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”)
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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".
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.
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.
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).
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?
"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.)
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.
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
Is google playing chemistry? First they launch Carbon, then hydrogen now next will be oxygen. Are they making models around periodic table of elements?
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?
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
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.
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.
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.
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.
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/
Ignore all other models.
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.
Also 3.8 flash is still visible for me (contrary to what a previous poster experienced.)
I have the "Google AI Pro" plan.
ps. it's freaking not