moon.
Sol, means "sun", the biggest object in the solar system.
Astra, plural of the word "astrum" which means "star".
Anyone who gets confused should be embarrassed.
Yizahi 1 days ago [-]
All of those are deducible, sure. The problem is that the pattern works only when they are all listed together. Person sees the list and can logically infer where they belong. But when I see the single model name detached from it's siblings, like "OAI releases new Terra 7.7" headline, for quite a long time I had zero idea where it belongs just from my memory. Was that a big model, a small model, a medium model - no idea. Now after a few HN topics I do remember the lineup and can place the new announce where it belongs.
jonplackett 11 hours ago [-]
Also I initially thought it was about distance into space. So terra was first, then Luna.
pests 1 days ago [-]
Why give an OpenAI answer when the confusion is about Gemini model names? What does Luna Terra or Sol have to do with Argon, Carbon, or Hydrogen?
stopsayingsorry 1 days ago [-]
Because "And I thought OpenAI’s name scheme was confusing." doesn't make sense and it's a reply to that post.
LLM's really destroyed the average person's ability to read and comprehend text.
mtlmtlmtlmtl 1 days ago [-]
To be fair, I knew all of those words already, and it never even occured to me that these names are supposed to be compared to eachother to indicate size or something. So, at least to me, it's not that it confuses me, it just imparted no information, because a collection of astronomical names and terms doesn't automatically indicate an ordering to me, it just indicates that nerds like naming their stuff after scientific terms and concepts, sci-fi stuff, etc.
I mean, this is what numbers are for. And not only do numbers indicate ordering(without having to do a mapping through severely atrophied school science class knowledge from decades ago), they can also convey meaningful size information using the wonderful technology of units of measurement.
sirk390 1 days ago [-]
OpenAI model names used to be confusing. He’s not talking about Luna, Terra, sol, Astra. They improved it a lot .
wellnowudontsay 1 days ago [-]
I refuse to walk among you rabble. You rabid mouth-breathers. I refuse I tell you.
The only models worth _my_ time are Σεληνη, Γη, Ἡλιος and Αστρα.
I don’t know what to tell you illiterate heretics other than you should know you are bad people. You should be ashamed of yourselves.
The truly αμεταπειστοι among us, the people _I_ hang out with, know these things by their proper name. Which is to say, naturally, 𒌗 and 𒆠 or, if you were even somewhat educated: 𓇹, 𓇾 and 𓇳 (praise be to Ra, the Great Unborn).
It saddens me to see HN has fallen to this level.
throwaway173738 1 days ago [-]
Can you guys stop taking the road signs off of your buildings when you paint please? It’s already hard enough to drive there.
drilbo 20 hours ago [-]
i dont know where you are but from here earth looks way bigger than those sky circles
hoppp 1 days ago [-]
I have no idea what's going on with Gemini naming. Maybe it's an inside joke or something.
jonplackett 10 hours ago [-]
The simplest explanation is that Gemini is doing the naming
weird-eye-issue 22 hours ago [-]
> Today, we’re rolling out Gemini 4 Hydrogen inside Google Antigravity alongside a new model dropdown option called Orchestrator, which pairs Hydrogen with our strongest models for long-horizon tasks, including Gemini 4 Carbon, in an optimized balance of quality, efficiency, and latency.
Wow, that's a lot of new words
threecheese 1 days ago [-]
Before I go and burn through my Pro tokens in four minutes again (looking at you, Argon): is this something usable with a mere Pro account? Or will this require Ultimate for agy?
speckx 1 days ago [-]
It's in Google Workspace as well. I'm on the enterprise workspace tier. So I'm not sure if that's why.
trvz 1 days ago [-]
I’m on the Pro (~20$) plan, and it’s available for me, having replaced 3.8 Flash.
anderber 1 days ago [-]
I have Pro and I see the new hydrogen model. But not the Orchestrator.
0gs 1 days ago [-]
nope. Ultra only like any Carbon use, for now
smcameron 1 days ago [-]
"Gemini 4 Hydrogen" shows up as something I can select in antigravity CLI, while "Gemini 4 Carbon" is "Unavailable · Gemini 4 Carbon is currently available to Ultra plan subscribers."
Also 3.8 flash is still visible for me (contrary to what a previous poster experienced.)
