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Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

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401–410 of 616 posts

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#401
post #334

Earlier quoted context omitted.

[flagged]

Mostly because the person I was replying to has commented about using it to write code. If you're using it for other purposes, then I give you permission to ignore my comment; there's no reason to descend into name calling.

the person you were replying to says absolutely nothing about using it to write code.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#402

I'm going to get downvoted/flagged but I feel like we need a new type of "Show HN/Tell HN" etc for "New AI Model Available". Front page is tedious these days.

> I'm going to get downvoted/flagged but [...] Why do you care that much? Just say it. You're letting an imaginary score determine if you should express your suggestion for improvement. That's a bit wild.

No I'm not, I expressed it...

I prefaced it with that to simply say I knew it'd be an unpopular opinion.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#403

Google somehow managed to snatch defeat from the jaws of success with their AI products. They literally forced me and my company out of Antigravity by phasing out AI Ultra subscription without any proper product follow-up. Antigravity IDE cannot even have poweruser subscriptions now from Google Workspace an Gemini Enterprise Agent Platform cannot be attached to Antigravity IDE. Gemini Enterprise Agent Platform has an…

Aren’t the subscriptions extremely subsidized and burning cash for Anthropic and OpenAI? A reasonable explanation is they’re simply abstaining from the war of attrition, especially given cheaper comparable models are breaking the illusion that the “frontier of intelligence” has any kind of per token margin.

they're subsidized if you max them out, i'd imagine most users are paying $20 for maybe $2-5 of tokens.

anthropic probably has more customers that use more of their sub, but for open ai where a lot of their subs are consumers through chatgpt.com, they have a lot of free money to work with there

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#404

Earlier quoted context omitted.

That and/or the business case isn’t as clear when serving enormous models? You’re constantly stuck in a red queen’s race where your profitability window is increasingly measured in weeks because the Chinese are right behind you. For small models (which are probably distilled from their big ones) you can serve them economically all the time and not hemorrhage money.

[flagged]

without any hard data one way or another your comment is worthless. "pile up subscriptions" - based on what? neither company is public. "piling up subscriber counts", "piling up API usage"? cool. how much money are they making? oh you don't know because they're not public.

the reality is one way or another that as long as there exists an alternative that a USA company could serve with the same compute rented from hyperscalers, this represents a threat, even if the extent to which is unknown

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#405

Earlier quoted context omitted.

Google Cloud is probably Google Deepminds biggest competitor. Big company kinda bullshit.

How so?

Google cloud sells compute out from under Deepmind to other labs. So they basically are in competition with Google cloud for compute.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#406

Earlier quoted context omitted.

That and/or the business case isn’t as clear when serving enormous models? You’re constantly stuck in a red queen’s race where your profitability window is increasingly measured in weeks because the Chinese are right behind you. For small models (which are probably distilled from their big ones) you can serve them economically all the time and not hemorrhage money.

[flagged]

But what does that mean for Google if their model isn't as good as OpenAI's and Anthropic's?

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#407
post #256

Earlier quoted context omitted.

I wonder if the broad use of AI overviews on Google search results is having an impact. Maybe the numbers make it more profitable to use their compute on several billion searches a day rather than selling API access.

AI overview is just a summarization of the top 2-3 results. Of course at Google scale that will still need a ton of compute, but the requirement for generating an overview is many orders of magnitude lower than asking the same question in Gemini.

based off what?

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#408

Earlier quoted context omitted.

That and/or the business case isn’t as clear when serving enormous models? You’re constantly stuck in a red queen’s race where your profitability window is increasingly measured in weeks because the Chinese are right behind you. For small models (which are probably distilled from their big ones) you can serve them economically all the time and not hemorrhage money.

[flagged]

> Domestic China is the only very large audience for their own models

I don't think so. US models are very expensive, and not available in every country. I am not willing to pay $50/1M tokens for writing my pet projects.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#409
Bottom line it looks about on equal footing with GLM 5.2 in terms of both overall intelligence and cost per task, while being significantly faster (in fact it is the fastest model on artificial analysis as of rn [0])

[0] https://artificialanalysis.ai/models/gemini-3-6-flash

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#410
post #167

Earlier quoted context omitted.

I feel the same way. It was fun at first but has gotten tiresome. Does anyone actually use these models to generate SVGs?

Yeah I don’t get it. It tells me which model can draw an svg of a pelican riding a bicycle. It does a great job at that and the presentation is good. But why is this an indication of literally anything else?

It is simply a benchmark. It is well known that benchmarks are not meant to apply to every possible task you might perform.
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