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.

Thanks any Googlers who had a hand in this

So this is an actual change of pace

Alibaba is forced to do this stuff: https://www.tomshardware.com/tech-industry/semiconductors/al...

Meanwhile Deepseek: https://news.ycombinator.com/item?id=45643163#45652636

Carbon is the next version of Argon. But Hydrogen is supposed to coexist with Carbon. Also no idea where the scheme is coming from, what elements should we expect.

Wild guess: maybe they are going with how abundant the elements are to scale the models. I'm no chemist so I don't know reliably how the relative abundance of Argon and Carbon works out, but Hydrogen is "well-known" as the most abundant element in the universe, so maybe that's why its the base model. But, this is essentially a trend of one, so not a trend at all, unless someone can verify it still works for Argon and Carbon.

Intuitively, Argon is 4 Pro, Carbon is 4.1 Pro, and Hydrogen is 4.1 Flash (slightly better than Argon according to benchmarks).

The sol/terra/astra, haiku/sonnet/opus clicked without needing to be explained

A fable is a tame mythos.

My only real complaint with Google is they regularly change names for seemingly no reason. I'm still out here saying "Gemini" when I type "agy" and I don't bother saying "Anti gravity" because I assume that name won't exist in a year or two.

I think OpenAI's names are clearest. In most people's understanding, moon < Earth < sun < stars.

• Cupcake (Android 1.5)

• Donut (Android 1.6)

• Eclair (Android 2.0–2.1)

• Froyo (Android 2.2)

• Gingerbread (Android 2.3)

• Honeycomb (Android 3.0–3.2)

• Ice Cream Sandwich (Android 4.0)

• Jelly Bean (Android 4.1–4.3)

• KitKat (Android 4.4)

• Lollipop (Android 5.0–5.1)

• Marshmallow (Android 6.0)

• Nougat (Android 7.0–7.1)

• Oreo (Android 8.0–8.1)

• Pie (Android 9)

Using constantly changing names for tiers is a bad idea. Unless the tiers are pre-existing (bronze, silver, gold).

Fables are short.

They should have used "saga" / "epic" / "cycle" / "series" / "universe".

They botched it.

A haiku is a short poem. A sonnet is a longer work. An opus is a great work. Mythos is a connected body of works.

As with Open AI, Luna --> Terra --> Sol --> Astra from smallest to largest. Very straightforward.

With Google it's totally incoherent. Hydrogen --> Argon --> Carbon!?

Hydrogen is small, but it's the most abundant element in the universe by far. Argon is >3x larger than carbon by molecular mass, though carbon is more abundant. It's impossible to determine what's supposed to be smaller and what's supposed to be larger.

If Google was going to go with elements, it should have been an absolute no-brainer to link size of of the element to the size of the model eg. Hydrogen/carbon/argon, but no, Google screws up the naming like they _always_ do. Hell, use the noble gases for christ sake. Helium/neon/argon/krypton/xeon would have been great, not perfect mind you, because a lot of people might not remember the ordering of those elements, but at least it would be consistent and make sense.

Letters of the alphabet: Also makes no sense. There was a theory that Argon = A, that there was an unreleased B model (Bismuth or Barium or something), Carbon = C, etc. (Similar to Intel's MMORPG-inspired Alchemist --> Battlemage --> Celestial...) Hydrogen broke this notion.

It's just completely incoherent.

Also, the biggest being Astra is a bit confusing. Sol is also a star.

Furthermore, unless you know they’re supposed to be ordered by size you can’t know which is best.

I don't think these are as difficult as you're making them sound? I think the majority of people who will care what model they're using will know "lunar", "terrestrial", "solar", "astronomy" etc?

Ar - C - H - ?

Hydrogen: this thing floats. Density less than air.

Argon: does not float. Density more than air.

Carbon: this thing is a solid, whichever allotrope you pick. It’s solidly heavier.

See, so easy! /s

Google's is just random.

Fable is essentially Mythos but with guard rails added.

Small/medium/large/etc. has the most easily deducible ordering, but it's not great from a marketing perspective and also has headroom issues unless you're ok with names like gpt-8-xxxxl.

OpenAI's naming is probably the best. The ordering is easily deducible and there's plenty of headroom in both directions. Tons of cool sci-fi sounding names still on the table, and it also comes with the implication that they're approaching a singularity.

I don't know what Google is doing. It's kind of impressive to have an inconsistent ordering after only three names.

