Gemini 3

https://blog.google/products/gemini/gemini-3/

by preek • 8 months ago

1735 1027 8 months ago

blog.google

https://blog.google/technology/developers/gemini-3-developer...

https://aistudio.google.com/prompts/new_chat?model=gemini-3-...

nilsingwersen• 8 months ago

Feeling great to see something confidential

RobinL• 8 months ago

- Anyone have any idea why it says 'confidential'?

- Anyone actually able to use it? I get 'You've reached your rate limit. Please try again later'. (That said, I don't have a paid plan, but I've always had pretty much unlimited access to 2.5 pro)

[Edit: working for me now in ai studio]

sd92• 8 months ago

How long does it typically take after this to become available on https://gemini.google.com/app ?

I would like to try the model, wondering if it's worth setting up billing or waiting. At the moment trying to use it in AI Studio (on the Free tier) just gives me "Failed to generate content, quota exceeded: you have reached the limit of requests today for this model. Please try again tomorrow."

Squarex• 8 months ago

Today I guess. They were not releasing the preview models this time and it seems the want to synchronize the release.

mpeg2• 8 months ago

Allegedly it's already available in stealth mode if you choose the "canvas" tool and 2.5. I don't know how true that is, but it is indeed pumping out some really impressive one shot code

Edit: Now that I have access to Gemini 3 preview, I've compared the results of the same one shot prompts on the gemini app's 2.5 canvas vs 3 AI studio and they're very similar. I think the rumor of a stealth launch might be true.

sd92• 8 months ago

Thanks for the hint about Canvas/2.5. I have access to 3.0 in AI Studio now, and I agree the results are very similar.

csomar• 8 months ago

It's already available. I asked it "how smart are you really?" and it gave me the same ai garbage template that's now very common on blog posts: https://gist.githubusercontent.com/omarabid/a7e564f09401a64e...

magicalhippo• 8 months ago

https://gemini.google.com/app

How come I can't even see prices without logging in... they doing regional pricing?

Romario77• 8 months ago

It's available in cursor. Should be there pretty soon as well.

ionwake• 8 months ago

are you sure its available in cursor? ( I get: We're having trouble connecting to the model provider. This might be temporary - please try again in a moment. )

netdur• 8 months ago

On gemini.google.com, I see options labeled 'Fast' and 'Thinking.' The 'Thinking' option uses Gemini 3 Pro

mil22• 8 months ago

It's available to be selected, but the quota does not seem to have been enabled just yet.

"Failed to generate content, quota exceeded: you have reached the limit of requests today for this model. Please try again tomorrow."

"You've reached your rate limit. Please try again later."

Update: as of 3:33 PM UTC, Tuesday, November 18, 2025, it seems to be enabled.

misiti3780• 8 months ago

seeing the same issue.

sottol• 8 months ago

you can bring your google api key to try it out, and google used to give $300 free when signing up for billing and creating a key.

when i signed up for billing via cloud console and entered my credit card, i got $300 "free credits".

i haven't thrown a difficult problem at gemini 3 pro it yet, but i'm sure i got to see it in some of the A/B tests in aistudio for a while. i could not tell which model was clearly better, one was always more succinct and i liked its "style" but they usually offered about the same solution.

lousken• 8 months ago

I hope some users will switch from cerebras to free up those resources

sarreph• 8 months ago

Looks to be available in Vertex.

I reckon it's an API key thing... you can more explicitly select a "paid API key" in AI Studio now.

CjHuber5• 8 months ago

For me it’s up and running. I was doing some work with AI Studio when it was released and reran a few prompts already. Interesting also that you can now set thinking level low or high. I hope it does something, in 2.5 increasing maximum thought tokens never made it think more

r0fl• 8 months ago

Works for me.

informal007• 8 months ago

It seem that Google doesn't prepare well to release Gemini 3 but leak many contents, include the model card early today and gemini 3 on aistudio.google.com

guluarte• 8 months ago

it is live in the api

gemini-3-pro-preview-ais-applets
gemini-3-pro-preview

spudlyo• 8 months ago

Can confirm. I was able to access it using GPTel in Emacs using 'gemini-3-pro-preview' as the model name.

__jl__• 8 months ago

API pricing is up to $2/M for input and $12/M for output

For comparison: Gemini 2.5 Pro was $1.25/M for input and $10/M for output Gemini 1.5 Pro was $1.25/M for input and $5/M for output

jhack• 8 months ago

With this kind of pricing I wonder if it'll be available in Gemini CLI for free or if it'll stay at 2.5.

xnx9• 8 months ago

There's a waitlist for using Gemini 3 for Gemini CLI free users: https://docs.google.com/forms/d/e/1FAIpQLScQBMmnXxIYDnZhPtTP...

raincole• 8 months ago

Still cheaper than Sonnet 4.5: $3/M for input and $15/M for output.

brianjking2• 8 months ago

It is so impressive that Anthropic has been able to maintain this pricing still.

fosterfriends2• 8 months ago

Thrilled to see the cost is competitive with Anthropic.

dktp4• 8 months ago

It's interesting that grounding with search cost changed from

* 1,500 RPD (free), then $35 / 1,000 grounded prompts

* 1,500 RPD (free), then (Coming soon) $14 / 1,000 search queries

It looks like the pricing changed from per-prompt (previous models) to per-search (Gemini 3)

DeathArrow• 8 months ago

It generated a quite cool pelican on a bike: https://imgur.com/a/yzXpEEh

rixed2• 8 months ago

2025: solve the biking pelican problem

2026: cure cancer

GodelNumbering• 8 months ago

And of course they hiked the API prices

Standard Context(≤ 200K tokens)

Input $2.00 vs $1.25 (Gemini 3 pro input is 60% more expensive vs 2.5)

Output $12.00 vs $10.00 (Gemini 3 pro output is 20% more expensive vs 2.5)

Long Context(> 200K tokens)

Input $4.00 vs $2.50 (same +60%)

Output $18.00 vs $15.00 (same +20%)

CjHuber5• 8 months ago

Is it the first time long context has separate pricing? I hadn’t encountered that yet

Topfi• 8 months ago

Google has been doing that for a while.

brianjking2• 8 months ago

Google has always done this.

1ucky• 8 months ago

Anthropic is also doing this for long context >= 200k Tokens on Sonnet 4.5

panarky2• 8 months ago

Claude Opus is $15 input, $75 output.

xnx9• 8 months ago

If the model solves your needs in fewer prompts, it costs less.

aliljet4• 8 months ago

When will this be available in the cli?

_ryanjsalva• 8 months ago

Gemini CLI team member here. We'll start rolling out today.

aliljet4• 8 months ago

This is the heroic move everyone is waiting for. Do you know how this will be priced?

evandena• 8 months ago

How about for Pro (not Ultra) subscribers?

Sammi• 8 months ago

I'm already seeing it in https://aistudio.google.com/

skerit• 8 months ago

Not the preview crap again. Haven't they tested it enough? When will it be available in Gemini-CLI?

CjHuber5• 8 months ago

Honestly I liked 2.5 Pro preview much more than the final version

prodigycorp5• 8 months ago

I'm sure this is a very impressive model, but gemini-3-pro-preview is failing spectacularly at my fairly basic python benchmark. In fact, gemini-2.5-pro gets a lot closer (but is still wrong).

