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Just remembered i haven't tried argon yet, they announced argon then and delayed releasing it, didn't even know they've made it publically available. I don't understand why google thinks this is an awesome strategy in a market where there are other really good models.


For what it's worth: Argon is a pretty good model, and this is coming from someone who just sticks with Opus 5.5 mostly across the board. For the current introductory price, it provides an exceptional value. Looks like they're trying to release Carbon (which is apparently a significant improvement) at the same price as Argon, which would be a crazy value.

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.


We're working on a battle system for local coding agents [1] and Argon is really bad. Literally the worst model in our initial ranking, and Deepseek Flash, Muse Wonder, Grok are all in there.

Top is Opus 5.5, followed by Fable.

[1] https://github.com/bottomless/agent-duel


This does not mesh with other battles like Arena where Argon is nearer to the top.

Yeah, we are doing something different and actually running parallel local coding agents head to head, something Arena doesn't do.

That doesn't seem to match the arena.ai rankings, who I'm assuming has a far larger dataset of rankings than you currently hold.

https://arena.ai/leaderboard


You're right Arena.ai has far more data. Our data is actual local coding agent head-to-head battles, so I think our quality is far higher.

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%.


Have you tested older Gemini models? I wonder if their anti-distillation security measures are silently downgrading you to a less capable model.

Only 3.8 Flash which also didn't do particularly well.

It's possible, but we are getting real prompts from people on real projects, and the instructions about the battle are pretty minimal.


Well, my perspective is somewhat narrow (I use it primarily for software engineering and pretty technical data engineering work), so it's possible that Argon is well-suited for the work I do but not for other tasks. I suppose it's just more data points to consider.

Our data is all software engineering run via local coding agents, but yeah your specific use case could be one where Argon is stronger. (Or your personal preference.)

my anecdotal experience is that argon and muse wonder full are both a full tier below opus/sol.

So far in our data, there's no difference between Wonder and Sol 6.1. This is with wide error bars, as we're just getting started. Note this is Wonder, not Full as it's not on openrouter yet.

But yes, Opus is a tier above Wonder and Argon with very high confidence.


> local coding agents

what does "local" coding agents mean? Surely you're not hosting it..


Yeah, this is a new project so help me out here. I mean that the harness is running locally. I'm trying to distinguish this from arena.ai webdev arena, where they run the agent in a cloud container.

I've used argon via `agy` cli tool and was not impressed at all. However, I decided to burn up the remainder of my ultra credits on a visual reasoning pet project.

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!


Okay, this is interesting. We are hardcoding the effort (to improve data concentration), and Argon is hardcoded to "high".

It's important to note that Argon works best on Antigravity Harness: https://x.com/wenhaocha1/status/2114559544156205413

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.


This would make sense. In our local coding agent battle system, Argon is tanking, and this is running on opencode, importing agents.md and claude.md.

claude.md is not needed anymore btw, claude now reads agents.md if it doesn't find the other.

Oh, sure, but isn't claude code still generating this by default? We're just inheriting opencode behavior.

?! When did that happen. Great!

I find their products confusing as usual. Does Antigravity sub work same as $20 Codex? Are the limits somewhat similar to ChatGPT and Claude?

I've just renamed my files from CLAUDE.md to AGENTS.md I certainly won't do that again regressing back in the vendor specific direction lol

Argon is the best writing model that's been released in a while

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.


Argon is easily the worst model I've tried this year. From all the discourse I've seen, that seems to be the general consensus.

This might be the first comment I've ever seen saying something nice about the model.


Haven’t tried opus 5, sol 6 or haiku 4.5 I see

I agree. Announcing a new model without immediate availability or a definite release date seems confusing than just doing it later. When Carbon is made GA, OpenAI or Anthropic might just release their new model, and we'd be like: Carbon what?

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.


They’re not the only ones to do it, so I’m guessing their idea is to double-dip attention.

For me it also works the opposite way, when it actually comes out eventually it’ll already be old news.


Argon has been publicly available for weeks to Ultra users.

Anthropic has been doing this with Mythos for quite some time...


Argon has also been publicly available for the same amount of time for Pro users.

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)


Mythos has never been publicly available.

great writer, starts forgetting instructions around 80k context in my experience

They finally gave the $20/month pro tier access to argon in antigravity so I tried it a few days ago on one small thing and ...

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.


it’s pleasant

> it’s pleasant

for whom?


I paid for their lowest-cost subscription, thinking that it would give me a small quota of use of their most recent flash models. Instead, they give me an unnecessarily large quota of their old models, which I have precisely zero use for given that open-weight models are better and cost next to nothing.

Consequently, I have zero intention of renewing my Gemini subscription. What a dumb business choice they made.


It's Google. They can't help themselves. This is what they do.



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