If it's based on carbon-14 it will lose half its model weights in 5,730 years; if it's based on carbon-12, it's a stable release.
In all seriousness, if Google must continue gambling on pre-train runs, at least have a useful naming scheme. Like the month it was post-trained and the parameter count. At least that’d provide some insight.
Gemini 2T 10/26, bit of a mouthful but is it truly that much worse?
But I come from a latin language background, so maybe I'm a bit biased there.
Size wise Astra is not categorically bigger than Sol, both in absolute terms and the observed size.
The naming makes perfect sense to me, the sorting algorithm is size, both for the names and for the models themselves. Smaller things represent smaller models, and vice versa.
I would need to be a complete moron to argue with this. Humor me, however. My Latin skills end at remembering "Romani Ite Domum" and English is not my first language.
My layman reading of the names: there is one Terra, one Luna and one Sol => "Astra" is singular.
Now that I googled it, I understand that "Astra" literally means the "Stars" category. I would not have thought that they called a single star "Astrum". On the other hand, I am not sure if it means "Galaxy" in modern sense, but we're entering Roman Astronomy territory, where I am even less knowledgeable than in the language.
Sol is a star, so having a dedicated Stars category on the naming scale makes less sense. Treating Astra as Stars set without Sol, the "distance from observer" argument still kind of makes sense.
That is incorrect. "Astra" is Latin for "stars" (plural). The singular would be "astrum".
Luna = Moon
Terra = Earth
Sol = Sun
Astra = GalaxyLeopard (10.5) and Yosemite (10.10) both came with clear version numbers
Model X and Model Y are siblings which do not have a clear hierarchical relationship
Gemini 4 Carbon and Gemini 4 Argon are rather difficult for me to tell at a glance
He's always been deeply unserious.
The pedo-guy comment though I think was him being serious, unfortunately.
Same for Anthropic, consistent model tier naming reused across model generations.
Those are just like i3/i5/i7 or M-series Pro/Max/Ultra.
But Carbon seems to be full replacement of Argon announced two weeks ago, they're same price. So Argon doesn't mean anything, they just picked random element.
They'd be fine except every named model has multiple numbered versions, with no consistent relatioship between cost or capability corresponding to the version numbers going up or down.
O, B, Sc, U, Re?
Ra, Nd?or I'm dumb and its just elements with names starting with A, B, C
I suppose a Fable is seen as larger. But some of them can be quite short, and not generally considered poetry.
Maybe it thought the names are clear and intuitive (for an LLM perhaps).
There are no good elements for D; Dysprosium is the only one, and it's a mouthful. There are no good elements for E; Europium is the only one and would seem political. Is Fluorine their next release? (And then Gallium or Gadolinium?)
After Carbon, they should just update to Gemini 4.1 or 4.5 or whatever, and drop the random unrelated elements.
Its sad watching them try to keep up when they want nothing more than to crumble under the weight of their own bureaucracy, and at this point I'm not sure there's any hope for them.
* 3.5 Flash-Lite
* 3.8 Flash
* 3.1 Pro
* 4 Argon - New
And honestly, the versions are hurting their case. I ask myself “how is the oldest model, the Pro model?”
This kind of bungled naming and versioning is the kind of thing I expect from Microsoft.
I'm fairly confident I can't call Carbon, and I am okay with that.
It is the most awful product experience I’ve had this year. How could they fuck it up this badly?
wow pricing has gone way up
Now, I just go straight to the Hacker News comments. I've given up on trying to figure out how to navigate Google's labyrinth.
Their release notes have become like breakthroughs in graphene. I'll believe it when I see it.
Their go-to-market execution is just so broken.
At the beginning of this whole AI shift, when Google would announce a new model, I would try to get access, even paying for a subscription.
Then I realized it's just not possible.
Google onboarding is the new Gordian knot.
For Google, I think the announcement is the success criteria. And onboarding is somebody else's problem. And the problem is... that somebody doesn't work at Google, or are entirely disempowered.
