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Gemini 3 Flash: Frontier intelligence built for speed

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Re: Gemini 3 Flash: Frontier intelligence built for speed

#181

Post by timpera »

happyopossum wrote: post #163
timpera wrote: post #137

Looks awesome on paper. However, after trying it on my usual tasks, it is still very bad at using the French language, especially for creative writing. The gap between the Gemini 3 family and GPT-5 or Sonnet 4.5 is important for my usage. Also, I hate that I cannot send the Google models in a "Thinking" mode like in ChatGPT. When I send GPT 5.1 Thinking on a legal task and tell it to check and cite all sources, it ta…

> whereas the Gemini models, even 3 Pro, always answer after a few seconds and never cite their sources Definitely has not been my experience using 3 Pro in Gemini Enterprise - in fact just yesterday it took so long to do a similar task I’d thought something was broken. Nope, just re-chrcking a source

Does Gemini Enterprise have more features?

Just tried once again with the exact same prompt: GPT-5.1-Thinking took 12m46s and Gemini 3.0 Pro took about 20 seconds. The latter obviously has a dramatically worse answer as a result.

(Also, the thinking trace is not in the correct language, and doesn't seem to show which sources have been read at which steps- there is only a "Sources" tab at the end of the answer.)

Re: Gemini 3 Flash: Frontier intelligence built for speed

#182

Post by leumon »

kingstnap wrote: post #54

It has a SimpleQA score of 69%, a benchmark that tests knowledge on extremely niche facts, that's actually ridiculously high (Gemini 2.5 *Pro* had 55%) and reflects either training on the test set or some sort of cracked way to pack a ton of parametric knowledge into a Flash Model. I'm speculating but Google might have figured out some training magic trick to balance out the information storage in model capacity. Tha…

Or could it be that it's using tool calls in reasoning (e.g. a google search)?

Re: Gemini 3 Flash: Frontier intelligence built for speed

#184

Post by [deleted] »

SyrupThinker wrote: post #41

I wonder if this suffers from the same issue as 3 Pro, that it frequently "thinks" for a long time about date incongruity, insisting that it is 2024, and that information it receives must be incorrect or hypothetical. Just avoiding/fixing that would probably speed up a good chunk of my own queries.

[deleted]

Re: Gemini 3 Flash: Frontier intelligence built for speed

#185

Post by jay_kyburz »

int32_64 wrote: post #162
Obertr wrote: post #125

At this point in time I start to believe OAI is very much behind on the models race and it can't be reversed Image model they have released is much worse than nano banana pro, ghibli moment did not happen Their GPT 5.2 is obviously overfit on benchmarks as a consensus of many developers and friends I know. So Opus 4.5 is staying on top when it comes to coding The weight of the ads money from google and general direct…

Is there a "good enough" endgame for LLMs and AI where benchmarks stop mattering because end users don't notice or care? In such a scenario brand would matter more than the best tech, and OpenAI is way out in front in brand recognition.

This is why both google and microsoft are pushing Gemini and Copilot in everyone's face.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#186

Post by louiereederson »

Obertr wrote: post #125

At this point in time I start to believe OAI is very much behind on the models race and it can't be reversed Image model they have released is much worse than nano banana pro, ghibli moment did not happen Their GPT 5.2 is obviously overfit on benchmarks as a consensus of many developers and friends I know. So Opus 4.5 is staying on top when it comes to coding The weight of the ads money from google and general direct…

i think the most important part of google vs openai is slowing usage of consumer LLMs. people focus on gemini's growth, but overall LLM MAUs and time spent is stabilizing. in aggregate it looks like a complete s-curve. you can kind of see it in the table in the link below but more obvious when you have the sensortower data for both MAUs and time spent.

the reason this matters is slowing velocity raises the risk of featurization, which undermines LLMs as a category in consumer. cost efficiency of the flash models reinforces this as google can embed LLM functionality into search (noting search-like is probably 50% of chatgpt usage per their july user study). i think model capability was saturated for the average consumer use case months ago, if not longer, so distribution is really what matters, and search dwarfs LLMs in this respect.

https://techcrunch.com/2025/12/05/chatgpts-user-growth-has-s...

Re: Gemini 3 Flash: Frontier intelligence built for speed

#187

Post by encroach »

Obertr wrote: post #180
encroach wrote: post #175

Earlier quoted context omitted.

That's not how the arena works. The evaluation is blind so Google's advertising/integration has no effect on the results.

3 points, sure

Right, it only scores 3 points higher on image edit, which is within the margin of error. But on image generation, it scores a significant 29 points higher.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#188

Post by crazygringo »

int32_64 wrote: post #162
Obertr wrote: post #125

At this point in time I start to believe OAI is very much behind on the models race and it can't be reversed Image model they have released is much worse than nano banana pro, ghibli moment did not happen Their GPT 5.2 is obviously overfit on benchmarks as a consensus of many developers and friends I know. So Opus 4.5 is staying on top when it comes to coding The weight of the ads money from google and general direct…

Is there a "good enough" endgame for LLMs and AI where benchmarks stop mattering because end users don't notice or care? In such a scenario brand would matter more than the best tech, and OpenAI is way out in front in brand recognition.

For average consumers, I think very much yes, and this is where OpenAI's brand recognition shines.

But for anyone using LLM's to help speed up academic literature reviews where every detail matters, or coding where every detail matters, or anything technical where every detail matters -- the differences very much matter. And benchmarks serve just to confirm your personal experience anyways, as the differences between models becomes extremely apparent when you're working in a niche sub-subfield and one model is showing glaring informational or logical errors and another mostly gets it right.

And then there's a strong possibility that as experts start to say "I always trust more", that halo effect spreads to ordinary consumers who can't tell the difference themselves but want to make sure they use "the best" -- at least for their homework. (For their AI boyfriends and girlfriends, other metrics are probably at play...)

Re: Gemini 3 Flash: Frontier intelligence built for speed

#190

Post by rfw300 »

int32_64 wrote: post #162
Obertr wrote: post #125

At this point in time I start to believe OAI is very much behind on the models race and it can't be reversed Image model they have released is much worse than nano banana pro, ghibli moment did not happen Their GPT 5.2 is obviously overfit on benchmarks as a consensus of many developers and friends I know. So Opus 4.5 is staying on top when it comes to coding The weight of the ads money from google and general direct…

Is there a "good enough" endgame for LLMs and AI where benchmarks stop mattering because end users don't notice or care? In such a scenario brand would matter more than the best tech, and OpenAI is way out in front in brand recognition.

That might be true for a narrow definition of chatbots, but they aren't going to survive on name recognition if their models are inferior in the medium term. Right now, "agents" are only really useful for coding, but when they start to be adopted for more mainstream tasks, people will migrate to the tools that actually work first.
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