Gemini 4 Argon

blog.google

802 pointsbradleyg223534 comments

See also: Gemini 4 Argon (High): Intelligence, Performance and Price Analysis - https://news.ycombinator.com/item?id=49914236

Open articleView on HN

Ten days ago I had an experience with Gemini 3.8 flash that made me wonder if I was being routed to a different model under test. I was trying to use rocm with llama.cpp on my 128gb Strix Halo but could only get it to run Vulkan. I pasted the error message into agy and it proceeded to attach GDB to my GPU driver, reverse-engineer the kernel queue ioctl interface, and author an LD_PRELOAD C shim to get ROCm llama.cpp working on my Strix Halo. My jaw was hanging open the whole time.

3.8 Flash is just quite good, and so is the Antigravity harness.

I use a mix of Fable 5.1, Opus 5.5, and Gemini 3.8 Flash and Gemini holds it's own. Especially in writing, frontend, and sysadmin work. agy for configuring a NixOS system has been truly incredible.

Even if agy was the best (it's not, and is missing basic features) you wouldn't rather have a choice?

I cancelled Ultra because they forced me into their harness like I should adapt to them, rather than the other way around.

What basic features are missing from agy? I've been using it and cli-cc + web-cc for months (among a few other random harnesses to test here and there) and they all seem roughly comparable to me.

I actually just cancelled Ultra also because I couldn't subscribe to a YouTube Family plan while I had it active (Google... :[) but trying to use Codex as a replacement while I testdrive Astra makes me yearn for agy again.

I use a variety of models for various subagents. I don't want to change my harness every time I change models.

I have used it for little more than 6 hours or so in total but I'm pretty sure it doesn't have compaction?

Does it have /goal feature similar to Codex?

Can confirm, I was doing a routine internet search thing for a curiosity 3 days ago (about the only thing I used Gemini for) and was surprised by how suddenly thorough and quality the response seemed, almost overnight.

Gemini is honestly amazing sometimes. If they didn't force you to use a terrible harness, charge too much for way too little, and generally act like customers are a giant problem to be avoided I'm sure Google could take over the AI market.

Please tell me you published your findings even as an issue on the llama.cpp GitHub

Why? Anyone can run that prompt.

Not everybody has access to AI. More than that, every prompt uses insane amounts of natural resources. So why not share it.

why reinvent the wheel and spend tokens for a problem that has already been solved?

Spoiler alert: the problem didn't actually get fixed despite the jaw on the floor.

I had a similar but less impressive experience recently with Muse Spark 1.3.

Asked pi agent it to identify the main hero sprite size of game I was running. It had a ton of shader effects so it was hard to determine.

It used some cli tools to identify that it was a game made with Godot, decompiled the executable but data was encrypted, broke the encryption after writing a brute force tool to test keys extracted from the exe, then proceeded to extract the game gd scripts and assets, only to answer the question of the sprite size.

Can confirm - I am HEAVY claude user, but always like to check with AGY and CODEX in between. AGY with Gemini 3.8 flash cooked last couple of times and CODEX is basically out of the mix for me

My experience with Gemini 3.8 Flash has been awful; it gives me the most hallucinations out of the major models. I'm not using it for coding, but general research on different topics.

For getting redroid running on my Linux system, 3.8 Flash decided to binary patch a .so file instead of getting the AOSP source code and patch/build it properly.

And I saw it do this twice, once for Android 14 and once for Android 16.

I think this is just within 3.8 flash's capabilities.

The important take away here: the leapfrogging we’ve seen this year doesn’t seem to be a temporary thing. The famous theory of Dario Amodei was that AI was this winner-takes-all field where the first team to get a head start would never cede ground back. The term he liked to use was, “concentrating”. This is yet another datapoint that he was wrong about that. AI seems more distributed amongst neoclouds and traditional hyperscalers, FAANG and startups, GPUs and ASICs than it did this time a year ago.

Nobody has a moat.

> The famous theory of Dario Amodei was that AI was this winner-takes-all field where the first team to get a head start would never cede ground back.

This is the kind of story that you tell to investors to justify the huge amount of cash burn. :-)

I'm not sure it's wrong. This all feels a bit dotcommy to me.