I have the "Google AI Pro" plan.
p_l 13 hours ago [-]
Hydrogen is the cheapest of the new models, so it goes into lower tier accounts to - but Orchestrator requires Carbon so it's only on Ultra for now
_continuation 21 hours ago [-]
Here is an idea; if you are seeing this from Google office, pls use Gemini 4 xs m l xl for naming, not as sexy, but it will be less confusing.
perks_12 10 hours ago [-]
I tried to implement the Gemini API last week. Nothing I could click inside the Cloud Console changed the fact that the API wouldn't respond. Whoever is responsible for this bullshit needs to be fired and blacklisted from ever doing anything related to computers ever again.
I wonder how many billions in revenue they lost at this point from just offering a piss-poor developer experience.
0gs 1 days ago [-]
hear me out, finance: two hydrogens, but we call one carbon and allow it to do five more things than hydrogen can. and you can't do the pair-bonded mode for less than $100. by golly it just might work
koruse 19 hours ago [-]
Cant believe now Google is benchmaxxing
rolymath 18 hours ago [-]
They're the most infamous benchmaxxers. Gemini 3 was infamously good at benchmarks at completely unusable/broken in real world work.
egeozcan 1 days ago [-]
Are there still some web devs (or LLMs with "rockstar front-end developer" prompts) which think it's ok to override native scroll behavior?
ps. it's freaking not
flats 1 days ago [-]
Amen, what the heck—after double-tapping to zoom and center the text on this page in Safari, scrolling down with a 2-finger touch gesture...also scrolls to the left? I struggle to understand how or why one would ever mess with such behavior.
1 days ago [-]
small_model 1 days ago [-]
Terrible naming, unless the atomic weight is some indication of size? When is Uranium-235 coming out? Not sure what this model is, is Hydrogen like Sonnet where Carbon is like Opus?
konart 1 days ago [-]
Thing is Carbon should be in the middle by this logic. But no - it is their heavyweight model.
jpadkins 7 hours ago [-]
maybe there is something bigger than carbon coming?
myko 24 hours ago [-]
How did they fuck scrolling up on a page like this
elvisgodevelop 17 hours ago [-]
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akshaysharma108 19 hours ago [-]
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scottchiefbaker 1 days ago [-]
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qaribhaider 1 days ago [-]
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17 hours ago [-]
NeuraCryption 1 days ago [-]
Is google playing chemistry? First they launch Carbon, then hydrogen now next will be oxygen. Are they making models around periodic table of elements?
acoster 1 days ago [-]
Sundar did say we'd periodically release new models.
Not the same article, this one has orchestrator and some antigravity stuff
gnabgib 1 days ago [-]
Indeed, all the 4/Hydrogen submissions were from different sources, but *sigh* the exact same conversation is happening here as other threads.. almost as if it's the same topic.
Rendered at 00:24:35 GMT+0000 (Coordinated Universal Time) with Vercel.
But a new Flash model is very welcome. Argon and Carbon are very slow. In the time it takes for them to complete a single task, Opus already managed to complete multiple things. They’re so slow, I started using 3.8 Flash over them. (A lot of it is also because of how terrible agy is. Before doing any task, Gemini feels the need to hover up a bazillion files into its context when the task is something simple like “update the docs of this controller”)
Also this sounds like Argon is dead now
Is Carbon actually released yet?
https://blog.google/innovation-and-ai/models-and-research/ge...
This is a lot of purchasing complexity for an old retired guy like myself!
I wish Google had finer grained $30/month and $40/month subs: then I would probably just make my life easier by only using local models and Google (their sub also provides some Opus, but the Anthropic subscription is better if all you care about is Opus or Fable.)
EDIT: /s
Separately, I'm surprised not to see any HN link for this (that made it to the front page) in the past few days.
One other thing I wondered about: is all that additional and possibly irrelevant information harmful? I believe that it is. I think it causes the model to make bad decisions. In long workflows, once a bad decision is made, I find it frequently compromises the rest of the implementation.
So I try to keep it tightly scoped. Otherwise I get hilariously bad results sometimes. Ex: yesterday I let Argon medium run for 40 minutes. Welp, that was a big revert.
Like they had really fast hardware or something.