For reference: gpt-5.1-thinking passes, gpt-5.1-instant fails, gpt-5-thinking fails, gpt-5-instant fails, sonnet-4.5 passes, opus-4.1 passes (lesser claude models fail).

This is a reminder that benchmarks are meaningless – you should always curate your own out-of-sample benchmarks. A lot of people are going to say "wow, look how much they jumped in x, y, and z benchmark" and start to make some extrapolation about society, and what this means for others. Meanwhile.. I'm still wondering how they're still getting this problem wrong.

edit: I've a lot of good feedback here. I think there are ways I can improve my benchmark.

m00dy• 8 months ago

that's why everyone using AI for code should code in rust only.

Filligree• 8 months ago

What's the benchmark?

petters• 8 months ago

Good personal benchmarks should be kept secret :)

ahmedfromtunis• 8 months ago

I don't think it would be a good idea to publish it on a prime source of training data.

prodigycorp5• 8 months ago

nice try!

GuB-422• 8 months ago

NIBBLES.BAS maybe [1]

If you make some assumptions about the species of the snake, it can count as a basic python benchmark ;)

[1] https://en.wikipedia.org/wiki/Nibbles_(video_game)

mupuff1234• 8 months ago

Could also just be rollout issues.

prodigycorp5• 8 months ago

Could be. I'll reply to my comment later with pass/fail results of a re-run.

ddalex2• 8 months ago

I moved to using the model from python coding to golang coding and got incredible speedups in writing the correct version of the code

layer84• 8 months ago

Is observed speed meaningful for a model preview? Isn’t it likely to go down once usage goes up?

mring33621• 8 months ago

I agree that benchmarks are noise. I guess, if you're selling an LLM wrapper, you'd care, but as a happy chat end-user, I just like to ask a new model about random stuff that I'm working on. That helps me decide if I like it or not.

I just chatted with gemini-3-pro-preview about an idea I had and I'm glad that I did. I will definitely come back to it.

IMHO, the current batch of free, free-ish models are all perfectly adequate for my uses, which are mostly coding, troubleshooting and learning/research.

This is an amazing time to be alive and the AI bubble doomers that are costing me some gains RN can F-Off!

testartr2• 8 months ago

and models are still pretty bad at playing tic-tac-toe, they can do it, but think way too much

it's easy to focus on what they can't do

big-and-small• 8 months ago

Everything is about context. When you just ask non-concrete task it's still have to parse your input and figure what is tic-tac-toe in this context and what exactly you expect it to do. This is why all "thinking".

Ask it to implement tic-tac-toe in Python for command line. Or even just bring your own tic-tac toe code.

Then make it imagine playing against you and it's gonna be fast and reliable.

benterix2• 8 months ago

This is a reminder that benchmarks are meaningless – you should always curate your own out-of-sample benchmarks.

Yeah I have my own set of tests and the results are a bit unsettling in the sense that sometimes older models outperform newer ones. Moreover, they change even if officially the model doesn't change. This is especially true of Gemini 2.5 pro that was performing much better on the same tests several months ago vs. now.

Iulioh• 8 months ago

A lot of newer models are geared towards efficency and if you add the fact that more efficent models are trained on the output of less efficent (but more accurate) models....

GPT4/3o might be the best we will ever have

adastra2213• 8 months ago

I maintain a set of prompts and scripts for development using Claude Code. They are still all locked to using Sonnet 4 and Opus 4.1, because Sonnet 4.5 is flaming hot garbage. I’ve stopped trusting the benchmarks for anything.

Archer6621• 8 months ago

I wonder whether it could be related to some kind of over-fitting, i.e. a prompting style that tends to work better with the older models, but performs worse with the newer ones.

WhitneyLand• 8 months ago

>benchmarks are meaningless

No they’re not. Maybe you mean to say they don’t tell the whole story or have their limitations, which has always been the case.

>my fairly basic python benchmark

I suspect your definition of “basic” may not be consensus. Gpt-5 thinking is a strong model for basic coding and it’d be interesting to see a simple python task it reliably fails at.

NaomiLehman5• 8 months ago

they are not meaningless, but when you work a lot with LLMs and know them VERY well, then a few varied, complex prompts tell you all you need to know about things like EQ, sycophancy, and creative writing.

I like to compare them using chathub using the same prompts

Gemini still calls me "the architect" in half of the prompts. It's very cringe.

Rover222• 8 months ago

curious if you tried grok 4.1 too

sosodev3• 8 months ago

How can you be sure that your benchmark is meaningful and well designed?

Is the only thing that prevents a benchmark from being meaningful publicity?

prodigycorp5• 8 months ago

I didn't tell you what you should think about the model. All I said is that you should have your own benchmark.

I think my benchmark is well designed. It's well designed because it's a generalization of a problem I've consistently had with LLMs on my code. Insofar that it encapsulates my coding preferences and communication style, that's the proper benchmark for me.

thefourthchime• 8 months ago

I like to ask "Make a pacman game in a single html page". No model has ever gotten a decent game in one shot. My attempt with Gemini3 was no better than 2.5.

ofa0e2• 8 months ago

Your benchmarks should not involve IP.

Workaccount28• 8 months ago

It made a working game for me (with a slightly expanded prompt), but the ghosts got trapped in the box after coming back from getting killed. A second prompt fixed it. The art and animation however was really impressive.

bitexploder2• 8 months ago

Something else to consider. I often have much better success with something like: Create a prompt that creates a specification for a pacman game in a single html page. Consider edge cases and key implementation details that result in bugs. <take prompt>, execute prompt. It will often yield a much better result than one generic prompt. Now that models are trained on how to generate prompts for themselves this is quite productive. You can also ask it to implement everything in stages and implement tests, and even evaluate its tests! I know that isn't quite the same as "Implement pacman on an HTML page" but still, with very minimal human effort you can get the intended result.

dekhn• 8 months ago

Using a single custom benchmark as a metric seems pretty unreliable to me.

Even at the risk of teaching future AI the answer to your benchmark, I think you should share it here so we can evaluate it. It's entirely possible you are coming to a wrong conclusion.

prodigycorp5• 8 months ago

after taking a walk for a bit i decided you’re right. I came to the wrong conclusion. Gemini 3 is incredibly powerful in some other stuff I’ve run.

This probably means my test is a little too niche. The fact that it didn’t pass one of my tests doesn’t speak to the broader intelligence of the model per se.

While i still believe in the importance of a personalized suite of benchmarks, my python one needs to be down weighted or supplanted.

my bad to the google team for the cursory brush off.

lofaszvanitt4• 8 months ago

No, do not share it. The bigger black hole these models are in, the better.

luckydata• 8 months ago

I'm dying to know what you're giving to it that's choking on. It's actually really impressive if that's the case.

nomel5• 8 months ago

I find this hard to understand. I have AI completely choke on my code constantly. What are you doing where it performs so well? Web?

I constantly see failures in trivial vectors projections, broken bash scripts that don't properly quote variables (fail if space in filenames), and near completely inability to do relatively basic image processing tasks (if they don't rely on template matches).

I accidentally spent $50 on Gemeni 2.5 Pro last week, with Roo, trying to make a simple Mock interface for some lab equipment. The result: it asks permission to delete everything it did and start over...

t0mas88• 8 months ago

Google reports a lower score for Gemini 3 Pro on SWEBench than Claude Sonnet 4.5, which is comparing a top tier model with a smaller one. Very curious to see whether there will be an Opus 4.5 that does even better.

nickandbro• 8 months ago

What we have all been waiting for:

"Create me a SVG of a pelican riding on a bicycle"

https://www.svgviewer.dev/s/FfhmhTK1

Thev00d00• 8 months ago

That is pretty impressive.