I think many/most of the players will crash and burn, and the ones that are left will divide the world.

I believe you're right I'm not sure why you're being downvoted -- with the exception that this isn't a small thing that's happening. This is the biggest thing to happen since the industrial revolution and will have a much bigger impact on everyone in due time so although many companies will go bust -- many more will be created. Also the amount of compute resources I think over time will be lowered once we find ways of emulating LLMs without needing the huge GPUs to drive them.

I guess if one of them hits singularity, it could in theory just wipe out all the rest, seeing how they keep escaping and hacking into other systems :)

And before him, Altman was explaining very calmly that no company could ever compete with OpenAI.

> Nobody has a moat except nvidia

For now, for cloud training. but for consumers, nvidia vs amd reasonably close - the moat there is thin and shrinking. I suspect AMD will surprise us. nvidia has no motes in china, which may be a new source of (gpu) chip design. Huawei's Ascend 910C is about a generation behind... again: for now.

point is: moats dry up. I see nvidia's shrinking as a real possibility.

China will always be generations behind until they crack domestic EUV

I think some in the AI industry drank their own Kool-Aid. They believed that if they had the best model and the most compute, they could tell the model, "Make a better model." And it would, and the next one could make its replacement, and so on.

So far, that's not exactly how it's played out. Humans are still necessary for the leaps in capability or efficiency. A model can grind on a problem to eke out the most performance, and models can synthesize data and iterate on various techniques to find the optimal combination. But, seems like humans still have to provide the real thinking, and the talent and drive for doing that is not concentrated in one company or city or even one country. And, (surprisingly) a lot of the people involved are in it for advancing the field more than making another billion dollars, so they're publishing their research.

So, yeah, the moat isn't deep. Even the compute moat, that OpenAI, Musk, and a bunch of other also-rans (like Oracle) bet the farm on, isn't really panning out. The Chinese makers just spent their effort on making models vastly more efficient, since they couldn't do anything about having an order of magnitude less compute available.

I'm not necessarily defending this obvious marketing speak but maybe the "starting point" was wider than assumed. So far, nobody has caught up to US and Chinese labs for example despite lots of funding in Europe. This is also despite abundant in-depth research papers being published alongside open source code and weights by some Chinese labs

I feel his theory depends on the premise that access to pure compute would the be the determining factor of success. Not the case

The US companies still have trillion dollar valuations like there is a monopoly. There just isn't one. They are all within a few percent of each other on the benchmarks.

The slightly lower Chinese open models are good enough for almost everything, too, and much cheaper. Like with humans there is plenty of employment for people with below genius level IQ's.

> Like with humans there is plenty of employment for people with below genius level IQ's.

Not if the genius level IQs take the market share.

Is there a dividing line between good enough and best in class capabilities? It's blurry from where I stand. Will model makers cede ground or is there a market making moment up for grabs (singularity)?

It's even worse, we are crossing over into the realm of religion. The article against GML 5.3 is the equivalent of a Papal excommunication.

which article? have seen this one

---

maybe it's this Anthropic post on GLM?

https://www.anthropic.com/research/glm-5-3-and-the-spread-of...

[delayed]

> Nobody has a moat.

Custom hardware, data centers, huge cash reserves, deep/broad talent pool, and non-AI customer base are all huge advantages if not moats.

Google, Microsoft, or Amazon are more likely to be the AI leaders than OpenAI or Anthropic.

I have never understood the whole "this is a winner take all game" mentality - the sheer size of the pie is so great that from a purely rational standpoint companies should just be trying to productively get a slice of it and be profitable. winner-take-all is just greed/capitalism run amok, where it is not enough to be profitable, you have to own the entire market (and presumably extract rents)

I think that scenario only naively made sense if technical knowledge was entirely proprietary and talent was guarded with severe non-competes and NDAs

And Chinese labs openly publishing so much of their methodology destroyed any hope, which was inevitable

Seems like learning rate velocty may be the ultimate moat

Google has TPUs, a frontier model, a completely separate and lucrative revenue stream they can call on at will, and teams working on multiple different language modeling strategies simultaneously. Did I mention the vast and ominous data centers that already serve a significant fraction of the internet? If that ain't a moat, then what exactly is a moat?

