| 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. |
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| ▲ | 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. |
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| ▲ | 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. |
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