So impressive it makes you wonder if someone has noticed it being used a benchmark prompt.

burkaman• 8 months ago

Simon says if he gets a suspiciously good result he'll just try a bunch of other absurd animal/vehicle combinations to see if they trained a special case: https://simonwillison.net/2025/Nov/13/training-for-pelicans-...

rixed2• 8 months ago

I have tried combinations of hard to draw vehicle and animals (crocodile, frog, pterodactly, riding a hand glider, tricycle, skydiving), and it did a rather good job in every cases (compared to previous tests). Whatever they have done to improve on that point, they did it in a way that generalise.

bitshiftfaced• 8 months ago

It hadn't occurred to me until now that the pelican could overcome the short legs issue by not sitting on the seat and instead put its legs inside the frame of the bike. That's probably closer to how a real pelican would ride a bike, even if it wasn't deliberate.

xnx9• 8 months ago

Very aero

CjHuber5• 8 months ago

Interesting that they added an option to select your own API key right in AI studio‘s input field. I sincerely hope the times of generous free AIstudio usage are not over

golfer• 8 months ago

Supposedly this is the model card. Very impressive results.

https://pbs.twimg.com/media/G6CFG6jXAAA1p0I?format=jpg&name=...

Also, the full document:

https://archive.org/details/gemini-3-pro-model-card/page/n3/...

tweakimp• 8 months ago

Every time I see a table like this numbers go up. Can someone explain what this actually means? Is there just an improvement that some tests are solved in a better way or is this a breakthrough and this model can do something that all others can not?

rvnx3• 8 months ago

This is a list of questions and answers that was created by different people.

The questions AND the answers are public.

If the LLM manages through reasoning OR memory to repeat back the answer then they win.

The scores represent the % of correct answers they recalled.

stavros• 8 months ago

I estimate another 7 months before models start getting 115% on Humanity's Last Exam.

HardCodedBias• 8 months ago

If you believe another thread the benchmarks are comparing Gemini-3 (probably thinking) to GPT-5.1 without thinking.

The person also claims that with thinking on the gap narrows considerably.

We'll probably have 3rd party benchmarks in a couple of days.

iamdelirium• 8 months ago

This is easily shown that the numbers are for GPT 5.1 thinking high.

Just go to the leaderboard website and see for yourself: https://arcprize.org/leaderboard

samuelknight• 8 months ago

"Gemini 3 Pro Preview" is in Vertex

ponyous8• 8 months ago

Can’t wait to test it out. Been running a tons of benchmarks (1000+ generations) for my AI to CAD model project and noticed:

- GPT-5 medium is the best

- GPT-5.1 falls right between Gemini 2.5 Pro and GPT-5 but it’s quite a bit faster

Really wonder how well Gemini 3 will perform

santhoshr• 8 months ago

Pelican riding a bicycle: https://pasteboard.co/CjJ7Xxftljzp.png

mohsen1• 8 months ago

Some time I think I should spend $50 on Upwork to get a real human artist to do it first to know what is that we're going for. What a good pelican riding a bicycle SVG is actually looking like?

AstroBen6• 8 months ago

IMO it's not about art, but a completely different path than all these images are going down. The pelican needs tools to ride the bike, or a modified bike. Maybe a recumbent?

robterrell• 8 months ago

At this point I'm surprised they haven't been training on thousands of professionally-created SVGs of pelicans on bicycles.

notatoad• 8 months ago

i think anything that makes it clear they've done that would be a lot worse PR than failing the pelican test would ever be.

arresin• 8 months ago

It’s a good pelican. Not great but good.

cubefox• 8 months ago

The blue lines indicating wind really sell it.

xnx9• 8 months ago

2D SVG is old news. Next frontier is animated 3D. One shot shows there's still progress to be made: https://aistudio.google.com/apps/drive/1XA4HdqQK5ixqi1jD9uMg...

knownjorbist• 8 months ago

Did you notice that this embedded a Gemini API connection within the app itself? Or am I not understanding what that is?

Alex-Programs2• 8 months ago

Incredible. Thanks for sharing.

agnosticmantis• 8 months ago

This says Gemini 2.5 though.

nick326611232• 8 months ago

Great improvement by only adding one feedback prompt: Change the rotation axis of the wheels by 90 degrees in the horizontal plane. Same for the legs and arms

https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...

Der_Einzige2• 8 months ago

When will they allow us to use modern LLM samplers like min_p, or even better samplers like top N sigma, or P-less decoding? They are provably SOTA and in some cases enable infinite temperature.

Temperature continues to be gated to maximum of 0.2, and there's still the hidden top_k of 64 that you can't turn off.

I love the google AI studio, but I hate it too for not enabling a whole host of advanced features. So many mixed feelings, so many unanswered questions, so many frustrating UI decisions on a tool that is ostensibly aimed at prosumers...

ttul• 8 months ago

My favorite benchmark is to analyze a very long audio file recording of a management meeting and produce very good notes along with a transcript labeling all the speakers. 2.5 was decently good at generating the summary, but it was terrible at labeling speakers. 3.0 has so far absolutely nailed speaker labeling.

iagooar• 8 months ago

What prompt do you use for that?

gregsadetsky6• 8 months ago

I just tried "analyze this audio file recording of a meeting and notes along with a transcript labeling all the speakers" (using the language from the parent's comment) and indeed Gemini 3 was significantly better than 2.5 Pro.

3 created a great "Executive Summary", identified the speakers' names, and then gave me a second by second transcript:

    [00:00] Greg: Hello.
    [00:01] X: You great?
    [00:02] Greg: Hi.
    [00:03] X: I'm X.
    [00:04] Y: I'm Y.
    ...

Super impressive!

punnerud• 8 months ago

I made a simple webpage to grab text from YouTube videos: https://summynews.com Great for this kind of testing? (want to expand to other sources in the long run)

valtism• 8 months ago

Parakeet TDT v3 would be really good at that

kridsdale32• 8 months ago

Yes, this is the best solution for that goal. Use the MacWhisper app + Parakeet 3.

renegade-otter• 8 months ago

It's not even THAT hard. I am working on a side project that gets a podcast episode and then labels the speakers. It works.

satvikpendem2• 8 months ago

I'd do the transcript and the summary parts separately. Dedicated audio models from vendors like ElevenLabs or Soniox use speaker detection models to produce an accurate speaker based transcript while I'm not necessarily sure that Google's models do so, maybe they just hallucinate the speakers instead.

trvz• 8 months ago

Agreed. I don’t see the need for Gemini to be able to do this task, although it should be able to offload it to another model.

rfw300• 8 months ago

My audio experiment was much less successful — I uploaded a 90-minute podcast episode and asked it to produce a labeled transcript. Gemini 3:

- Hallucinated at least three quotes (that I checked) resembling nothing said by any of the hosts

- Produced timestamps that were almost entirely wrong. Language quoted from the end of the episode, for instance, was timestamped 35 minutes into the episode, rather than 85 minutes.

- Almost all of what is transcribed is heavily paraphrased and abridged, in most cases without any indication.