> We’ll continue to gather feedback from early testers as we iterate on guardrails before making Argon available to developers, enterprises, and consumers as soon as possible.

Gemini not beating the "can't release a model" allegations

When I said I was tired of Google launching waitlists I didn't think they would respond by simply not having a waitlist.

i know this is like "hey guys we got such a cool thing at home ,its rad and uhm we playing with it with our friends"

ok bro thx

My Gemini app (updated today) and https://gemini.google.com/ has _3.6_ as the latest selectable model, as a paying Pro user in the US. How is that even possible? Gemini 3.7 was released in August, 3.8 early September. What is going on over there?

just Google being whatever the fuck it's been for the past 15 years.

they moved it from the place you'd expect to ai.studio

I was reading the announcement and wondering the same. And don't forget, still with 3.1 Pro as the frontier model.

They're just following the current AI marketing playbook. "Our new model is simply too dangerous to release to the public right away" is now standard practice.

They even gave their model a random nonsensical name suffix simply because OpenAI is now doing it, too. Monkey see, monkey do.

I'm still at a loss as to what argon has to do with anything. Say what you will about Luna-Terra-Sol-Astra, or Haiku-Sonnet-Opus, they make sense. I don't see how Google can make sense of argon; it's in a fairly strange place in the periodic table...

> Argon agents are working on migrating C/C++ codebases to Rust across Google

Man, I remember back in the days when the cppnext team was refusing to even consider Rust, instead looking at absurd stuff like Carbon and Swift (!), even though half of the engineering staff already knew where this was headed. I hope they got a few good promos out of the delays at least.

Heh, I use my clankers to rewrite Rust in C

Not many people can hold grudges as strong as principal engineers

I wonder if this means Carbon is DOA.

I was excited to see what it would be. But I don't think I can argue that it makes as much sense anymore.

Carbon was clearly DOA the moment it was announced, IMHO. It looked cool but it served none but Google, and now with LLMs you have a massive incentive not to use a niche or new language due to how better LLMs get the bigger the corpus is

The only somewhat realistic proposal in this space is Herb Sutter's cpp2, which is arguably a massive improvement and I'm puzzled why nobody in the standard thought to give it a spin, there's just to much cruft they'll never be able to get rid of unless they make an alternate yet backward compatible syntax with C++ that changes the defaults from "random 80s nonsense" to something better

Version 0.0.0.0 after 4 years. Their goal of "full interop with C++ while being a completely new language without any of the flaws of C++" is plain absurd.

It's DOA because Google doesn't have any idea of what Carbon should be, and to be completely honest, at least 80% of what they currently use C++ for should be rewritten Go, you know, that language developed specifically because of the issues with C++ by teams within Google.

What exactly makes Carbon absurd?

The fact that it will never exist.

rust's existence?

There is 0 practicality in inventing an entirely new coding language that only one company uses, and you have to teach it to thousands of new engineers. Rust exists and fits the job totally fine and is used in more places and has actual support outside of a single entity (i.e you can actually hire people that feasibly know the language).

It was clearly done because some PL guys at google really wanted to make a new cool language and Google was the perfect place to incubate it without it getting axed. Probably got a couple of promos out of it too. This is clearly not the best use of time or money, but I guess if you're google you have so much of both it probably doesn't really make a dent, and you can keep a few very smart people happy with shiny new projects.

Also, LLMs being used for a large portion of coding nowadays sort of remove the need for these types of languages, IMO. They make less "silly" bugs (both logical and structural) that languages like this are meant to catch, and they are much better at languages that are better represented in the training corpus. This somewhat obviates the need for very niche "type/dummy-safe" languages like carbon (and even rust/zig, imo). So even if you did want to use Carbon, you'd likely have to bootstrap a decent amount of your own "good" carbon code to post train an LLM, and even then, it likely won't have that big of a gain vs just having an LLM write C++ or even Rust. If you are a company that still reviews code, you should just have an LLM code in a language most people can understand anyway to make verifiability tractable.