Google, though, really has broken new ground in incoherence. WTF.

It doesn't do anything! It's inert!

Which will be launched after GPT 7 Uranus.

Carbon (6) > Hydrogen (1) > Argon (18).

Double nonsense because it appears Hydrogen is in fact a smaller model than Argon, in which case this should obviously be released as "Gemini 4.1 Hydrogen" or something.

What they probably should've done if they really wanted to use elements is to do noble gases, and start these first three models in the middle (to leave room for bigger/smaller models in the future).

So you'd have:

Argon => Argon (18)

Hydrogen => Krypton (36)

Carbon => Xenon (54)

Not exactly because as noted it appears hydrogen is in fact the smaller model, but then this should be (again) 4.1 or something.

And they'd leave space for a truly massive model if needed (Radon) and two slots for much smaller models, with Helium (2) presumably being a model that could be run on basically any consumer device.

No matter what you do you can't go wrong if you spin it right!

"Claude and Codex have cool names, they are more successful than us, so therefore if we give gemini cool names we'll be successful too"

-marketing drone, probably

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??

It's cheaper than the last Pro models.

So I'm a little spooked by this; if you don't mind, can you be specific about exactly what you did that seems to have preceded this?

The thing that preceded this was an upgrade to ultra today from pro, and a call of agy cli from within opencode (explicitly not using it via some login/oauth, but just calling `agp -p "prompt"`, which had been working for months). Right now it seems that every agy chat works for 1-3 messages, then gives a suspension error.

If this gets resolved via live/email support timely I would be fine. But I am spooked by the appeal form/process that is completely opaque via a google form(!) and seemingly can can take days: https://docs.google.com/forms/d/e/1FAIpQLScOJWibQ_-hYuVv63kJ...

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

For more egregious violations like the kid uploading naked pictures of himself, I don't know.

On the other hand, I'm very glad they have separate quotas.

Otherwise you can use agy on the Cosyra mobile app, its far better. I'm not going to claim its better than the Claude app, but its certainly better than the Gemini RC.

I've read this same comment every time a new Luna came out, and the difference between free GPT (Luna) and paid (Sol and Astra) is still outrageous for general use.

Right now DeepSeek Flash 4.1 Flash has a 64% win rate against GPT 6.1 Sol. Small data still, but it has 33 wins vs. 18 losses, which is confidence interval of 52% - 78% win rate. https://agentduel.com/leaderboard/models/deepseek/deepseek-v...

The free default was 3.5 flash lite.

Opus-tier on open models and local hardware.

The thing that is being subsidized is the TRAINING costs, and that is because they aren’t selling enough tokens yet to pay for the training costs. This is just like most other growth businesses, though, and if enough people use enough inference, it can be self sustaining.

If the subscriptions (of all of the big companies - unlikely?) give a poor amount of value in the future, will move to trusted/open router and use a harness that uses the latest cheap good models for most things, more expensive models as orchestrators.

Already there are non-SOTA models that should be sufficient for most non-coding tasks, and soon for coding, also.

The future is bright, in that respect, without subsidizing the ridiculous IPOs.

But for enterprises, who have to pay API costs with no discounts, no way.

1) There was a false narrative called tokenmaxxing whereby one is more productive by spending more tokens

2) This narrative was fueled by discount prices on tokens (which still happens to this day on subscriptions)

3) There is a point where we collectively realize that tokenmaxxing was a state of mind that is not rational for either the consumer or provider

4) We will then pay API prices because LLMs are obviously amazing but no one will offer subscriptions

5) API costs of Opus 5.5 and Fable tier become uneconomical

6) That leaves us in Sonnet/Haiku tier

The analogy made sense to me: Tokenmaxxing policies were the result of an irrational drive by execs who just craved an, ahem, explosion of metrics due to the excitement over new technology. Now that cost sensitivities are setting in, there’s a growing sense of unease that maybe they were in an altered state when they created the mess and now that the excitement has passed they have to clean it up.

Or is it just a throwaway phrase that makes no sense?

Haiku, sonnet, opus.. is ok

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

but this?

Then they needed a flash model so they picked the lightest element.

Argon internally was called Barium (Argon was a different model) so the models were originally named in alphabetical order. Then they change their mind and decided to call the lightweight model following the atomic weight so Hydrogen after they have released (A)rgon and (C)arbon. I imagine that this lightweight model is the original Argon.