Understandable that Gemini can't cope with such a long audio recording yet, but I would've hoped for a more graceful/less hallucinatory failure mode. And unfortunately, aligns with my impression of past Gemini models that they are impressively smart but fail in the most catastrophic ways.

ant6n• 8 months ago

The worst when it fails to eat simple pdf documents and lies and gas lights in an attempt to cover it up. Why not just admit you can’t read the file?

Rudybega2• 8 months ago

I wonder if you could get around this with a slightly more sophisticated harness. I suspect you're running into context length issues.

Something like

1.) Split audio into multiple smaller tracks. 2.) Perform first pass audio extraction 3.) Find unique speakers and other potentially helpful information (maybe just a short summary of where the conversation left off) 4.) Seed the next stage with that information (yay multimodality) and generate the audio transcript for it

Obviously it would be ideal if a model could handle the ultra long context conversations by default, but I'd be curious how much error is caused by a lack of general capability vs simple context pollution.

satvikpendem2• 8 months ago

Now try an actual speech model like ElevenLabs or Soniox, not something not made for it.

denysvitali• 8 months ago

Finally!

thedelanyo• 8 months ago

Reading the introductory passage - all I can say now is, Ai is here to stay.

meetpateltech• 8 months ago

DeepMind page: https://deepmind.google/models/gemini/

Gemini 3 Pro DeepMind Page: https://deepmind.google/models/gemini/pro/

Developer blog: https://blog.google/technology/developers/gemini-3-developer...

Gemini 3 Docs: https://ai.google.dev/gemini-api/docs/gemini-3

Google Antigravity: https://antigravity.google/

fuzzythinker• 8 months ago

Also recently: Code Wiki: https://codewiki.google/

wohoef• 8 months ago

Curious to see it in action. Gemini 2.5 has already been very impressive as a study buddy for courses like set theory, information theory, and automata. Although I’m always a bit skeptical of these benchmarks. Seems quite unlikely that all of the questions remain out of their training data.

aliljet4• 8 months ago

Understanding precisely why Gemini 3 isn't front of the pack on SWE Bench is really what I was hoping to understand here. Especially for a blog post targeted at software developers...

cube2222• 8 months ago

Yeah, they mention a benchmark I'm seeing the first time (Terminal-Bench 2.0) and are supposedly leading in, while for some reason SWE Bench is down from Sonnet 4.5.

Curious to see some third-party testing of this model. Currently it seems to primarily improve of "general non-coding and visual reasoning" primarily, based on the benchmarks.

nico1207• 8 months ago

They are not even leading in Terminal-Bench... GPT 5.1-codex is better than Gemini 3 Pro

svantana2• 8 months ago

SWEBench-Verified is probably benchmaxxed at this stage. Claude isn't even the top performer, that honor goes to Doubao [1].

Also, the confidence interval for a such a small dataset is about 3 percent points, so these differences could just be up to chance.

[1] https://www.swebench.com/

usaar333• 8 months ago

claude 4.5 gets 82% on their own highly customized scaffolding. (parallel compute with a scoring function). That beats Doubao

pawelduda2• 8 months ago

Why is this particular benchmark important?

aliljet4• 8 months ago

Thus far, this is one of the best objective evaluations of real world software engineering...

spookie• 8 months ago

Does anyone trust benchmarks at this point? Genuine question. Isn't the scientific consensus that they are broken and poor evaluation tools?

mudkipdev3• 8 months ago

I make my own automated benchmarks

energy1237• 8 months ago

They overly emphasize tasks with small context without noise and red herrings in the context.

rkozik19893• 8 months ago

Honestly, I am inclined to think a lot of the people who are wowed by benchmarks and simple tech demos probably aren't doing very much at their day job and if they're either working on simple codebases or ones that don't have very many users(more users == more bugs found). When you throw these models at complex software projects like SOAs, big object-oriented codebases, etc. their output can be totally unusable.

Workaccount28• 8 months ago

It doesn't matter, the real benchmark is taking the community temperature on the model after a few weeks of usage.

ramesh31• 8 months ago

"It doesn't matter, the real benchmark is taking the community temperature on the model after a few weeks of usage."

Indeed. It's almost impossible to truly know a model before spending a few million tokens on a real world task. It will take a step-change level advancement at this point for me to trust anything but Claude right now.

epolanski4• 8 months ago

Imho Gemini 2.5 was by far the better model on non-trivial tasks.

ezekiel68• 8 months ago

I mean... it achieved 76.2% vs the leader (Claude Sonnet) at 77.2%.

That's a "loss" I can deal with.

svantana2• 8 months ago

Grok got to hold the top spot of LMArena-text for all of ~24 hours, good for them [1]. With stylecontrol enabled, that is. Without stylecontrol, gemini held the fort.

[1] https://lmarena.ai/leaderboard/text

inkysigma2• 8 months ago

Is it just me or is that link broken because of the cloudflare outage?

Edit: nvm it looks to be up for me again

dyauspitr2• 8 months ago

Grok is heavily censored though

KingMob3• 8 months ago

Is it censored... or just biased towards edge-lord MechaHitler nonsense whenever Musk feels like tinkering with the system prompt?

bnchrch• 8 months ago

I've been so happy to see Google wake up.

Many can point to a long history of killed products and soured opinions but you can't deny theyve been the great balancing force (often for good) in the industry.

- Gmail vs Outlook

- Drive vs Word

- Android vs iOS

- Worklife balance and high pay vs the low salary grind of before.

Theyve done heaps for the industry. Im glad to see signs of life. Particularly in their P/E which was unjustly low for awhile.

digbybk• 8 months ago

Ironically, OpenAI was conceived as a way to balance Google's dominance in AI.

dragonwriter3• 8 months ago

I thought it was a workaround to Google's complete disinterest in productizing the AI research it was doing and publishing, rather than a way to balance their dominance in a market which didn't meaningfully exist.

CobrastanJorji2• 8 months ago

Pffft. OpenAI was conceived to be Open, too.

kccqzy• 8 months ago

Balance is too weak of a word. OpenAI was conceived specifically to prevent Google from getting AGI first. That was its original goal. At the time of its founding Google was the undisputed leader of AI anywhere in the world. Musk was then very worried about AGI being developed behind closed doors particularly Google, which was why he was the driving force behind the founding of OpenAI.

63stack• 8 months ago

- Making money vs general computing

rvz4• 8 months ago

Google always has been there, its just that many didn't realize that DeepMind even existed and I said that they needed to be put to commercial use years ago. [0] and Google AI != DeepMind.

You are now seeing their valuation finally adjusting to that fact all thanks to DeepMind finally being put to use.

[0] https://news.ycombinator.com/item?id=34713073

ThrowawayR22• 8 months ago

They've poisoned the internet with their monopoly on advertising, the air pollution of the online world, which is an transgression that far outweighs any good they might have done. Much of the negative social effects of being online come from the need to drive more screen time, more engagement, more clicks, and more ad impressions firehosed into the faces of users for sweet, sweet, advertiser money. When Google finally defeats ad-blocking, yt-dlp, etc., remember this.

visarga• 8 months ago

Yes, this is correct, and it happens everywhere. App Store, Play Store, YouTube, Meta, X, Amazon and even Uber - they all play in two-sided markets exploiting both its users and providers at the same time.

notepad0x904• 8 months ago

They're not a moral entity. corporations aren't people.