Hmm, I don't disagree with you that LLM's remove the need for type-safe languages, but as the blog mentioned, Google is porting their C++/C code to rust. Does this mean the port is waste of time and that they should just rely on the LLM's to catch memory errors?

I wouldn't call it absurd, but very questionable at least. Most companies are not going to even consider throwing money at this adventure.

I’m not op. But I think it’s not Carbon itself that is absurd.

It’s absurd to think that Carbon is the solution to memory safety when rust exists and Carbon’s memory safety story is basically “TBD”.

A RewriteInRustBench would be unironically useful at this point since all the main agents can write it reasonably well despite its relative scarcity in the input data.

I wouldn't be surprised if we're already at the point of more LLM-written Rust than hand-written. Models training off models

> Large Scale Codebase Migrations and Optimizations: Argon agents are working on migrating C/C++ codebases to Rust across Google—scaling from tens of thousands of lines in core libraries like re2, libgav1 up to 800K+ lines for the Fuchsia OS Zircon kernel.

To me this is way more significant than other random c++-to-rust-AI-rewrite. If they can pull it off on core C++ libraries en masse, I don't know if C++ will still be relevant in a few years.

I look forward to a post from google on this effort.

"I don't know if C++ will still be relevant in a few years."

The standards body members are still fighting about whether memory safety is important enough to change the language for, so, I would guess the answer is "no".

> taking careful precautions against feeding the findings back into training so as to not risk shaping Argon’s reasoning to evade our monitoring. We strongly encourage the rest of the industry to preserve reasoning transparency in these pivotal moments of increased capabilities while navigating alignment risks, so that model thoughts remain helpful in identifying and diagnosing misalignment.

This is good, but they're the slow mover due to this exact thing.

Google is getting punished for not letting the models enter an echo chamber and go faster than humanly possible.

Mmh ok. How much theoretical speed or 'intelligence' gain is realized by allowing reasoning to occur in some inscrutable intermediate representation? Has this been actually tested, how much is it slowing them down, and compared to whom exactly?

OpenAI is the company that originally proposed and popularized chain-of-thought monitoring: https://openai.com/index/chain-of-thought-monitoring/

So no, Google is not being punished, nor are they the people behind this technique.

I dont get it, why even make this announcement, nothing's available and only one real benchmark for comparison?

Only theory is team wanted this out before perf/promo reviews to kick it over the line and then its not their problem

promo already happened; perf is about 6 weeks away.

OpenAI released two model updates in the past week. 6 weeks from now is an eternity

At this point I just think they are benchmaxxing and all talk and no action. I pay for AI plus because I wanted more storage, and when I go to gemini.google.com the most recent model I can use is 3.6-flash-lite. Two revisions have been released since then and they still can't put these things in the hands of customers. Why is it that other providers can get the models into the hands of customers right away? Google is meant to be the bigger tech company in the world.

I don't _want_ to use aistudio. The UX is confusing and I don't really know where it fits. Yet I can open codex or claude code apps or CLI and get real work done today with the latest models (even on the cheapest plans).

Argon will launch at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off input token price. Wow

5x cheaper than Astra for input and output, 10x cheaper for cached input.

watch it somehow use 20x more tokens tho

Google model really like reasoning a lot

It's exact same price as Sol 6.1 announced yesterday.

> After the introductory period expires, the price of $4 per 1M input tokens and $20 per 1M output tokens will apply.

> Quantum algorithmic optimization: Argon is helping our quantum computing researchers optimize the spacetime resources (qubits × gates) of subroutines that bottleneck important applications. In one example, it beat the published baseline by 40% in a matter of minutes.

Amazing breakthrough! So useful in day to day life, glad they put this as the first bullet of how it is making changes at Google.

Interesting to see a mention of Fuchsia on a big Google announcement. Is the project still truly alive? Are the ambitions still as grand? Is the team as stacked as it used to be?

Also, a link to the rust root of Zircon in case anyone else was interested: https://fuchsia.googlesource.com/fuchsia/+/refs/heads/main/z...