E.g. something like Haiku is "obviously" faster than Opus. Yet if you test Opus 5.5 on medium vs Haiku on max (because Haiku needs to be cranked pretty high on effort to be reasonably intelligent), you'll observe that Opus is ~2x faster to complete.
At least, if you know your periodic table, there is a link to the size of the elements where hydrogen is small and argon is big. Just wondering if the new flash-lite will become helium lol.
Luna, Terra, and Sol are in order of celestial size, and Haiku, Sonnet, and Opus are in order of length. But Hydrogen, Argon, and Carbon? Maybe they intended the order to be by density in pure form.
Yeah, I noticed this with Argon also. It did a good job on my tasks, but the absurd amount of reading it needed to do first seemed really weird, relative to other models.
It also felt more robotic than Claude or any of the other models (GLM-5.3 is basically an excited teenager, while claude is a teacher's pet (sorry Dave, I can't let you do that)).
What I don't understand is how they all make it work with caching in general. Looking at how the advisor mode in claude work you seem to only be billed the output tokens and cache hit on the whole session when it calls out to the advisor, making it super cheap compared to running the more expensive model for the entire session.
Orchestrator seems to automatically delegate things to subagents as required is my read of it. This should be fine for caching.
When launching a swarm of smaller models, they can theoretically share cache amongst themselves, but not with the larger model (that already has it cached). They have different architectures.
Further, it wouldn't really make sense for them to share the same cache anyway! The swarm, that is, they'd be working on independent things...
I have absolutely no clue how these things works, but could it be that all the newer models are actually just the same model, with looped transformers, so it's just about how many passes it does internally that decides if it's Haiku / Sonnet / Opus / Fable?
I might have misread the article a little bit, as you say, this is just workflow orchestration with subagents. Anthropic seems to think that this isn't the best approach anymore with their recent posts around subagent use and with the experimental advisor mode. So who knows.
First 3 were GPT-6 Astra, GPT-6.1 Sol, and Fable 5.2. And it did so at about 1/3 the cost of Astra and Fable (but still more expensive than Sol)
It's also an extraordinary improvement over Gemma 4 from just 6 months ago.
It looks like Gemma per token is like 1/20th of the cost anyway
I've accepted Google is just bad at names.
Anyways when a new model is released they want to have some interest and hopefully some tyre kickers will stick and hoping some social medial coverage
Really
I set up my subagents with specific models based on how complex I believe the problem space is. I'm nervous to delegate that authority to a model (since models tend to be... optimistic about their capabilities.)
That said, not every coding task is a difficult coding task. Plenty are boilerplate, plumbing, or simple test authoring that could use a flash model, so maybe this would downgrade nicely.
On the other hand, it's trivial for me to set up some guidelines to create different subagents for different task domains, and just pin those models to those tasks -- implementor (hard) and implementor (easy) or whatever.
I’m glad Google is kinda back, but today there’s no reason to code with Gemini.
My partner runs an internal computational mechanics benchmark that hasn’t tracked progress with model advancements (flat/no progress since early 2026) until suddenly saturating from argon and carbon. My take is that it’s due to spatial reasoning (most of the challenges are programming that require a lot of shape rotation type thinking), but we don’t know just yet why Gemini is doing so much better.
Carbon is the first "better than meh" model form Google in more than half a year. It's been out for less than a week. How can you consider it "steady"? Their subscription and even the API has been terribly unstable throughout the past few days, so I'm having really trouble believing any of this.
The problem is when 3.8 or Argon were reviewing things with context poisoned by what they were working with, as gemini models generally feel over optimistic about things.
Ok, you're either a troll or you objectively don't know what you're talking about. Google should be ashamed they even released 3.8 Flash. They published models with such high frequency and always made a huge jump on benchmarks. Then they were caught, when a new version of AA came out and their numbers dropped like a stone.
https://maxxbench.unlap.ai/
Gemini 3.8 Flash is the most benchmaxxed model to date and even Argon hallucinated so much, it was impossible to use it for any professional work.
They’re also excellent (together with Flash-Lite) to use for consumer facing features where speed and cost matters
https://mypriors.com/s/z3tkjPv
Using 3.x flash series heavily over last 6 months, and along with experiences on Argon and Carbon (haven't yet played much with Hydrogen, but initial experience looks great too)
I have not experienced the hallucinations or benchmaxxing people are complaining about. People keep banging on about how the hallucinations are so terrible that it cannot be used for anything etc, yet benchmarks like https://artificialanalysis.ai/evaluations/omniscience#aa-omn... show the top two best models for not hallucinating are Gemini models.