I think a lot of the harms you mentioned are real, but they're a natural consequence of capitalistic profit chasing. Governments are supposed to regulate monopolies and anti-consumer behavior like that. Instead of regulating surveillance capitalism, governments are using it to bypass laws restricting their power.

If I were a google investor, I would absolutely want them to defeat ad-blocking, ban yt-dlp, dominate the ad-market and all the rest of what you said. In capitalism, everyone looks out for their own interests, and governments ensure the public isn't harmed in the process. But any time a government tries to regulate things, the same crowd that decries this oppose government overreach.

Voters are people and they are moral entities, direct any moral outrage at us.

bitpush8• 8 months ago

This is an understandable, but simplistic way of looking at the world. Are you also gonna blame Apple for mining for rare earths, because they made a successful product that requires exotic materials which needs to be mined from earth? How about hundreds of thousands of factory workers that are being subjected to inhumane conditions to assemble iPhones each year?

For every "OMG, internet is filled with ads", people are conveniently forgetting the real-world impact of ALL COMPANIES (and not just Apple) btw. Either you should be upset with the system, and not selectively at Google.

nwienert3• 8 months ago

Suppressed wages to colluding with Apple to not poach.

kryogen1c• 8 months ago

They've poisoned the internet

And what of the people that ravenously support ads and ad-supported content, instead of paying?

What of the consumptive public? Are they not responsible for their choices?

I do not consume algorithmic content, I do not have any social media (unless you count HN for either).

You can't have it both ways. Lead by example, stop using the poison and find friends that aren't addicted. Build an offline community.

ApolloFortyNine• 8 months ago

People love getting their content for free and that's what Google does.

Even 25 years ago people wouldn't even believe Youtube exists. Anyone can upload whatever they want, however often they want, Youtube will be responsible for promoting it, they'll provide to however many billions users want to view it, and they'll pay you 55% of the revenue it makes?

starchild3001• 8 months ago

What kind of world do you live in? Actually Google ads tend to be some of the highest ROI for the advertiser and most likely to be beneficial for the user. Vs the pure junk ads that aren't personalized, and just banner ads that have zero relationship to me. Google Ads is the enabler of free internet. I for one am thankful to them. Else you end up paying for NYT, Washinton Post, Information etc -- virtually for any high quality web site (including Search).

qweiopqweiop• 8 months ago

Forgot to mention absolutely milking every ounce of their users attention with Youtube, plus forcing Shorts!

polotics• 8 months ago

frankly when compared against TikTok, Insta, etc, YouTube is a force for good. Just script the shorts away...

bitpush8• 8 months ago

Why stop at YouTube? Blame Apple for creating an additive gadget that has single handedly wasted billions of hours of collective human intelligence. Life was so much better before iPhones.

But I hear you say - you can use iPhones for productive things and not just mindless brainrot. And that's the same with YouTube as well. Many waste time on YouTube, but many learn and do productive things.

Dont paint everything with a single, large, coarse brush stroke.

drewda• 8 months ago

For what it's worth, most of those examples are acquisitions. That's not a hit against Google in particular. That's the way all big tech co's grow. But it's not necessarily representative of "innovation."

charcircuit• 8 months ago

most of those examples are acquisitions

Taking those products from where there were to the juggernauts they are today was not guaranteed to succeed, nor was it easy. And yes plenty of innovation happened with these products post aquisition.

redbell• 8 months ago

Drive vs Word

You mean Drive vs OneDrive or, maybe Docs vs Word?

lemoncucumber3• 8 months ago

Workspace vs Office

BHSPitMonkey• 8 months ago

Surely they meant Writely vs Word

stephc_int136• 8 months ago

Google is using the typical monopoly playbook as most other large orgs, and the world would be a "better place" if they are kept in check.

But at least this company is not run by a narcissistic sociopath.

kevstev• 8 months ago

All those examples date back to the 2000s. Android has seen some significant improvements, but everything else has stagnated if not enshittified- remember when google told us not to ever worry about deleting anything?- and then started backing up my photos without me asking and are now constantly nagging me to pay them a monthly fee?

They have done a lot, but most of it was in the "don't be evil" days and they are a fading memory.

storus• 8 months ago

If you consider surveillance capitalism and dark pattern nudges a good thing, then sure. Gemini has the potential to obliterate their current business model completely so I wouldn't consider that "waking up".

IlikeKitties• 8 months ago

Something about bringing balance to the force not destroying it.

epolanski4• 8 months ago

Outlook is much better than Gmail and so is the office suite.

It's good there's competition in the space though.

brailsafe• 8 months ago

Outlook is not better in ways that email or gmail users necessarily care about, and in my experience gets in the way more than it helps with productivity or anything it tries to be good at. I've used it in office settings because it's the default, but never in my life have I considered using it by choice. If it's better, it might not matter.

vanillax• 8 months ago

I couldn't disagree more

samdoesnothing• 8 months ago

Seriously? Google is an incredibly evil company whose net contribution to society is probably only barely positive thanks to their original product (search). Since completely de-googling I've felt a lot better about myself.

zurfer• 8 months ago

It also tops LMSYS leaderboard across all categories. However knowledge cutoff is Jan 2025. I do wonder how long they have been pre-training this thing :D.

mudkipdev3• 8 months ago

Isn't it the same cutoff as 2.5?

mihau• 8 months ago

@simonw wen pelican

Workaccount28• 8 months ago

It still failed my image identification test ([a photoshopped picture of a dog with 5 legs]...please count the legs) that so far every other model has failed agonizingly, even failing when I tell them they are failing, and they tend to fight back at me.

Gemini 3 however, while still failing, at least recognized the 5th leg, but thought the dog was...well endowed. The 5th leg however is clearly a leg, despite being where you would expect the dogs member to be. I'll give it half credit for at least recognizing that there was something there.

Still though, there is a lot of work that needs to be done on getting these models to properly "see" images.

lukebechtel• 8 months ago

ah interesting. I wonder if this is a "safety guardrails blindspot" due to the placement.

achow• 8 months ago

Op is right.

https://imgcdn.stablediffusionweb.com/2024/4/19/8e54925a-004...

For the above pic I asked "What is wrong with the image?"

Result: - It totally missed the most obvious one - six fingers.

Instead it said this:

Based on a close inspection of the image, here are the things that are "wrong" or anomalous, indicating that it is likely an AI-generated image:

- The Thumb Anatomy: This is the most obvious error. The digit in the thumb's position (far left) looks exactly like a long index finger. A natural human thumb has two segments (phalanges) and is shorter and thicker, opposing the other fingers. This digit appears to have three segments and is roughly the same length and shape as the other fingers, giving the hand the appearance of having five fingers and no thumb.

- Unnatural Skin Texture: The skin is unnaturally smooth, waxy, and free of normal human imperfections like distinct pores, fine wrinkles, or hair. It has a "plastic" or "airbrushed" look typical of generative AI.

- Palm Lines: The creases on the palm are vague and generic. They don't follow the distinct pattern of major flexion creases (like the heart, head, and life lines) found on a real human hand.

- Wrist Connection: The connection between the hand and the wrist looks slightly distorted, with tendons that appear too prominent and smooth for the pose.

[Edit: 3.0 is same as 2.5 - both answered almost identically]

recitedropper11• 8 months ago

Perception seems to be one of the main constraints on LLMs that not much progress has been made on. Perhaps not surprising, given perception is something evolution has worked on since the inception of life itself. Likely much, much more expensive computationally than it receives credit for.

