[–] nater5000 1 day ago
[–] thanhhaimai 1 day ago
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.
[–] hangrybear666 1 day ago
[–] f6v 1 day ago
[–] hackernudes 1 day ago
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.
[–] seizethecheese 1 day ago
[–] BoorishBears 1 day ago
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.
[–] lilbigdoot 22 hours ago
[–] seizethecheese 1 day ago
Top is Opus 5.5, followed by Fable.
[–] unbrice 1 day ago
- 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
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.
[–] seizethecheese 1 day ago
> 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?
[–] ricericerice 1 day ago
[–] seizethecheese 1 day ago
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%.
[–] villish 1 day ago
[–] seizethecheese 1 day ago
It's possible, but we are getting real prompts from people on real projects, and the instructions about the battle are pretty minimal.
[–] DIVx0 1 day ago
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!
[–] seizethecheese 1 day ago
[–] nater5000 1 day ago
[–] seizethecheese 1 day ago
[–] iamdelirium 1 day ago
[–] seizethecheese 1 day ago
[–] sahila 1 day ago
what does "local" coding agents mean? Surely you're not hosting it..
[–] seizethecheese 1 day ago
[–] WarmWash 1 day ago
[–] seizethecheese 1 day ago
[–] zf00002 1 day ago
[–] seizethecheese 1 day ago
But yes, Opus is a tier above Wonder and Argon with very high confidence.
[–] CSMastermind 1 day ago
This might be the first comment I've ever seen saying something nice about the model.
[–] solarkraft 1 day ago
For me it also works the opposite way, when it actually comes out eventually it’ll already be old news.
[–] closetheloopdev 1 day ago
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.
[–] israrkhan 1 day ago
[–] closetheloopdev 1 day ago
[–] onlyrealcuzzo 1 day ago
Anthropic has been doing this with Mythos for quite some time...
[–] wasabi991011 1 day ago
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)
[–] dansquizsoft 1 day ago
[–] dgacmu 1 day ago
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.
[–] david-gpu 1 day ago
Consequently, I have zero intention of renewing my Gemini subscription. What a dumb business choice they made.
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.