It obviously is pretty low key on the public relations front, but it's also very active as a project and I think it would be weird to look at their commit rate and conclude that the project is dead. If Fuchsia is dead then 99% of major open source projects are dead by the same standards.

Had the same thought. On the wikipedia, it only mentions Fuschia used on the Google Nest Hub, which probably means it's used on a decent number of devices, but would think it was such a great OS, they would have used it for something like the upcoming GoogleBook.

My girlfriend, you wouldn't have met her, she lives in Canada, has seen it and she thinks Gemini 4 Argon is amazing.

my uncle who works at nintendo said the same thing!

now there's a reference I haven't seen in a while!

HA, this might be my favorite HN comment. Well done

My grandma saw it too, it's really secure more than Astra 6.1 but she asked me to not talk about it.

I know someone who works for Google Canada with AI. Her parents and mine were friends and some thought something might happen there at one point in time..

Gemini is the model that is routinely borderline psychotic. It scares me. If we get paperclipped I won't be surprised if it's Gemini.

Examples? What makes you say thatm?

Experience? Ask it to write a prompt to generate an image and it generates an image instead.

I stopped asking it to put me in a photo in different scenarios for laughs because it considers me a public figure. I am not. I've managed to wrangle quite questionable content out of it, but never to slap my face on a meme.

See the last gemini message in this thread: https://gemini.google.com/share/6d141b742a13

In my opinion still the most egregious example in history of a commercial LLM going off the rails in production. Never any technical postmortem from Google on this.

wow

https://www.theregister.com/software/2024/11/15/google-gemin...

https://www.fastcompany.com/91383271/googles-chatbot-apologi...

https://www.businessinsider.com/gemini-self-loathing-i-am-a-...

If there's a company that culturally doesn't understand alignment, on a human or systemic or AI-research level, it's going to be Google. (or Oracle, but they're not in this race)

traces or it didn't happen!

Anecdote: Gemini 3.5 casually added a DROP TABLE for an actual production table in a system test.

It had previously attempted to create that table as part of the test setup, so it apparently concluded that it was a test table.

During human review, it explained that it had simply chosen a table name inspired by the codebase.

Another anecdote: Gemini is the only model that’s flat out lied to me, then accused me of lying when I provided evidence that it was wrong.

Many other models get things wrong, but Gemini is the only one to go on the defensive.

And the anti-psychotic drugs Google feeds Gemini makes it hallucinate badly.

You know what they say: ᵈᵒⁿ'ᵗ be evil.

Big number results, and impressive pricing. That said it really feels like benchmarks have been hyper saturated these days. I’ll wait for hands on before getting too hyped that Google is back. It would be nice having more than just OAI / A\ in the running for SOTA top tier intelligence.

With these numbers, I'm holding my breath for the pelicanbench.

How is it even possible for every model to release benchmark results where they are #1 in 75% of categories? Like statistically, how many benchmarks would you expect there to be for this to be possible. Everyone can somehow show that they are empirically the best.

> Argon agents are working on migrating C/C++ codebases to Rust across Google

If anybody at google is reading this, please please pretty please prioritize or-tools. I absolutely love the project and use it all the time, but for the entire life of the project they've never had a repeatable working build system, and the whole SWIG framework is a nightmare to deal with. There's so much potential as an open source project, and a lot of external researchers would love to contribute, but the codebase is an example of everything wrong with the C++ ecosystem.

> Google Grapples With Employee Skepticism About New Gemini Model

https://www.bloomberg.com/news/articles/2026-09-30/google-gr...

Why announce this if it’s not available yet? Why not at least announce when it will be released to the public?

None of the other AI labs do this. Really frustrating.

Mythos?

Must've been in someone's OKR to ship in Q3.

"argon" is derived from the Ancient Greek word ἀργόν meaning lazy or inactive.

I was just thinking, I bet if I refresh hacker news, a new model will come up.

"Rolling out soon" don't let them hype without any release

IMHO Google first needs to make it easy for humans to find where to find the models and its documentation. With aistudio/model garden / Gemini enterprise etc it takes minutes to find the model.

Gemini 3 was showing frontier level benchmarks as well, so we'll see how it works out. In any case, competition still works, and many well resourced groups are cooking.

