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.
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.
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
I find their products confusing as usual. Does Antigravity sub work same as $20 Codex? Are the limits somewhat similar to ChatGPT and Claude?
Me too. I have a basic Google One account which is now called "Google AI Plus" and it says "Get 2x higher usage access than Free". The Google AI Pro plan says "Get 4x higher usage access than Free" (from https://gemini.google/subscriptions/).
I tried antigravity with Gemini 3.8 Flash High. I used a prompt similar to what I use with Codex and Claude Code and it used up my weekly quota in 10 minutes without stopping or giving me anything useful at all.
I have the $20 plan on Anthropic and OpenAI and frequently use up the five hour window but usually get at least 2-3 hours of useful work from similar prompts. The prompt was about an embedded firmware designing a bluetooth protocol for a gamepad (the firmware was already quite mature and this is not a large change).
I was super excited to sign up for the Pro plan and compare it until I read the limits so now I didn't even bother because I'm convinced it will be trash. And just for the record I see "Gemini 4 Argon" available in my antigravity install.
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!
Who the fuck knows they roll out so many updates it's impossible to keep track
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.
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
I asked Gemini to review the repo. Apparent issues include:
The full report is here, if you're interested: https://docs.google.com/document/d/1-HqujXuDRJSWJIqEvmctcINr...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.
Wow, cool, thanks!
> 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?
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".
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.)
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.
Have you considered that the harness might be the issue?
it's opencode
> 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.
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.
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