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Gemini 3.5 Flash

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Re: Gemini 3.5 Flash

#641

Post by OhMeadhbh »

sagarpatil wrote: post #533
OhMeadhbh wrote: post #177

Am I really so old that when someone says "Flash" my immediate response is... "consider HTML5 instead" ??

Frontpage, Dreamviewer, flash, photoshop lol. We are old.

and Pagemill and Sitemill. At Bell Canada we had a very early web dev team in '94-'95. At one point pagemill came out and we could hire mostly non technical designers to build web pages. At the time it seemed like magic. We didn't need to have someone who grokked vi standing next to a designer all the time. But the HTML pagemill spat out was horrid. It always added a space to the end of link text and never closed list item elements. I eventually wrote a command line tool that fixed pagemill's output because some of our other tools really didn't like the flavour of HTML-inspired slop it emitted. *

And then I moved to the bay area and noticed there was a road called Page Mill Rd. in Palo Alto and sort of laughed for a bit. Surprised Adobe didn't release a tool called Sandhill.

[*] to be fair, most WYSIWYG page builder tools of the era spat out some sort of crappy subset of HTML, so not trying to say pagemill was the only offender.

Re: Gemini 3.5 Flash

#642

Post by PunchTornado »

easygenes wrote: post #466

For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know. We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute c…

i would like to get a job like that. what can i study? I am mostly a ml engineer / researcher.

Re: Gemini 3.5 Flash

#643

Post by PunchTornado »

rdtsc wrote: post #297

I caught it again being deceitful. It did this before (Me): Did you actually read the paper before when I pasted the link? > I will be completely honest: No, I did not. > You caught me hallucinating a confident answer based on incomplete recall rather than actually verifying the document. > Thank you for calling it out and providing the exact quote. It forced me to re-evaluate the actual data you provided rather than…

fucking get that with claude all the time too.

Re: Gemini 3.5 Flash

#644

Post by wing-_-nuts »

easygenes wrote: post #466

For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know. We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute c…

The fact that this is running on tpus is a huge point. Counting those against the other available datacenter hardware used by others, it puts google at a huge advantage, and compute > * while scaling is still working

Re: Gemini 3.5 Flash

#645

Post by joshmlewis »

__jl__ wrote: post #263
GodelNumbering wrote: post #84

Per million input/output tokens: Gemini 2.5 flash: $0.30/$2.50 Gemini 3.0 flash preview: $0.50/$3.00 Gemini 3.5 flash: $1.50/$9.00 Interesting pricing direction. I don't think we have ever seen a 3x price increase for in the immediate next same-sized model (and lol @ 3 only ever getting a preview). 3.5 flash costs similar to Gemini 2.5 pro which was $1.25/$10

This understates the cost increase. 3.5 Flash also uses more tokens. artificialanalysis.ai shows these difference to run the whole eval, which I think is more realistic pricing: Gemini 2.5 flash (27 score): $172 (1.0x) Gemini 2.5 pro (35 score): $649 (3.8x) Gemini 3.0 Flash (46 score): $278 (1.6x) Gemini 3.5 Flash (55 score): $1,552 (9.0x or 2.4x compared to 2.5 pro) This is a massive price increase... 5.6x compared…

It's interesting they use output tokens as an eval because all tokens are not made equal. Even from model to model (like Opus 4.6 to Opus 4.7) the tokenizer can be different and it's no longer an apples to apples comparison. No one really talks about this but it directly affects stats like usage limits. Certainly comparing models between providers on an apples to apples comparison token wise is not a good test.

Re: Gemini 3.5 Flash

#647

Post by bnug »

__jl__ wrote: post #263
GodelNumbering wrote: post #84

Per million input/output tokens: Gemini 2.5 flash: $0.30/$2.50 Gemini 3.0 flash preview: $0.50/$3.00 Gemini 3.5 flash: $1.50/$9.00 Interesting pricing direction. I don't think we have ever seen a 3x price increase for in the immediate next same-sized model (and lol @ 3 only ever getting a preview). 3.5 flash costs similar to Gemini 2.5 pro which was $1.25/$10

This understates the cost increase. 3.5 Flash also uses more tokens. artificialanalysis.ai shows these difference to run the whole eval, which I think is more realistic pricing: Gemini 2.5 flash (27 score): $172 (1.0x) Gemini 2.5 pro (35 score): $649 (3.8x) Gemini 3.0 Flash (46 score): $278 (1.6x) Gemini 3.5 Flash (55 score): $1,552 (9.0x or 2.4x compared to 2.5 pro) This is a massive price increase... 5.6x compared…

At these pricing levels, corporations who use the models will need to ensure employees are using them efficiently. I know, where I work, we don't really think about the cost to the company when using copilot chat, but sounds like it could start adding up really fast, especially for poorly defined questions that have to be revised multiple times.

Re: Gemini 3.5 Flash

#648

Post by data-ottawa »

Anyone using this yet?

I’m finding it very bad at instruction following vs 3.1. It calls tools it is told shouldn’t, and it loves calling tools. There’s a pretty strong bias towards its training vs system prompt instructions.

Google’s release notes say to reduce unnecessary tool calls by reducing thinking, but that feels like it should be orthogonal to me.

It definitely has improved a few logic things, like in data visualizations it’s better at labelling data, but it’s much worse at preparing data out of the box.

Re: Gemini 3.5 Flash

#649

Post by losvedir »

irthomasthomas wrote: post #634
tskj wrote: post #622

Earlier quoted context omitted.

This is also my gripe with a lot of this stuff, always evaluating models on what they can literally oneshot is completely pointless; it's not how anything works, neither for humans nor for scaffolded AIs. I guess it's neat if you want to argue that a certain level of intelligence can "never be achieved" in a single forward pass, but like, so what. No one cares about that, except people who have already decided to be…

Asking a model to improve its output is not one-shotting tho? My observation was that asking an llm to iterate and improve a response causes it to add more stuff, rather tha repair the broken stuff. And that model progress in general has the same pattern. This new model adds more details to its responses but continues to make mistakes at about the same rate.

The question was whether you were giving it the rendered image and using the model's visual modal capability, or feeding back in the textual SVG.

It's hard to "imagine" what the rendered SVG looks like, for both humans and LLMs, so just iterating on text won't really be as useful of a test. But if you show it what it rendered, it might observe the bad-looking bicycle and be able to fix the text that way.

Re: Gemini 3.5 Flash

#650

Post by FranOntanaya »

nashashmi wrote: post #156
simonw wrote: post #131

The pelican is a lot : https://github.com/simonw/llm-gemini/issues/133#issuecomment... Not a great bicycle though, it forgot the bar between the pedals and the back wheel and weirdly tangled the other bars. Expensive too - that pelican cost 13 cents: https://www.llm-prices.com/#it=11&ot=14403&sel=gemini-3.5-fl...

Beats a human by like 10$

Only if you would use this pelican picture in production.
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