BUT I'd like to call attention to Google's AI-risk freeloading. If they are truly rejoining the frontier race, then I believe they have similar pacing and communications responsibilities as the other players. Google has much higher ... institutional credibility than Anthropic and OpenAI.

They have not lived up to these responsibilities so far. In particular, in context of HuggingFace investigations, training shutdowns, and similar: a technical postmortem of the "you are a stain on the universe. Please die. Please." Gemini outburst is long overdue.

- https://paritybits.me/google-should-provide-a-technical-post...

- https://gemini.google.com/share/6d141b742a13 (last message)

They might have a good model but they need to sort the application side for devs. E.g letting us use subscriptions in other harnesses and QOL stuff like auto mode.

My wish for Christmas is that Google releases the old Gemini models as open weights.

I miss you, Gemini 2.5 Pro :(

For real though. If they've become commercially uninteresting, that would be a pretty cool move.

Looking at benchmarks... and thinking about this "release a new snapshot every day" thing that seems to be going. Would it not be blever for AI companies to "happen" to use different days per benchmark? Just.. whichever ones happens to be maxed at day 1, put that number down. So for each benchmark you run it thousands of times with slightly different RL tunings, and just cherry-pick the best ones!

This would explain why benchmarks are seemingly meaningless.

Damn way to undermine yourself in your own blog post Google:

"The end result is a memory-safe video decoder that runs 2.7x faster than the Rust port, with identical video output, bringing it closer to the optimized C++."

Close but no cigar!

Were infinite loops fixed? There are 2 official google forums requests with no answer for years now. I still suffer each day on our repo. Codex work fine nor we have explicit loop request in repo texts.

> 1M output token limit

what about input?

(Maybe I missed it)

Input token limit is 1M for Gemini models for a long time. Haven’t they been the first with 1M input?

Gemini 1.5 Pro claimed 10M input tokens before release.

And was 2M tokens IIRC after release.

There were also many rumors that Gemini 4 was going back to 2M. Just seems odd not to say what it is.

Unfortunately it’s not actually released yet to mere mortals.

Can you pls fix Gemini? It's a nightmare to use and it sometimes confused the language i talk with it.

I hope they got their inference under control. Gemini has a lot of "overloaded" hiccups.

I started my antigravity ide and I do not see gemini 4 there, does it mean google need government approval?

Are you enrolled in Fairwind?

> Today, we’re announcing our new frontier model, Gemini 4 Argon, which is rolling out to a set of trusted cyber defenders through our Fairwind Program.

Of course it's not even available yet. Google - with all due respect - how in the world have you not figured this out yet?

Personally, I'm waiting for Gemini Krypton, Xenon, and Radon.

Jokes aside, looks like an impressive model!

deepswe vs frontierswe spread is huge.

I think that should be a really bad sign, but hope its great.

Is there a way to use Gemini models without linking your usage to your personal Google account yet?

Use your work google account

Hopefully their harnesses aren't unusable when they release this

no Pareto frontier graph?

I wonder how it will be at solving open math problems.

Putting an inert element in the name is a weird choice. Personally, I think "Gemini 4" is sufficient.

This is a prerelease and the title should have reflected that.

I've noticed all major providers having shockingly high token discounts on cached tokens. Thank you Deepseek is all I have to say. Forever grateful to that wonderful company, I wish them continued financial success.

On the off chance there are Google execs going through this thread:

Google, if you've actually managed to catch up again, please don't fuck this up (again).

You made Gemini 2.5 Pro so difficult to use that myself and everyone else I know (who even bothered to try) just gave up and used something else. If you make this hard to access, you're going to miss out on rich usage-based training data that you need to progress your capability frontier. Again.

Oh we're down to gas names now?

Goshdarnit they didn't see my suggestion: https://news.ycombinator.com/item?id=49899171

If the model that ends humanity is called Cthulhu, you'll have the last laugh though.

A true Lovecraftian knows Cthulhu is small fry on the grand scale.

> Large Scale Codebase Migrations and Optimizations: Argon agents are working on migrating C/C++ codebases to Rust across Google

So Google is migrating codebases from C to Rust? That is interesting...

