This was rolled out RIGHT away, as when I just went to use Gemini, seeing 3.8 Flash be replaced with "4 Hydrogen" was less hype and more a thought along the line of "What [on Earth] is Gemini Hydrogen???", then me going here to figure it out.

This model naming scheme works for separate products, but using elements, molecules, etc. for products you're supposed to compare with each other... Not very helpful.

If anything, my intuition would say that Hydrogen is more powerful than Argon... I don't know. Not liking this naming scheme trend.

As this is a) being served in Search, b) supposed to be 2.5x faster than 3.8 Flash, c) the element with lowest atomic weight; I deduce that, despite being more capable than 3.8 Flash, now the “entry level” model set to replace 3.5 Flash Lite.

But it is priced the same as the non-discounted 3.8 Flash, considerably higher than what anyone is paying today for 3.8 Flash or 3.5 Flash Lite or the deprecated 3.0/2.x Gemini models. How does this work? Is Google abandoning the “fast and cheap” tier? That seems like a mistake since plenty of workflows are absolutely price inelastic, meaning when the 3.8 Flash discount ends at EOY, lots of current enterprise Gemini customers would have to take their business to another shop??

Anyone else got suspended for just using agy on the command line? "This service has been disabled in this account for violation of Terms of Service. Please submit an appeal to continue using this product.". The support claims that it can do nothing, not even see a reason and pointed me toward a form with no text inputs just a checkbox along the lines of "I understand the TOS, please check". So I filed an appeal, and it seems that it was automatically processed and within a few minutes. agy was working for one more prompt and it triggered a suspension again. What channel can I use to get any attention on something like this? I've heard these Google horror stories... fortunately this is only the Antigravity part, but I've just today upgraded to Ultra and this coincided with that. I've become extremely hesitant to continue using broader Google services when this can not be resolved via their customer support.

If there are any Google employees reading:

I want to go all in the Gemini ecosystem but several things keep me going back to OpenAI:

* the Gemini app is glitchy on iPhone (my chats frequently fail or are lost if I background the app)

* the Work equivalent (I guess task?) is not as powerful. I often have ChatGPT Work to arbitrary computation and even install ML on the short-lived VM.

* there is no simple integration between antigravity and the Gemini app. I want a way to continue working away from my server while using the familiar app. No I don’t want VNC.

* ChatGPT sites are cool for putting up proof of concepts with zero effort

I think a new default free model for AI Mode being so close to the frontier will be a massive jump in perceived AI intelligence by the general public.

This is the most important class of models to keep watch. These are the ones that are going be to workhorses in the post-tokenmaxxing clarity

Can anyone understand the logic behind the names? Argon, hydrogen, carbon, what is the mental model one should use to understand where they fit, or what comes before/after?

Haiku, sonnet, opus.. is ok

terra, Luna, Sol... is also ok..

but this?

The pricing on these models make really little sense. This is $1.5. Argon is $2. Carbon is also $2 for now.

Feel like this pricing only makes sense for a product where you don't even select the model. Maybe Antigravity is like that.

It's starting to feel like OpenAI is in 3rd place now. Really eager to see how / if they can claw their way back up.

I have a stupid benchmark: Bongard Problem 2 from here (https://matheminutes.blogspot.com/2019/04/bongard-eggs.html). It's an open-ended visual task that is easy enough for humans, but models are still somewhat bad at visuals, so it's one of the few remaining reliable ways to trigger hallucinations. This one answered correctly, but then felt the need to add a fun fact that was wrong:

> The rule separating the two baskets is layering (which color is on top). Left basket: In every pattern on all six eggs, the blue shape is on top of (overlapping) the green shape. Right basket: In every pattern on all six eggs, the green shape is on top of (overlapping) the blue shape. [true solution]

> (Note: Both baskets contain the exact same distribution of motif counts per egg—two eggs with 2 pairs, three eggs with 3 pairs, and one egg with 4 pairs—serving as a classic Bongard distractor to hide the occlusion rule.) [factually incorrect and also would make no sense as a distractor]

And then trying a harder puzzle just makes it bullshit completely.

I don't understand why Gemini models always add these "it's typical XYZ" bits, which are typically so much worse than everything else in the answer.

Personally I found my usage of llms bimodal, I only have uses for the top frontier models (for research and development) or for the cheapest and fastest ones (to use in production for consolidated, simple flows). I am curious what people find the mid tier models useful for.

Wow. On paper this looks like the best Gemini release OAT. They really dialed in the usage and cost issues.

On the AA benchmark it kinda makes Sonnet and Terra look weak. Hopefully that translates to real world usage. Can’t wait to try it out.

I'm very impressed with it as a model for image->html builds. It's the first non-anthropic low-param model that successfully captures complex flows.

Comparisons:

Hydrogen: https://html.non.io/lcars-gemini-4-hydrogen

Sonnet 5.5: https://html.non.io/lcars-sonnet-5.5/

Original designs: https://diffui.ai/app/canvas/5093e689-1e74-4f26-b632-2a4500f...