And "Hydrogen surpasses Argon on the Artificial Analysis Intelligence Index at its default high thinking level"

Given it's twice the price of 3.8 Flash I hope they would find room for another cheaper tier, but the Hydrogen name suggests not.

I'm glad Google are coming out with some decent models but it's a slightly confusing line up.

A = argon for initial release B was skipped because you can't name a product boron C = carbon D = ??????

They might be going for atomic weight, but the average person couldn't say whether argon or carbon was heavier.

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

It would (rightfully) be catastrophic for wells fargo. And great for the industry. If your security model relies on children not having access to things state actors can leverage, your in for a rude awakening.

Hence why they are gating model releases. Even Chinese models are doing this as Kimi K3 shipped with a lobotomized cyber sec ability. The major labs all have invite only cyber models too.

“Security by availability” doesn’t seem really different to me from “security by obscurity” which has already been proven to be complete bullshit.

I wonder now that Terra-6 is out how it would compare to Sol-6. (Which was replaced a week latter by sol-6.1 after chat got dropped opus 5.5 to incredible fanfare then sonnet 5.5 that radically upped the medium model ability).

> 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.

And then the real problem number 1. The answer is "Left - each figure contains an even number of arrow heads. Right - each figure contains an odd number of arrow heads"... but on the right I can clearly see that the three eggs across the top have an even number of arrowheads.

I won't share the solution (you have to keep some mystery in the world), but I showed this a year ago at a high-school reunion and five people independently found the same solution, so it should be well-posed.

If the highest tier model makes even one or two fewer mistakes that require human intervantion, that almost makes it a no-brainer choice for production.

At least for my use case of evaluations of a set of features.

I'm building stuff at home with my work focused on managing infra. If anyone wants to sponsor a SOTA model subscription I will check it out. Until then I'll see how flexible a Strix Halo setup and my homelab can be.

Even if the difference is a single extra error caught early, that can end up saving me hours of work later.

I think many people still expect their tasks to need something more fancy, but could do with a reset of expectations and try to go much lower.

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.

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.

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.

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.

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.

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

Where is Gemma5?

Where is Gemma5?

Where is Gemma5?

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.

> An internal document shows that Google has tested a series of Gemini 4 models, internally named Argon, Barium, and Carbon.

Then I suppose they tacked on Hydrogen since it's supposed to be a "light" model and hydrogen is the lightest element. I agree that it's super confusing though.

[0] https://www.businessinsider.com/google-employees-test-new-ge...

Or maybe they just pick them out of a hat.

alphabetical skipping the weird names

next would be iron krypton and lithium

There is no hint of what each one does. I get that these were internal code names, fine, but to everyone outside Google it's not helpful to have these meaningless names.

ChatGPT and Claude aren't much better - there is still quite a lot of assumed knowledge there assuming you know what e.g. a sonnet is and what an opus is - but at least if you squint there is something there.

Google's names just seem to be randomly generated.

Maybe they were worried that the 3.1 Pro model being around for so lunch ruined the brand? But 3.8 Flash was pretty decent I thought so it's not like "flash" was burnt. I dunno.

Also totally agree. What a bad way to name models...

At this point even using Starbucks sizes would be better.

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.)

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

Gemini: "I am operating normally."

Smooth.

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

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

I do not understand ai marketing.

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.

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?

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.

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.

Argon, Carbon, Hydrogen?

Luna, Terra, Sol, Astra, Betelgeuse?

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.

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

Having said this, I don't defend this trend at all and also think a model picker ought to be good enough with at most three tiers rather than five or so with sometimes like five effort levels each for 25 combos. I refuse to believe we need this granularity.

Anthropic - Literary scale.

Google - random elements with no clear relation to model value/capacity.

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.

I have found it a good subagent workhorse for code implementation, with some higher level model doing the spec and review.

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)

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.

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

What is your prompt?

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.

So which one of these six options is the one I should use?

You know how Claude Code is like a little program that your computer can run which lets you talk to Claude? Well Gemini is actually really similar! If that's more your speed, you should use Antigravity.

But if all of this is feeling really overwhelming and you just want something simple, I would recommend just Googling it! Hydrogen will be the one generating the response :)

AI studio if you want to just try it out for some code things (think of it as a web IDE)

API if you want it to use it as an API.

For business if you are an enterprise.

Antigravity

Or just you know - just go to Google.com and search for something. It's really not hard.

This instapost "wah I don't know how to use it wah" from anyone as soon as Google release a model is getting tiring - change the record please.