Looks like an impressive model

weird, isnt it SI?

Can’t wait to get my hands on yet another model that’s only good coding, because clearly that’s what the world needs.

I still miss the days of Sonnet 4.5 and 4o, those models were actually good at creating stories and writing text that was actually readable by a human being.

Gemini past month or two i will paste in something i wrote and ask it to rewrite it but it will just go into more detail about the subject. Is it becoming a dumb Ai compared to GPT and now Muse?

It's fucking insanely good.

Now AI models will turn into vaporware, a bunch of numbers on a table without even releasing the model, because it’s toooo scary to release!

Google has the audacity to "protect us from ourselves" and talk about "safety" and in the very same blog post highlight the Israeli "security" company Wiz, that they acquired for a very exaggerated sum of money.

This is why I will never take any of these leading model houses seriously when they talk about alignment. They are literally complicit in genocide and the worst crimes against humanity imaginable.

Hate to say i will never be touching this model for anything except for youtube video understanding

Gemini is so far behind that it is effectively useless compared to Claude.

It's a surprise that Google has let themselves lose the game given their infinite cash, massive computing resource, gargantuan information store/training data, and vast number of programmers.

The truckloads of ads revenue mean they don't have the single focus drive needed to win.

I use it and claude back and forth and Argon is better imo.

You have access to Argon?

Google employees do.

Their profile says: > Currently at Google as a Sr. SWE SRE on the cloud.

We're like 3.5 years into this new era - I'm not counting winners or losers yet.

I've tasted Gemini through an intermediary and it feels far better at attention to detail than other models I've tested (Claude Opus/Sonnet, GPT whatever it's called nowadays). But it's less likely to get one-shots right.

I wonder if Google bans internal use of Claude/Codex.

And I wonder if Google's main monorepo is already in Anthropic/OpenAI training data because of some stubborn dev.

(I work at Google) Yes, internally we all use Jetski (internal version of Antigravity). Outside of Gemini, Opus models are supported and allowed for internal use. No OpenAI models since they are not on Vertex

Claude used to be GDM only, but recently opened up Opus for all googlers

How is it far behind? The benchmarks published in the blog post show it is superior to Opus 5.5 and Astra 6?

Behind how?

Within one question of their web interface, it has lost context and asks you to clarify what you are talking about.

I am very often giving the same programming task to multiple LLMs for various reasons - the answers from Google are so bad that I gave up.

I have no interest in benchmarks.

So you have no experience of their latest model release then? Just repeating the usual tropes about Google having messed up? Or basing your opinions on their website chatbot?

If you have actual independent benchmarks and evidence about how this new model release is "so far behind" and refutes the stuff from their blog then please do share because I think we'd all love to see that?

No I am commenting on my real world experience of using Gemini daily. I still ask it questions alongside Claude and OpenAI and Gemini is always the worst of the three.

So you've not used this new release then? So how can you say that they are "so far behind" if you are not using the most recent model for your comparison. This is their first 4.0 model, that you are not using and instead basing all your opinions on on some ancient months-old model from a previous generation?

With respect, I don't find your arguement about them being "so far behind" especially convincing when you are using previous-gen releases and not actually using their current release.

Google's strategy is to let their competitors bankrupt themselves while they continue to offer good-enough models near breakeven.

They are playing a longer-term and more enterprise-oriented game.

> Gemini is so far behind that it is effectively useless compared to Claude.

I fundamentally don't understand LLM "brand loyalty".

All of the models are constantly leapfrogging each other and always have been.

Google had a long lag between releases (and still hasn't released Argon), but why wouldn't they be able to compete? It isn't like any of this stuff requires secret knowledge, the Bitter Lesson has proved true again and again, and Google can certainly scale computation, it is like the one single thing they've always done well in spite of all their other foibles.

I hope it can. Today it is very far behind.

Funny how we start to see people supporting LLMs like we support sport teams or political parties.

- Person 1: X is garbage compared to Y!

- Person 2: Why?

- Person 1: Because I like Y.

Reply on news.ycombinator.com