IMO it sits between sonnet and opus in terms of quality, and is equivalent with gpt sol (for this particular benchmark). Google did a great job with this.

Good they are able to replace Flash. And cool this is available to everyone via search. But I still don’t understand Googles strategy with these new models.

For pro sub, Argon is still very limited and Carbon is only available on Ultra. This is not competitive at all. To say nothing of also being locked into Antigravity.

How do you actually use hydrogen in the app? The only model selection options I see are "auto," "code and analysis Argon 4" which is paid, and 3 thinking levels.

Nice upgrade from 3.8 flash.

My use case benchmarks 37% more expensive per task but 40-60% of the total time per task (median and p90 had the same improvement).

Both models were smart enough to complete all eval tasks, speed was the main thing we were struggling with. Both models on medium reasoning.

Overall feels like a good upgrade.

The orchestrator in Antigravity might be the most important part of this release. I'm excited that this is being built natively into harnesses.

I really hope hydrogen keeps the excellent conversational ability of 3.8 flash. For brainstorming or even decoding the dense output of the powerhouse models, flash was a real delight to use. Its the first non-SOTA model that I would actually go to often over the larger models, it was fast, plenty smart enough, and generally wrote really well. Here's to hoping hydrogen keeps that up

This is a good blog post because of the graphs comparing directly to Terra and Sonnet for both wall-clock time and cost per task. This is the exact information I'm looking for.

My TL;DR is: seems like a better choice than Sonnet in areas outside of coding, and at high reasoning it's smarter than Terra but somewhat more expensive.

Can anyone compare usage allowance on Google subscriptions vs Claude or Codex?

Why all the Ai companies are dropping the names that meant something like flash, mini, pro to these meaningless name. It's very confusing

Google are doing such a terrible job. They aren't allowing Pro accounts access to this in antigravity that they gave to students or via mobile plans elsewhere, because they messed up badly and don't have the compute. They have been absolutely horrible about communicating this and even gaslighting the users, completely nerfing the same models that they do get to use, without telling them that they are doing.

So after being caught up in this, it's left a very bad taste and I'm subscribing elsewhere.

I'm really enjoying all these Gemini releases. I know a lot of people keep saying Google is too far behind in the race and that they dropped the ball to early but I don't feel that way at all. I had both Opus and Fable try to find a discreet bug in my codebase and both models assured me I had nothing to worry about and was probably overthinking. Argon was the only model that got to the bottom of the matter and developed the fix for me. I constantly find the Gemini models perform better in the real world as compared to the other frontier models and I also find they have less of the AI-isms that many of us have now come to associate with ChatGPT and Claude. Gemini feels like you're speaking to a comrade. Claude feels like you're speaking to a friend and it's an important distinction I feel.

Oh hey my google workspace account actually got this. It was on like 3.6 and 3.1 for a long time.

I went to geminiIsland[1] and asked for spongebob's, squidward's, and patrick's houses [1] https://geminisland.raph.plus/

These names are honestly too confusing. Given carbon, hydrogen, and argon I have no clue from the names which is small, medium, and large

Gemini was never my first choice. The only thing built on Google models I use is NotebookLM.

Where is Gemma5?

Where is Gemma5?

Where is Gemma5?

Where is Gemma5?

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The naming of these Gemini 4 models is ridiculous.

In order of sophistication and cost, the models are Hydrogen -> Argon -> Carbon.

What kind of ordering is that?!?

With the introduction of Hydrogen, it's no longer ordered alphabetically. That would be Argon → Carbon → Hydrogen.

And it never was ordered by atomic mass, which is arguably the best ordering if you're going to name your model classes after chemical elements. That would be Hydrogen → Carbon → Argon.

It's also not ordered by prevalence in the universe. That ordering would also be Hydrogen → Carbon → Argon.

It's not ordered by electronegativity, boiling point, melting point, or any other remotely defensible chemical property I can think of.

It's not even ordered by letter count, Scrabble score, or NFPA 704 Flammability Rating, all of which would be Argon → Carbon → Hydrogen.

Surprisingly plain pelicans for a Gemini model, quite a nice illustration of how Hydrogen really is significantly less powerful than Carbon and Argon: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

For comparison here's Argon: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

And Carbon: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

Here's a comparison grid: https://static.simonwillison.net/static/2026/gemini-4-pelica... - note that Carbon and Argon are priced the same, so it's actually quite neat to see the difference in token usage between them (Google say that Argon is more token efficient.)

Their naming scheme seems a bit tough to follow. But it does seem like they finally learned their lesson and announced something at the same time it's actually available!

3.8 Flash pricing will double in January to match 4 Hydrogen pricing

https://aistudio.google.com/docs/pricing#gemini-3.8-flash

When are getting more powerful Gemini 4 Lead, and Gemini 4 Uranium models?

Looks like they are releasing these... periodically!

I get that hydrogen is the smallest element but like it's not exactly that intuitive for everyday people to know which to choose. Whatever happened to big/medium/small

First interaction, me: "Hello how are you"

Gemini: "I am operating normally."

Smooth.

