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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

#351

Post by bananaflag »

CamperBob2 wrote: post #258
lysace wrote: post #124

Earlier quoted context omitted.

Really stupid question: How is Gemini-like 'thinking' separate from artificial general intelligence (AGI)? When I ask Gemini 3 Flash this question, the answer is vague but agency comes up a lot. Gemini thinking is always triggered by a query. This seems like a higher-level programming issue to me. Turn it into a loop. Keep the context. Those two things make it costly for sure. But does it make it an AGI? Surely Googl…

I don't think we'll get genuine AGI without long-term memory, specifically in the form of weight adjustment rather than just LoRAs or longer and longer contexts. When the model gets something wrong and we tell it "That's wrong, here's the right answer," it needs to remember that. Which obviously opens up a can of worms regarding who should have authority to supply the "right answer," but still... lacking the core cap…

> When the model gets something wrong and we tell it "That's wrong, here's the right answer," it needs to remember that.

Problem is that when we realize how to do this, we will have each copy of the original model diverge in wildly unexpected ways. Like we have 8 billion different people in this world, we'll have 16 gazillion different AIs. And all of them interacting with each other and remembering all those interactions. This world scares me greatly.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#352

Post by andai »

lambda wrote: post #267
samyok wrote: post #4

Don’t let the “flash” name fool you, this is an amazing model. I have been playing with it for the past few weeks, it’s genuinely my new favorite; it’s so fast and it has such a vast world knowledge that it’s more performant than Claude Opus 4.5 or GPT 5.2 extra high, for a fraction (basically order of magnitude less!!) of the inference time and price

I'm a significant genAI skeptic. I periodically ask them questions about topics that are subtle or tricky, and somewhat niche, that I know a lot about, and find that they frequently provide extremely bad answers. There have been improvements on some topics, but there's one benchmark question that I have that just about every model I've tried has completely gotten wrong. Tried it on LMArena recently, got a comparison…

So this is an interesting benchmark, because if the answer is actually in the top 3 google results, then my python script that runs a google search, scrapes the top n results and shoves them into a crappy LLM would pass your benchmark too!

Which also implies that (for most tasks), most of the weights in a LLM are unnecessary, since they are spent on memorizing the long tail of Common Crawl... but maybe memorizing infinite trivia is not a bug but actually required for the generalization to work? (Humans don't have far transfer though... do transformers have it?)

Re: Gemini 3 Flash: Frontier intelligence built for speed

#353

Post by behnamoh »

guelo wrote: post #308
giancarlostoro wrote: post #233

Earlier quoted context omitted.

I wonder at what point will everyone who over-invested in OpenAI will regret their decision (expect maybe Nvidia?). Maybe Microsoft doesn't need to care, they get to sell their models via Azure.

OpenAI's doom was written when Altman (and Nadella) got greedy, threw away the nonprofit mission, and caused the exodus of talent and funding that created Anthropic. If they had stayed nonprofit the rest of the industry could have consolidated their efforts against Google's juggernaut. I don't understand how they expected to sustain the advantage against Google's infinite money machine. With Waymo Google showed that…

> I don't understand how they expected to sustain the advantage against Google's infinite money machine.

I ask this question about Nazi Germany. They adopted the Blitkrieg strategy and expanded unsustainably, but it was only a matter of time until powers with infinite resources (US, USSR) put an end to it.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#354

Post by leemoore »

ralusek wrote: post #289
leemoore wrote: post #281

Earlier quoted context omitted.

Gemini isn't code red for Anthropic. Gemini threatens none of Anthropic's positioning in the market.

Yes it does. I never use Claude anymore outside of agentic tasks.

What demographic are you in that is leaving anthropic in mass that they care about retaining? From what I see Anthropic is targeting enterprise and coding.

Claude Code just caught up to cursor (no 2) in revenue and based on trajectories is about to pass GitHub copilot (number 1) in a few more months. They just locked down Deloitte with 350k seats of Claude Enterprise.

In my fortune 100 financial company they just finished crushing open ai in a broad enterprise wide evaluation. Google Gemini was never in the mix, never on the table and still isn’t. Every one of our engineers has 1k a month allocated in Claude tokens for Claude enterprise and Claude code.

