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▲ pietz a day ago

The only reason to do this is to save usage on the subscription. but because the value for money is so terrible in antigravity, you’re better off just using Claude Opus or GPT Sol for everything.

I’m glad Google is kinda back, but today there’s no reason to code with Gemini.

▲vrosas a day ago | parent | next [-]

FWIW I've found the complete opposite to be true, and have gone claude->chatgpt->gemini over the past few months.

▲imafish a day ago | parent | next [-]

Why?

▲engineer_22 a day ago | parent [-]

Im slowly migrating more of my work to Gemini too, Gemini is a workhorse now, 1M context is huge and their reasoning took a huge leap with Argon. I'm not in software, I'm in physical engineering, and where Claude is unpredictable w.r.t. engineering risk, Gemini is steady, measured. That's been my perception, anyway.

▲baoooooooooooo a day ago | parent | next [-]

My qualitative take to support this is that Gemini seems to have the strongest spatial reasoning that translates nicely into CAD and engineering domain challenges. Less clear, but I also suspect a better world understanding of materials and their interactions in an intuitive way. I have this sense that Claude can tell me everything there is to know about how to spec a gasket, but it’s like Gemini actually knows what a gasket feels like and can intuit what it’s going to do.

My partner runs an internal computational mechanics benchmark that hasn’t tracked progress with model advancements (flat/no progress since early 2026) until suddenly saturating from argon and carbon. My take is that it’s due to spatial reasoning (most of the challenges are programming that require a lot of shape rotation type thinking), but we don’t know just yet why Gemini is doing so much better.

▲pietz a day ago | parent | prev [-]

Any sources to back this up?

Carbon is the first "better than meh" model form Google in more than half a year. It's been out for less than a week. How can you consider it "steady"? Their subscription and even the API has been terribly unstable throughout the past few days, so I'm having really trouble believing any of this.

▲vrosas a day ago | parent [-]

what source could their possibly be? Argon has been out for a while now and has been solid. Even flash 3.8 is great as long as you check it's work on more complex tasks, and doesn't need 12 hours to chew through problems like claude does.

▲ilteris a day ago | parent | next [-]

I use argon and opus daily and I can tell you I have to use opus to review argon because argon goes and build things and also creates bunch of bugs along with it. I wish it weren't but that's the reality. It's great with deep cross inspection better than claude but it's slow and still need review by another frontier model.

▲p_l 17 hours ago | parent | next [-]

I solved some of that with running a very biased subagent (so fresh context) but using same model (back still with 3.8 and 4-Argon).

The problem is when 3.8 or Argon were reviewing things with context poisoned by what they were working with, as gemini models generally feel over optimistic about things.

▲vrosas a day ago | parent | prev [-]

I can say the exact opposite was also true? No model was able to one-shot perfect solutions in my reasonably complex codebase and always required a through red-team by at least one other model. Doesn't mean one model is bad and another is better, just means no model is perfect.

▲pietz a day ago | parent | prev [-]

Whatever they thought of when they said "measured"? Is that too much to ask?

Ok, you're either a troll or you objectively don't know what you're talking about. Google should be ashamed they even released 3.8 Flash. They published models with such high frequency and always made a huge jump on benchmarks. Then they were caught, when a new version of AA came out and their numbers dropped like a stone.

https://maxxbench.unlap.ai/

▲Citizen_Lame 14 hours ago | parent [-]

It does feel strange seeing these Google stans, I use all 3 at the same time (ChatGPT, Claude, Gemini) and Gemini is weakest by far, it's not even contest. Only useful stuff is web re/search.

▲petesergeant a day ago | parent | prev | next [-]

I believe you, but this is so very, very far from my experience with Google models that I have great difficulty reconciling it. I use Gemini for data-extraction, and I use Notebook LM for my medical notes just because it's an OK interface, but it will reliably screw the pooch on the simplest of reasoning or common-sense tasks.

▲pietz a day ago | parent | prev [-]

Glad you found what works for you but before Carbon, Gemini models have been utter garbage for more than 6 months now. I'm happy to debate anyone on this. Even DeepMind engineers agreed with this.

Gemini 3.8 Flash is the most benchmaxxed model to date and even Argon hallucinated so much, it was impossible to use it for any professional work.

▲artdigital a day ago | parent | next [-]

I disagree with this. Flash 3.7 and Flash 3.8 are excellent models and put (for me) Gemini back on the radar. I’ve been using them a lot since release, and still do for simple implementations and grunt work.

They’re also excellent (together with Flash-Lite) to use for consumer facing features where speed and cost matters

▲pietz 18 hours ago | parent [-]

Believe in your god. Claude and GPT models are more capable and a far better value.

https://mypriors.com/s/z3tkjPv

▲fer a day ago | parent | prev | next [-]

I've been using 3.8 Flash (and Argon and Carbon) to clean up a lot of Claude mess. But I fully agree on 3.1 Pro, it was only good for conversational stuff and some deep dives, but not for actual agent work.

▲p_l 17 hours ago | parent | prev | next [-]

I would like to see those hallucinations, because I haven't generally got any, and with my current loops in agy anytime they do minor hallucinations they get caught by adversarial review part.

Using 3.x flash series heavily over last 6 months, and along with experiences on Argon and Carbon (haven't yet played much with Hydrogen, but initial experience looks great too)

▲mattlondon 15 hours ago | parent | prev [-]

I've been using 3.8 Flash a lot and have been having a really nice time using it.

I have not experienced the hallucinations or benchmaxxing people are complaining about. People keep banging on about how the hallucinations are so terrible that it cannot be used for anything etc, yet benchmarks like https://artificialanalysis.ai/evaluations/omniscience#aa-omn... show the top two best models for not hallucinating are Gemini models.

Something does not align with these complaints from people who are trashing the Gemini models - one has to wonder if they just tried it for 5 mins then give up because it doesn't behave exactly like Claude does.

As mentioned I used 3.8 Flash for a lot of things because I don't like working with Claude all day (its generally a sanctimonious prick to work with) and I way prefer working with Gemini's personality. 3.8 Flash seemed to me to be a really decent model for every day run of the mill get-shit-done work. True I have not tried to cure cancer or solve navier-stokes recently, but for your standard day to day coding works its been really solid.

I am excited to try 4 Hydrogen now.

▲moshegramovsky 11 hours ago | parent | prev | next [-]

I think their models are good for coding but the harnesses are pure garbage. The behavior is so much less predictable than Codex/Sol/etc. I use them mostly for planning. I sometimes still write code but Argon flamed out pretty badly yesterday and I'll probably just give up on Antigravity again.

▲4lb3rn a day ago | parent | prev [-]

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