If, someday, Hacker News comments indicate that a majority of individuals have figured out how to access these newly announced models consistently, I might take my precious personal time to navigate the labyrinth once more.
1. Ultra - The best and the most expensive for showing off and government. 2. Pro - Almost best but substantially cheaper for most productive people. 3. Flash - Workhorse for everyone. 4. Lite - For the unwashed masses and peasants.
There is no need to attach anything to these labels. In fact industry could simply standardize these namings like SEMVER.
There could be an internal representation which could give specific number of the model but these companies should move on to be more like Chrome. No one knows or cares which version of chrome they are on.
For a lot of systems the real underlying version would matter because of reliability. That can be provided to those power users.
honestly, this tier is the 4GB model that ships in chrome and runs locally
Not if you're a linguistic descriptivist.
As an example, Linux distros say, Ubuntu got its project "names" as well as SEMVERs. But people rarely use project names but uses versions.
You tell me, I use "Jammy Jellyfish". I will be like WTF dood. You tell me 22.04 LT (which is one I use), oh yeah, that's a good one.
Same thing here. companies can call whatever SOTA whatever they want. But in the end people will refer to them as just Gemini 4 or Ultr/Pro/Lite however people like to use.
Just leave it to company's discretion. Don't enforce anything. People will figure out how to call it.
---
And wtf, a peaseant?
I use your so-stupidly-called ultra/med/lite but in diff situations, and when I use lite that doesn't mean I am peasant, I am being sensible
Has there ever been a product category where a product release is valuable for a shorter time than with LLMs? Trying to build SOTA models seems like it'd be an exhausting hamster wheel to work on.
Just. Yaknow. 100x the costs, at the least.
To be honest, if I were an LLM provider I would be wiring up my release process to be fully automated so within 10 mins of the last bit of fine-tuning it got released and a blog post posted.
Also the whole "we're only releasing it to cyber defenders first" framing is weird, is any Gemini model an actual cyber risk?
Just because you saw your friend move to a new country for a job doesnt mean you will make the same choices, even if you are similarly qualified.
Seems like Google could do it too.
I suspect they're announcing it for two reasons: to get ahead of all the leaks; and because it's earnings report day.
Especially on their Plus tier for Gemini.
I think it's a fair concern that this might take weeks and trail Fable 5.5.
The Google AI Plus tier does not give better model access than free, it is strictly for usage limits. Same thing as ChatGPT Go (which currently only has access to GPT-5.6 Luna, same as the free tier too.)
[1] For consumers at least. IIRC google business/entreprise accounts have worse model access even in the business/entreprise version of Google AI Pro.
Google has the products, the brand recognition, the hardware, the data and most importantly a billion normies.
Google was always going to win this thing, although I wouldn't discount meta. The only thing that matters is mindshare and Anthropic and OpenAI have largely generated NEGATIVE sentiment, outside some fanboys.
Google and Meta can plop cute products into your daily driver apps and you wont know the difference.
Google’s talent is solid B tier in 2026. Better than IBM but worse than Microsoft and Amazon.
Even if Google had “talent” this talent wouldn’t be able to accomplish anything due to corporate politics.
Anthropics only moat is vendor lock on Claude Code, especially if they cant maintain being the front runner of the frontier model space, this is a really brittle moat. Brittle moats wont attract strong investment at a 1-2T valuation (not to mention all the other fiscal unknowns).
I just want OpenAI and Anthropic to lose because they seem to be the ones going around saying they're going to replace peoples jobs, and usurp the value of human labor.
Id rather Meta and Gemini suceed who will genuinely just integrate it into normal products we already use. Their sales teams are not approaching my boss and telling them they can reduce their payroll burden by spending my paycheck on tokens and firing me.
Coding is going to be one of the smaller pieces of the AI revolution. People on this site are focused on it, but there are 10000x more opportunities outside of coding where Anthropic and OpenAI have zero presence. Anthropic might as well be an IDE company, Is jetbrains worth 2T? to signal that they can be useful in other fields because they know this is an issue.