There is 1 leader with enterprise. There is one leader with developers. And google has nothing to make a dent. Not Gemini 3, not Gemini cli, not anti gravity, not Gemini. There is no Code Red for Anthropic. They have clear target markets and nothing from google threatens those.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#355

Post by behnamoh »

samyok wrote: post #4

Don’t let the “flash” name fool you, this is an amazing model. I have been playing with it for the past few weeks, it’s genuinely my new favorite; it’s so fast and it has such a vast world knowledge that it’s more performant than Claude Opus 4.5 or GPT 5.2 extra high, for a fraction (basically order of magnitude less!!) of the inference time and price

> Don’t let the “flash” name fool you

I think it's bad naming on google's part. "flash" implies low quality, fast but not good enough. I get less negative feeling looking at "mini" models.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#357

Post by nemonemo »

behnamoh wrote: post #355
samyok wrote: post #4

Don’t let the “flash” name fool you, this is an amazing model. I have been playing with it for the past few weeks, it’s genuinely my new favorite; it’s so fast and it has such a vast world knowledge that it’s more performant than Claude Opus 4.5 or GPT 5.2 extra high, for a fraction (basically order of magnitude less!!) of the inference time and price

> Don’t let the “flash” name fool you I think it's bad naming on google's part. "flash" implies low quality, fast but not good enough. I get less negative feeling looking at "mini" models.

Fair point. Asked Gemini to suggest alternatives, and it suggested Gemini Velocity, Gemini Atom, Gemini Axiom (and more). I would have liked `Gemini Velocity`.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#358

Post by andai »

mips_avatar wrote: post #288
samyok wrote: post #4

Don’t let the “flash” name fool you, this is an amazing model. I have been playing with it for the past few weeks, it’s genuinely my new favorite; it’s so fast and it has such a vast world knowledge that it’s more performant than Claude Opus 4.5 or GPT 5.2 extra high, for a fraction (basically order of magnitude less!!) of the inference time and price

OpenAI made a huge mistake neglecting fast inferencing models. Their strategy was gpt 5 for everything, which hasn't worked out at all. I'm really not sure what model OpenAI wants me to use for my applications that require lower latency. If I follow their advice in their API docs about which models I should use for faster responses I get told either use GPT 5 low thinking, or replace gpt 5 with gpt 4.1, or switch to…

Hard to find info but I think the -chat versions of 5.1 and 5.2 (gpt-5.2-chat) are what you're looking for. They might just be an alias for the same model with very low reasoning though. I've seen other providers do the same thing, where they offer a reasoning and non reasoning endpoint. Seems to work well enough.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#359

Post by joecarpenter »

sabareesh wrote: post #356

Watch out these model are hallucinating lot more https://artificialanalysis.ai/evaluations/omniscience?omnisc...

Isn't it the opposite? From the link: Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

Gemini 3 Flash scored +13 in the test, more correct answers than incorrect.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#360

Post by lambda »

prettyblocks wrote: post #313
lambda wrote: post #267

Earlier quoted context omitted.

I'm a significant genAI skeptic. I periodically ask them questions about topics that are subtle or tricky, and somewhat niche, that I know a lot about, and find that they frequently provide extremely bad answers. There have been improvements on some topics, but there's one benchmark question that I have that just about every model I've tried has completely gotten wrong. Tried it on LMArena recently, got a comparison…

I don't think tricky niche knowledge is the sweet spot for genai and it likely won't be for some time. Instead, it's a great replacement for rote tasks where a less than perfect performance is good enough. Transcription, ocr, boilerplate code generation, etc.

The thing is, I see people use it for tricky niche knowledge all the time; using it as an alternative to doing a Google search.

So I want to have a general idea of how good it is at this.

I found something that was niche, but not super niche; I could easily find a good, human written answer in the top couple of results of a Google search.

But until now, all LLM answers I've gotten for it have been complete hallucinated gibberish.

Anyhow, this is a single data point, I need to expand my set of benchmark questions a bit now, but this is the first time that I've actually seen progress on this particular personal benchmark.

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