Workaccount28• 8 months ago

I strongly suspect it's a tokenization problem. Text and symbols fit nicely in tokens, but having something like a single "dog leg" token is a tough problem to solve.

orly013• 8 months ago

Why should it have to be expensive computationally? How do brains do it with such a low amount of energy? I think catching the brain abilities even of a bug might be very hard, but that does not mean that there isn't a way to do it with little computational power. It requires having the correct structures/models/algorithms or whatever is the precise jargon.

column2• 8 months ago

"[a photoshopped picture of a dog with 5 legs]...please count the legs"

Meanwhile you could benchmark for something actually useful. If you're about to say "But that means it won't work for my use case of identifying a person on a live feed" or whatever, then why don't you test that? I really don't understand the kick people get of successfully tricking LLMs on non productive task with no real world application. Just like the "how many r in strawberry?", "uh uh uh it says two urh urh".. ok but so what? What good is a benchmark that is so far from a real use case?

tngranados• 8 months ago

The point of benchmarking that is checking for hallucinations and overfitting. Does the model actually check the picture to count the legs or does it just see it's a dog and answer four because it knows dogs usually has four legs?

It's a perfectly valid benchmark and very telling.

GuB-422• 8 months ago

Gemini 3 however, while still failing, at least recognized the 5th leg, but thought the dog was...well endowed.

I see that AI is reaching the level of a middle school boy...

Workaccount28• 8 months ago

In reality it used the term "male anatomy" heh

icyfox2• 8 months ago

Pretty happy the under 200k token pricing is staying in the same ballpark as Gemini 2.5 Pro:

Input: $1.25 -> $2.00 (1M tokens)

Output: $10.00 -> $12.00

Squeezes a bit more margin out of app layer companies, certainly, but there's a good chance that for tasks that really require a sota model it can be more than justified.

rudedogg• 8 months ago

Every recent release has bumped the pricing significantly. If I was building a product and my margins weren’t incredible I’d be concerned. The input price almost doubled with this one.

icyfox2• 8 months ago

I'm not sure how concerned people should be at the trend lines. If you're building a product that already works well, you shouldn't feel the need to upgrade to a larger parameter model. If your product doesn't work and the new architectures unlock performance that would let you have a feasible business, even a 2x on input tokens shouldn't be the dealbreaker.

If we're paying more for a more petaflop heavy model, it makes sense that costs would go up. What really would concern me is if companies start ratcheting prices up for models with the same level of performance. My hope is raw hardware costs and OSS releases keep a lid on the margin pressure.

gertrunde2• 8 months ago

"AI Overviews now have 2 billion users every month."

"Users"? Or people that get presented with it and ignore it?

singhrac• 8 months ago

They're a bit less bad than they used to be. I'm not exactly happy about what this means to incentives (and rewards) for doing research and writing good content, but sometimes I ask a dumb question out of curiosity and Google overview will give it to me (e.g. "what's in flower food?"). I don't need GPT 5.1 Thinking for that.

recitedropper11• 8 months ago

"Since then, it’s been incredible to see how much people love it. AI Overviews now have 2 billion users every month."

Cringe. To get to 2 billion a month they must be counting anyone who sees an AI overview as a user. They should just go ahead and claim the "most quickly adopted product in history" as well.

mNovak• 8 months ago

Maybe you ignore it, but Google has stated in the past that click-through rates with AI overviews are way down. To me, that implies the 'user' read the summary and got what they needed, such that they didn't feel the need to dig into a further site (ignoring whether that's a good thing or not).

I'd be comfortable calling a 'user' anyone who clicked to expand the little summary. Not sure what else you'd call them.

gertrunde2• 8 months ago

You're right, I'm probably being a little uncharitable!

Normal users (i.e. not grumpy techies ;) ) probably just go with the flow rather than finding it irritating.

rvz4• 8 months ago

I expect almost no-one to read the Gemini 3 model card. But here is a damning excerpt from the early leaked model card from [0]:

The training dataset also includes: publicly available datasets that are readily downloadable; data obtained by crawlers; licensed data obtained via commercial licensing agreements; user data (i.e., data collected from users of Google products and services to train AI models, along with user interactions with the model) in accordance with Google’s relevant terms of service, privacy policy, service-specific policies, and pursuant to user controls, where appropriate; other datasets that Google acquires or generates in the course of its business operations, or directly from its workforce; and AI-generated synthetic data.

So your Gmails are being read by Gemini and is being put on the training set for future models. Oh dear and Google is being sued over using Gemini for analyzing user's data which potentially includes Gmails by default.

Where is the outrage?

[0] https://web.archive.org/web/20251118111103/https://storage.g...

[1] https://www.yahoo.com/news/articles/google-sued-over-gemini-...

stefs2• 8 months ago

i'm very doubtful gmail mails are used to train the model by default, because emails contain private data and as soon as this private data shows up in the model output, gmail is done.

"gmail being read by gemini" does NOT mean "gemini is trained on your private gmail correspondence". it can mean gemini loads your emails into a session context so it can answer questions about your mail, which is quite different.

inkysigma2• 8 months ago

Isn't Gmail covered under the Workspace privacy policy which forbids using that for training data. So I'm guessing that's excluded by the "in accordance" clause.

andrewinardeer• 8 months ago

The real question is, "For how long?"

aoeusnth12• 8 months ago

This seems like a dubious conclusion. I think you missed this part:

in accordance with Google’s relevant terms of service, privacy policy

recitedropper11• 8 months ago

I'm pretty sure they mention in their various TOSes that they don't train on user data in places like Gmail.

That said, LLMs are the most data-greedy technology of all time, and it wouldn't surprise me that companies building them feel so much pressure to top each other they "sidestep" their own TOSes. There are plenty of signals they are already changing their terms to train when previously they said they wouldn't--see Anthropic's update in August regarding Claude Code.

If anyone ever starts caring about privacy again, this might be a way to bring down the crazy AI capex / tech valuations. It is probably possible, if you are a sufficiently funded and motivated actor, to tease out evidence of training data that shouldn't be there based on a vendor's TOS. There is already evidence some IP owners (like NYT) have done this for copyright claims, but you could get a lot more pitchforks out if it turns out Jane Doe's HIPAA-protected information in an email was trained on.

Yizahi2• 8 months ago

By the year 2025 I think most of the HN regulars and IT people in general are so jaded regarding privacy that it is not even surprising anyone. I suspect all gmails were analyzed and read from the beginning of google age, so nothing really changed, they might as well just admit it.

Google is betting that moving email and cloud is such a giant hassle that almost no one will do it, and ditching YT and Maps is just impossible.

ponyous8• 8 months ago

Just generated a bunch of 3D CAD models using Gemini 3.0 to see how it compares in spatial understanding and it's heaps better than anything currently out there - not only intelligence but also speed.

Will run extended benchmarks later, let me know if you want to see actual data.

giancarlostoro• 8 months ago

I'm not familiar enough with CAD what type of format is it?

ponyous8• 8 months ago

It’s not a format, but in my mind it implies designs that are supposed to be functional as opposed to models that are meant for virtual games.

It generated a blender script that makes the model.

koakuma-chan• 8 months ago

When I see CAD, I always think of Casting Assistant Device.

lfx2• 8 months ago

Just hand sketched what 5 year old would do on the paper - the house, trees, sun. And asked to generate 3d model with tree.js.