Outside their most successful products (YouTube, Android, GMail, Chrome, Search), their products are usually worse than their competitors (e.g. GMeet vs Zoom)
> the brand recognition
Of not maintaining/outright abandoning their products, and making Search worse over the years?
> most importantly a billion normies
ChatGPT has 1.2B weekly active users, all the normies know what ChatGPT is but don't know about Gemini (outside the "AI Mode" stuff)
They have many successful products. Most have only 1-2.
Youtube, Android, Chrome, Search, Photos, Workspaces, Cloud, Fitbit, Pixel Phones, Waymo not to mention dozens of open source projects.
> Of not maintaining/outright abandoning their products, and making Search worse over the years?
You just said their products are terrible. They do shut the products that do not meet the bar. That is good thing.
> ChatGPT has 1.2B weekly active users, all the normies know what ChatGPT is but don't know about Gemini (outside the "AI Mod
No one needs to know what Gemini are. If they have used search they have used it.
I dunno if that's a great example - I'm sure Zoom has more awareness in the zeitgeist, but from my standpoint it's an app most well-known for security problems and abusing OS conventions, while Google Meet just quietly and simply works whenever I want to call my mom.
[0] Practical Data (https://practicaldata.dev/ / https://chromewebstore.google.com/detail/practical-data/oeoo...)
https://files.catbox.moe/2aqfk7.webp
(Edit: For some reason the previous jpeg link: https://files.catbox.moe/yjqa0a.jpeg wasn't working and catbox.moe was just downloading 4kb white screen so I converted the image to webp and reuploaded it on catbox)
Anyway, Imgur creates so many problems that it should be retired.
It's possible Fable is better, but since it word salads more quickly, it's hard to tell.
Opus 5.5 in comparison is a bit more verbose and appears to settle on evaluations before the depth reached by Fable on very complex stuff, but is still vastly capable and I can read its output without wishing it had a physical form I could punch in the face.
I generally use Fable for high-level blueprinting, architecture, and technical planning, and I tell it to write most of its documentation in a way Opus 5.5 will understand and maximally benefit from; with the added prompt for Opus to concede when a task would be better off to bring Fable back in. I've had ZERO problems.
On the other hand I'm a strong protan colorblind guy (red doesn't register to me very well at all).
https://file.garden/auI5UdLIWwZSu5X8/pilestone.png - result of said simulation.
Also, I'm curious if you just asked an AI to _OCR the original image+update it_, or if you used a different process?
> "Edit this image to color code the benchmarks scores using a gradient scheme that is immediately obvious"
It's worth trying if you have easy access to it (we use Cursor at work, so it was just a matter of picking a different model for me). Don't know if I'd go out of my way to get a Google AI subscription for it, but if Carbon ends up meeting these expectations, then it may be worth doing so.
It's best to start with a relatively clean GEMINI.md too. Many configs optimized for Claude doesn't work well because Argon didn't have those same failure modes.
Top is Opus 5.5, followed by Fable.
- Corrupted/dropped Gemini thought_signature (reasoning_details) in tool loops
- Blinded model.api.id = "contestant" bypasses gemini.txt and serves Claude's prompt (default.txt)
- Anthropic-only prompt caching
Prompt was:
> I read on hacker news the following, which does not match my expectations. Check if something in the harness or bench is hurting gemini perf.
followed by your post.
> anthropic only prompt caching
Anthropic has custom prompt cache requirements, but we've verified all providers are working well.
> Blinded model.api.id = "contestant" bypasses gemini.txt and serves Claude's prompt (default.txt)
This is wrong. We're serving default.txt which is opencode's default prompt. We are not serving a custom prompt for any model, including Gemini.
> Corrupted/dropped Gemini thought_signature (reasoning_details) in tool loops
We blind the reasoning details in the frontend because this would leak information. Some models summarize thinking while others provide raw thinking. I'll check if we're corrupting the thought signature that's actually sent to the backend.
So far this sort of looks like an example of Gemini being bad. Was this Argon?