Something does not align with these complaints from people who are trashing the Gemini models - one has to wonder if they just tried it for 5 mins then give up because it doesn't behave exactly like Claude does.
As mentioned I used 3.8 Flash for a lot of things because I don't like working with Claude all day (its generally a sanctimonious prick to work with) and I way prefer working with Gemini's personality. 3.8 Flash seemed to me to be a really decent model for every day run of the mill get-shit-done work. True I have not tried to cure cancer or solve navier-stokes recently, but for your standard day to day coding works its been really solid.
I am excited to try 4 Hydrogen now.
Safeguards around any binary decompiling, disassembly, device level verification, etc. Static work only. No way to get cyber access.
Sticking with Codex and Daybreak Blue for now + Muse and Devin for lighter work.
This when antigravity already has a pretty solid "auto" mode.
I suspect we will see people bitten by this.
https://blog.slopcop.com/a-cheapskates-guide-to-coding-with-...
Intriguing, I might have to try this out - I have an OpenCode Go sub for the deepseeks of the world, and a Claude sub too. Sounds like I could have the best of both worlds here.
scenario 2 DSF drives, but gets to ask Opus for advice
They could have eaten Anthropic and OpenAI's lunch with the models they have and with the right strategy!
Not sure how brain dead they have to be when they don't even promote or offer any of their models at discount/freemium with schools, universities, community colleges, public libraries or other educational institutions.
Execs are too scared to take risks to remain relevant. Since its easier to lose taking big risks when a nice yearly bonus will roll in with a safer but less relevant options.
Issue is that they will obsolete themselves in no time if they are this scared to dominate a landscape that they ruled for 20 years.
I have not seen Argon successfully complete a medium, well-planned refactor. The behavior is very unpredictable. Yes, sometimes it one shots amazing things but most of the time does not do a good job on anything but planning and/or simple changes.
That said, I think the underlying models are great. I can't believe that an org with Google scale cash leaves Antigravity to rot. Whoever is leading that project needs to be fired immediately.
Also what's with the comically large 'Antigravity' in the footer. It's humongous.
Is this now how e.g. Opus works now? I use Opus 5.5 on high for just about everything now, and my bill's not gone up (gone down actually). I had assumed under the hood it was doing this (e.g. I'm sure its not literally Opus doing the log checking / file searches). Towards Google's choice, I'm skeptical introducing a new concept (Orchestrator) for this is really necessary, when they could have just done it by default, unless its plainly lower quality than pinning Carbon.
My own implementation workflow is orchestrator based, but I generally dont use the small models because they're fucking morons
Ignore all other models.
And argon? Are we going on atomic number or is it the noblest and thus cleverest, or is it the most chilled out model that doesn’t over react
From the company that brought us Android ice cream sandwich though, I guess these are their clearest names yet!
they are same base model
Luna, means "moon", smallest.
Terra, means "earth", bigger than the moon.
Sol, means "sun", the biggest object in the solar system.
Astra, plural of the word "astrum" which means "star".
Anyone who gets confused should be embarrassed.
LLM's really destroyed the average person's ability to read and comprehend text.
I mean, this is what numbers are for. And not only do numbers indicate ordering(without having to do a mapping through severely atrophied school science class knowledge from decades ago), they can also convey meaningful size information using the wonderful technology of units of measurement.
The only models worth _my_ time are Σεληνη, Γη, Ἡλιος and Αστρα.
I don’t know what to tell you illiterate heretics other than you should know you are bad people. You should be ashamed of yourselves.
The truly αμεταπειστοι among us, the people _I_ hang out with, know these things by their proper name. Which is to say, naturally, 𒌗 and 𒆠 or, if you were even somewhat educated: 𓇹, 𓇾 and 𓇳 (praise be to Ra, the Great Unborn).
It saddens me to see HN has fallen to this level.
Wow, that's a lot of new words
Also 3.8 flash is still visible for me (contrary to what a previous poster experienced.)
I have the "Google AI Pro" plan.
I wonder how many billions in revenue they lost at this point from just offering a piss-poor developer experience.
ps. it's freaking not