Results are amazing! 2.5 and 3 seems way way head.

ponyous8• 8 months ago

Based on my benchmarks (run 100s of model generations).

2.5 stands between GPT-5 and GPT-5.1, where GPT-5 is the best of the 3.

In preliminary evals Gemini 3 seems to be way better than all, but I will know when I run extended benchmarks tonight.

thelinesnloops• 8 months ago

Sorry to ask 7 days late, but what sort of prompt do you use to get it to do it? I tried the same exercise but it just placed the image in 2D in the 3D world. Much like Paper Mario but not what I was going for! Thank you.

mindlessg• 8 months ago

I'm interested in seeing the data.

layer84• 8 months ago

Is observed speed meaningful for a model preview? Isn’t it likely to go down once usage goes up?

srameshc• 8 months ago

I think I am in this AI fatigue phase. I am past all hype with models, tools and agents and back to problem and solution approach, sometimes code gen with AI , sometimes think and ask for a piece of code. But not offloading to AI and buying all the bs, waiting it to do magic with my codebase.

amelius3• 8 months ago

Yeah, at this point I want to see the failure modes. Show me at least as many cases where it breaks. Otherwise, I'll assume it's an advertisement and I'll skip to the next headline. I'm not going to waste my time on it anymore.

jstummbillig4• 8 months ago

I think it's fun to see what is not even considered magic anymore today.

mountainriver• 8 months ago

People would have had a heart attack if they saw this 5 years ago for the first time. Now artificial brains are “meh” :)

yomismoaqui2• 8 months ago

Our ability to adapt to new things is both a blessing and a curse.

shiandow• 8 months ago

It is. But understandably the people who need to push back on what is still magic may get a bit tired.

Kiro3• 8 months ago

I agree but if Gemini 3 is as good as people on HN said about the preview, then this is the wrong announcement to sleep on.

redsymbol• 8 months ago

Why?

Not trying to challenge you, and I'd sincerely love to read your response. People said similar things about previous gen-AI tool announcements that proved over time to be overstated. Is there some reason to put more weight in "what people on HN said" in this case, compared to previous situations?

embedding-shape• 8 months ago

Only reasonable thing is to not listening to anyone who seem to be hyping anything, LLMs or otherwise. Wait until the thing gets released, run your private benchmarks against it, get a concrete number, compare against existing runs you've done before.

I don't see any other way of doing this. The people who keep reading and following comments either here on HN, from LocalLlama or otherwise will continue to be misinformed by all the FUD and guerilla marketing that is happening across all of these places.

bigstrat2003• 8 months ago

No LLM has ever been as good as people said it was. That doesn't mean this one won't be, but it does make it an unlikely bet based on past trends.

m3kw94• 8 months ago

it's not AI fatigue, its that you just need to shift mode to not pay attention too much to the latest and greatest as they all leap frog each other each month. Just stick to one and ride it thru ups and downs.

strangescript• 8 months ago

And by this time next year, this comment is going to look very silly

SchemaLoad4• 8 months ago

My test for the state of AI is "Does Microsoft Teams still suck?", if it does still suck, then clearly the AIs were not capable of just fixing the bugs and we must not be there yet.

bilekas• 8 months ago

The Gemini app surpasses 650 million users per month, more than 70% of our Cloud customers use our AI, 13 million developers have built with our generative models, and that is just a snippet of the impact we’re seeing

Not to be a negative nelly, but these numbers are definitely inflated due to Google literally pushing their AI into everything they can, much like M$. Can't even search google without getting an AI response. Surely you can't claim those numbers are legit.

blinding-streak• 8 months ago

Gemini app != Google search.

You're implying they're lying?

AstroBen6• 8 months ago

And you're implying they're being 100% truthful?

Marketing is always somewhere in the middle

lalitmaganti• 8 months ago

Gemini app surpasses 650 million users per month

Unless these numbers are just lies, I'm not sure how this is "pushing their AI into everything they can". Especially on iOS where every user is someone who went to App Store and downloaded it. Admittedly on Android, Gemini is preinstalled these days but it's still a choice that users are making to go there rather than being an existing product they happen to user otherwise.

Now OTOH "AI overviews now have two billion users" can definitely be criticised in the way you suggest.

aniforprez• 8 months ago

I don't know for sure but they have to be counting users like me whose phone has had Gemini force installed on an update and I've only opened the app by accident while trying to figure out how to invoke the old actually useful Assistant app

realusername• 8 months ago

it's still a choice that users are making to go there rather than being an existing product they happen to user otherwise.

Yes and no, my power button got remapped to opening Gemini in an update...

I removed that but I can imagine that your average user doesn't.

edaemon• 8 months ago

I unlocked my phone the other day and had the entire screen taken over with an ad for the Gemini app. There was a big "Get Started" button that I almost accidentally clicked because it was where I was about to tap for something else.

As an Android and Google Workspace user, I definitely feel like Google is "pushing their AI into everything they can", including the Gemini app.

mewpmewp22• 8 months ago

I constantly accidentally use some btn and Gemini opens up on my Samsung Galaxy. I haven't bothered to figure this out.

joaogui12• 8 months ago

It says Gemini App, not AI Overviews, AI Mode, etc

recitedropper11• 8 months ago

They claim AI overviews as having "2 billion users" in the sentences prior. They are clearly trying as hard as possible to show the "best" numbers.

Yizahi2• 8 months ago

This is benefit of bundling, I've been forecasting this for a long time - the only companies who would win the LLM race would be the megacorps bundling their offerings, and at most maybe OAI due to the sheer marketing dominance.

For example I don't pay for ChatGPT or Claude, even if they are better at certain tasks or in general. But I have Google One cloud storage sub for my photos and it comes with a Gemini Pro apparently (thanks to someone on HN for pointing it out). And so Gemini is my go to LLM app/service. I suspect the same goes for many others.

alecco• 8 months ago

Yeah my business account was forced to pay for an AI. And I only used it for a couple of weeks when Gemini 2.5 was launched, until it got nerfed. So they are definitely counting me there even though I haven't used it in like 7 months. Well, I try it once every other month to see if it's still crap, and it always is.

I hope Gemini 3 is not the same and it gives an affordable plan compared to OpenAI/Anthropic.

bespokedevelopr• 8 months ago

Wow so the polymarket insider bet was true then..

https://old.reddit.com/r/wallstreetbets/comments/1oz6gjp/new...

giarc2• 8 months ago

These prediction markets are so ripe for abuse it's unbelievable. People need to realize there are real people on the other side of these bets. Brian Armstong, CEO of Coinbase intentionally altered the outcome of a bet by randomly stating "Bitcoin, Ethereum, blockchain, staking, Web3" at the end of an earnings call. These types of bets shouldn't be allowed.

HDThoreaun• 8 months ago

I’m pretty sure that these model release date markets are made to be abused. They’re just a way to pay insiders to tell you when the model will be released.

The mention markets are pure degenerate gambling and everyone involved knows that

ethmarks7• 8 months ago

The point of prediction markets isn't to be fair. They are not the stock market. The point of prediction markets is to predict. They provide a monetary incentive for people who are good at predicting stuff. Whether that's due to luck, analysis, insider knowledge, or the ability to influence the result is irrelevant. If you don't want to participate in an unfair market, don't participate in prediction markets.