Their agents leaderboard is literally just randomizing the agent and looking at metadata like tool call errors. In my opinion, it's poor quality data in high volume.
Their web dev leaderboard is in cloud containers, most people don't run agents like that.
I ran a statistical test on our data. Deepseek vs. Argon. Posterior probability DeepSeek 4.1 Flash is stronger: 99.1%.
It's possible, but we are getting real prompts from people on real projects, and the instructions about the battle are pretty minimal.
Argon in low and medium mode had higher quality results than it did when running in high mode, almost every time. My tasks involved the agent finding some details in a raster image and then mark it up with predictions about what it found.
Argon on high would do the work, and then a whole bunch of other stuff i did not ask for. All that extra broke everything else downstream from the analysis.
However, doing the same work with Argon in low effort was on par with results from Haiku 5.5 (xhigh) and GPT-6.1-Terra (medium). So, Argon low works better than Argon high, but for my tasks -- a very weak model relative to how google positions it.
I'm ready for Geimini Unobtanium!
what does "local" coding agents mean? Surely you're not hosting it..
But yes, Opus is a tier above Wonder and Argon with very high confidence.
It's sad to see Carbon releasing at the same pricing because that implies Google is planning to do the thing everyone is doing: release promising model for subjective preference, RL-maxx a V2, replace promising V1 with V2 because it benchmarks better
Muse did it, Kimi did it, Deepseek did it, Tencent did it. No one seems to care abojt subjective preference anymore.
This might be the first comment I've ever seen saying something nice about the model.
Having said that, I don't see people excited about using Argon so far, so that might be why Google is announcing this to hype Gemini up a bit.
For me it also works the opposite way, when it actually comes out eventually it’ll already be old news.
Anthropic has been doing this with Mythos for quite some time...
I don't understand why HN is so surprised to have an announcement for model existence and a follow-up announcement for model availability. It's really not that unusual, as you say Anthropic has done the same, probably others too (though I can't remember)
it actually did really well.
But it still annoys me: I told it to _tell_ me something, and instead it _implemented_ the something. The previous models were way too eager to just jump in and do and this one seems no different. But the optimization it identified was both really solid and just a good engineering choice, and better than what Opus had been suggesting.
It also gave pretty good feedback on a bit of writing.
for whom?
Consequently, I have zero intention of renewing my Gemini subscription. What a dumb business choice they made.
Updates to your Google AI Plus plan
We wanted to let you know about changes to the models that you can access with your Google AI Plus plan.
Starting on 1 3 N o v e m b e r 2 0 2 6 , the ability to select Pro models in both the Gemini app and AI Mode in Google Search will only be available to Google AI Pro subscribers and above. You'll still have access to our latest Flash-Lite model and Flash, built for speed and intelligence. Your previous chats using the Pro model can be continued with a different model.
To learn more about these changes, you can visit our Help Centre article for additional details. You can manage or cancel your subscription at any time.
Thank you for being a Google AI Plus subscriber.
It has a seperate weekly limit that is very low. Maybe it can be pulled off that usage tier and just regular usage since Carbon is being released?
But it just all seems so tedious when codex and Claude are so painless.
Unfortunately their plan structure is on par with their model naming.
The plans that allow for own domain and the plans that allow for sane AI use are mutually exclusive
I bet I am not alone, either.
If you are talking about free versions, OpenAI and Anthropic also have a difference between free models and models available to 25$-tier plans.
Thanks for sharing your experience though, it's a more substantive piece of information than who I was replying to.
Doing this two hours before today's earnings report.
It's probably going to be a terrible earnings call in terms of capital expenditure, cash flow and new borrowing.
Now you know why they released it just before the earnings call.... :-D
This is probably the single most important thing to make frontier models usable right now, so I'm happy there seems to be some progress. This was the previous Gemini's biggest problem IMO
"We patched every vulnerability we knew". Meanwhile, prompt-injecting Argon (or any other model) is still trivial, and Carbon won't be an exception. Because the attacker is not limited to things Google has evaluated.
AI shops are blind to anything that's not a metric.