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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

#301

Post by bovermyer »

unsupp0rted wrote: post #131
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

How good is it for coding, relative to recent frontier models like GPT 5.x, Sonnet 4.x, etc?

In my own, very anecdotal, experience, Gemini 3 Pro and Flash are both more reliably accurate than GPT 5.x.

I have not worked with Sonnet enough to give an opinion there.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#302

Post by jack_riminton »

giancarlostoro wrote: post #233
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 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.

But you’re forgetting the Jonny Ive hardware device that totally isn’t like that laughable pin badge thing from Humane

/s

Re: Gemini 3 Flash: Frontier intelligence built for speed

#303

Post by dfsegoat »

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

> it’s more performant than Claude Opus 4.5 or GPT 5.2 extra high

...and all of that done without any GPUs as far as i know! [1]

[1] - https://www.uncoveralpha.com/p/the-chip-made-for-the-ai-infe...

(tldr: afaik Google trained Gemini 3 entirely on tensor processing units - TPUs)

Re: Gemini 3 Flash: Frontier intelligence built for speed

#304

Post by bayarearefugee »

Gemini is so awful at any sort of graceful degradation whenever they are under heavy load.

Its great that they have these new fast models, but the release hype has made Gemini Pro pretty much unusable for hours.

"Sorry, something went wrong"

random sign-outs

random garbage replies, etc

Re: Gemini 3 Flash: Frontier intelligence built for speed

#305

Post by bobviolier »

zurfer wrote: post #178

It's a cool release, but if someone on the google team reads that: flash 2.5 is awesome in terms of latency and total response time without reasoning. In quick tests this model seems to be 2x slower. So for certain use cases like quick one-token classification flash 2.5 is still the better model. Please don't stop optimizing for that!

This might also have to do with it being a preview, and only available on the global region?

Re: Gemini 3 Flash: Frontier intelligence built for speed

#306

Post by KoolKat23 »

jauntywundrkind wrote: post #59
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

Just to point this out: many of these frontier models cost isn't that far away from two orders of magnitude more than what DeepSeek charges. It doesn't compare the same, no, but with coaxing I find it to be a pretty capable competent coding model & capable of answering a lot of general queries pretty satisfactorily (but if it's a short session, why economize?). $0.28/m in, $0.42/m out. Opus 4.5 is $5/$25 (17x/60x). I…

I struggle to see the incentive to do this, I have similar thoughts for locally run models. It's only use case I can imagine is small jobs at scale perhaps something like auto complete integrated into your deployed application, or for extreme privacy, honouring NDA's etc.

Otherwise, if it's a short prompt or answer, SOTA (state of the art) model will be cheap anyway and id it's a long prompt/answer, it's way more likely to be wrong and a lot more time/human cost is spent on "checking/debugging" any issue or hallucination, so again SOTA is better.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#307

Post by procaryote »

Workaccount2 wrote: post #299
anukin wrote: post #273

Earlier quoted context omitted.

What will you use the ai in the phone to do for you? I can understand tablets and smart glasses being able to leverage smol AI much better than a phone which is reliant on apps for most of the work.

I desperately want to be able to real-time dictate actions to take on my phone. Stuff like: "Open Chrome, new tab, search for xyz, scroll down, third result, copy the second paragraph, open whatsapp, hit back button, open group chat with friends, paste what we copied and send, send a follow-up laughing tears emoji, go back to chrome and close out that tab" All while being able to just quickly glance at my phone. Ther…

is that faster to say than do, or is it an accessibility or while-driving need?

Re: Gemini 3 Flash: Frontier intelligence built for speed

#308

Post by guelo »

giancarlostoro wrote: post #233
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 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 they're willing to burn money for decades until they succeed.

This story also shows the market corruption of Google's monopolies, but a judge recently gave them his stamp of approval so we're stuck with it for the foreseeable future.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#309

Post by KoolKat23 »

__jl__ wrote: post #30

This is awesome. No preview release either, which is great to production. They are pushing the prices higher with each release though: API pricing is up to $0.5/M for input and $3/M for output For comparison: Gemini 3.0 Flash: $0.50/M for input and $3.00/M for output Gemini 2.5 Flash: $0.30/M for input and $2.50/M for output Gemini 2.0 Flash: $0.15/M for input and $0.60/M for output Gemini 1.5 Flash: $0.075/M for inp…

Token usage also needs to be factored in specifically when thinking is enabled, these newer models find more difficult problems easier and use less tokens to solve.

Re: Gemini 3 Flash: Frontier intelligence built for speed

#310

Post by danpalmer »

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…

Hardware is a factor here. GPUs are necessarily higher latency than TPUs for equivalent compute on equivalent data. There are lots of other factors here, but latency specifically favours TPUs.

The only non-TPU fast models I'm aware of are things running on Cerebras can be much faster because of their CPUs, and Grok has a super fast mode, but they have a cheat code of ignoring guardrails and making up their own world knowledge.

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