Argon, Carbon, now Hydrogen. If Google keeps climbing the periodic table, the roadmap writes itself: Californium finds gold in your codebase (enterprise only)

So a pretty mediocre model at best on par with the open Chinese models. At least the Chinese models have a coherent naming

The naming of this stuff is so bad. Hydrogen (1) is dumber than Carbon (6), sure. But Carbon (6) is smarter than Argon (18)!

The labs use a pretty clear progression: Luna -> Terra -> Sol -> Astra; Haiku -> Sonnet -> Opus -> Fable/Mythos. Google doesn't make it easy.

The era of "ai le bad" jokes might just be over

Billions of people will now be exposed to a model that crushes sonnet 5.5 on benchmarks (in google ai search suggestions).

I kinda miss dumb ai in a way actually, was a certain charm to it

Hydrogen... the smallest atom that can still call itself an atom... and they've named their model after it?

I do not understand ai marketing.

Next will be gemini 4 cornholio if they keep following this naming

looking as the price, seems like google wants to share the AI bowl with other companies, so generous!

though I suspect they keep the price this high to increase the profit margin for the shortened release cycle (instead of 6 months I think they will release newer checkpoints in 3 months or less from now on).

still, my application now permanently use deepseek models instead. no point using gemini, neglectable real life improvements for extremely higher price.

Pretty big Gemini fan, but my initial results with Hydrogen and Carbon are disappointing.

They are trading improvements on pass@1 pointless benchmarks for worse disasters at p90/99 that you're going to hit every week in agentic workflows (if not daily):

overreach (doing more than asked), overwork (when it should have failed fast), harm (doing the opposite of what was asked), orthogonal work (doing something completely unrelated to what was asked), etc.

Google doesn't seem to be the only lab making this trade...

The set of benchmarks they released are disappointing. 10 mostly random benchmarks. Really?

There was this almost peaceful time few days where antigraivty drop down menu was

argon

flash

opus

sonnet

now its

argon

hydrogen

flash

opus

sonnet

gptoss (i swear ths was removed earlier)

carbon

oh ahd hydrogen has 4th extra thinking.

holy shit just route this shit for me..

E: or not

This service has been disabled in this account for violation of Terms of Service. Please submit an appeal to continue using this product.

Haven't done anything, worked fine before update, now after. And lol where is even appeal form. Right after I said Google One was good value.

Terrible naming convention on the low-end, because what do you do if you make something smaller than Hydrogen next? Gemini 5 Electron?

On the high-end, I feel like there is an implicit promise that if they keep releasing larger models and go past Oganesson (118), they are on the hook for AI-discovering a new stable element, so that is fair at least.

Honestly I cannot keep up with the naming conventions that keep changing every month.

Argon, Carbon, Hydrogen?

Luna, Terra, Sol, Astra, Betelgeuse?

>For everyone: Start using it in the Gemini app model drop down

and then it says for free users there is only "automatic" and you will get Gemini 4 Hydrogen "when it's the appropriate model for the prompt". Yeah sure Google, whatever, I don't care about Gemini models anymore. Too hard to access, constant rugpulls, intransparent pricing, many, MANY outages and in general very unreliable. At this point I just want Google to fail.

Are we sure the guy that creates google naming schemes is not held hostage and those are his desperate attempts to communicate with the outside world in concealed way?

Google team: these names are an embarrassment

The naming scheme alone has no rhyme or reason. Model names should not be a source of cognitive load.

Is this a replacement for Flash-Lite? Because it’s being used to serve answers for Search.

The new naming scheme seems shockingly poor though, “Pro” and “Flash” made intuitive sense to me, and Anthropic and OpenAI kept a sense of scale. Nobody is going to intuitively understand “Oh yes, Hydrogen is smaller than Carbon”, even though it is.

Their super smart recursively improving ASI models didn't tell them this naming is absolutely terrible?

Are we going to talk about naming and confusing ways to access it, or are we going to discuss how capable the model is?

Every single time a Google model comes out, an army of Anthropic shills sidetrack the discussion.

Can we look at what the model does and discuss whether Google is still in the game or not? (naming models and whether you need to access it by clicking a drop-down menu or making a prayer ain't really relevant)

Another day, another nonsensically named google product.

I quit using Gemini models months ago because they are incomprehensible to understand in terms of when to use them and how to navigate the terrible GCP and Gemini UI. It’s a Kafkaesque nightmare.

With all the names for their AI offerings, I need to come up for Oxygen.

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Maybe I'm not on the latest models (I do actually pay the min plan), but just this week I tried Gemini again. It still doesn't even get the current date/time of day correct. If it cant do that, I cant trust any output from it. I have no idea how Google fumbled so badly, but benchmark scores don't mean a thing if you cant even get your LLM to output the current date and time correctly.

You could vibe code a better LLM with Fable than what they have delivered. It is embarassing.

Aren't Google leaders embarrassed that the first thing I think of when I see their models drop is: I will see if I can call it from openrouter?

Why are there 7 different ways to call this model from Google? Which one should I use?

Is no one at the wheel calling the shots at Google and it's a PIP every man for himself? I want to try them out, don't know how.