FergusArgyll2• 8 months ago

Abuse sounds bad, this is good! Now we have a sneak peek into the future, for free! Just don't bet on any markets where an insider has knowledge (or don't bet at all)

Dilettante_6• 8 months ago

Brian Armstong, CEO of Coinbase intentionally altered the outcome of a bet by randomly stating "Bitcoin, Ethereum, blockchain, staking, Web3" at the end of an earnings call.

For the kind of person playing these sorts of games, that actually really "hype".

ATMLOTTOBEER3• 8 months ago

It’s not really abuse though. These markets aggregate information; when an insider takes one side of a trade, they are selling their information about the true price (probability of the thing happening) to the market (and the price will move accordingly).

You’re spot on that people should think of who is on the other side of the trades they’re taking, and be extremely paranoid of being adversely selected.

Disallowing people from making terrible trades seems…paternalistic? Idk

ur-whale3• 8 months ago

people need to realize there are real people on the other side of these bets

None of whom were forced by anyone to place bets in the first place.

fresh_broccoli• 8 months ago

In hindsight, one possible reason to bet on November 18 was the deprecation date of older models: https://www.reddit.com/r/singularity/comments/1oom1lq/google...

mikeortman• 8 months ago

Its available for me now in gemini.google.com.... but its failing so bad at accurate audio transcription.

Its transcribing the meeting but hallucinates badly... both in fast and thinking mode. Fast mode only transcribed about a fifth of the meeting before saying its done. Thinking mode completely changed the topic and made up ENTIRE conversations. Gemini 2.5 actually transcribed it decently, just occasional missteps when people talked over each other.

I'm concerned.

fosterfriends2• 8 months ago

Gemini 3 and 3 pro are good bit cheaper than Sonnet 4.5 as well. Big fan

coffeecoders• 8 months ago

Feels like the same consolidation cycle we saw with mobile apps and browsers are playing out here. The winners aren’t necessarily those with the best models, but those who already control the surface where people live their digital lives.

Google injects AI Overviews directly into search, X pushes Grok into the feed, Apple wraps "intelligence" into Maps and on-device workflows, and Microsoft is quietly doing the same with Copilot across Windows and Office.

Open models and startups can innovate, but the platforms can immediately put their AI in front of billions of users without asking anyone to change behavior (not even typing a new URL).

Workaccount28• 8 months ago

AI overviews has arguable done more harm than good for them, because people assume it's Gemini, but really it's some ultra light weight model made for handling millions of queries a minute, and has no shortage of stupid mistakes/hallucinations.

acoustics2• 8 months ago

Microsoft hasn't been very quiet about it, at least in my experience. Every time I boot up Windows I get some kind of blurb about an AI feature.

CobrastanJorji2• 8 months ago

Man, remember the days where we'd lose our minds at our operating systems doing stuff like that?

bitpush8• 8 months ago

Google injects AI Overviews directly into search, X pushes Grok into the feed, Apple wraps "intelligence" into Maps and on-device workflows, and Microsoft is quietly doing the same with Copilot across Windows and Office.

One of them isnt the same as others (hint: It is Apple). The only thing Apple is doing with Maps is, is adding ads https://www.macrumors.com/2025/10/26/apple-moving-ahead-with...

int_19h5• 8 months ago

Gemini genuinely has an edge over the others in its super-long context size, though. There are some tasks where this is the deal breaker, and others where you can get by with a smaller size, but the results just aren't as good.

ehsankia• 8 months ago

The winners aren’t necessarily those with the best models

Is there evidence that's true? That the other models are significantly better than the ones you named?

mccoyb5• 8 months ago

I truly do not understand what plan to use so I can use this model for longer than ~2 minutes.

Using Anthropic or OpenAI's models are incredibly straightforward -- pay us per month, here's the button you press, great.

Where do I go for this for these Google models?

kachapopopow3• 8 months ago

ai studio, you get a bunch of usage free if you want more you buy credits (google one subscriptions also give you some additional usage)

mccoyb5• 8 months ago

I see -- so this is the "paid" AI studio plan?

Does that have any relation to the Gemini plan thing: https://one.google.com/explore-plan/gemini-advanced?utm_sour...

fschuett• 8 months ago

Update VSCode to the latest version and click the small "Chat" button at the top bar. GitHub gives you like $20 for free per month and I think they have a deal with the larger vendors because their pricing is insanely cheap. One week of vibe-coding costs me like $15, only downside to Copilot is that you can't work on multiple projects at the same time because of rate-limiting.

mccoyb5• 8 months ago

I'm asking about Gemini, not Copilot.

dboreham• 8 months ago

Also Google discontinues everything in short order, so personally I'm waiting until they haven't discontinued this for, say 6 months, before wasting time evaluating it.

mh-• 8 months ago

It's really impressive how much damage they've done to early adoption by earning themselves this reputation.

I've even heard it in mainstream circles that have no idea what HN is, and aren't involved in tech.

Probably would have been cheaper to keep Google Reader running - kidding, but this is the first time I remember the gut punch of Google cancelling something I heavily used personally.

KingMob3• 8 months ago

Generally a good idea with Google, but if the pace of model releases keeps up, nobody will be running 6-month-old models from anyone.

closewith3• 8 months ago

Yeah, it truly is an outstandingly bad UX. To use Gemini CLI as a business user like I would Codex or Claude Code, how much and how do I pay?

rafaquintanilha2• 8 months ago

You can install the Gemini CLI (https://github.com/google-gemini/gemini-cli) but assign a "paid" API key to it (unless you pay for Gemini Ultra).

dktp4• 8 months ago

Google actually changed it somewhat recently (3 months ago, give or take) and you can use Gemini CLI with the "regular" Google AI Pro subscription (~22eur/month). Before that, it required a separate subscription

I can't find the announcement anymore, but you can see it under benefits here https://support.google.com/googleone/answer/14534406?hl=en

The initial separate subscriptions were confusing at best. Current situation is pretty much same as Anthropic/OpenAI - straightforward

Edit: changed ~1 month ago (https://old.reddit.com/r/Bard/comments/1npiv2o/google_ai_pro...)

mccoyb5• 8 months ago

I see -- but does this allow me to us the models within "Antigravity" with the same subscription?

I poked around and couldn't figure this out.

8note2• 8 months ago

how do i actually make it use that though? i got a free year of subscription from buying a phone, but all i get is the free tier in the gemini cli

mantenpanther• 8 months ago

I am paying for AI ultra - no idea how to use it in the CLI. It says i dont‘t have access. The google admin/payment backend is pure evil. What a mess.

thelittleone2• 8 months ago

My test a few hours ago. Ultra plan got me ~20 minutes with Antigravity using Gemini 3 Pro (Low) before zero out.

ur-whale3• 8 months ago

I truly do not understand what plan to use so I can use this model for longer than ~2 minutes.

I had the exact same experience and walked away to chatgpt.

What a mess.

deanc• 8 months ago

The AntiGravity seems to be a bit overwhelmed. Unable to set up an account at the moment.

NullCascade• 8 months ago

I'm not a mathematician but I think we underestimate how useful pure mathematics can be to tell whether we are approaching AGI.

Can the mathematicians here try ask it to invent new novel math related to [Insert your field of specialization] and see if it comes up with something new and useful?

Try lowering the temperature, use SymPy etc.

ducttapecrown• 8 months ago

Terry Tao is writing about this on his blog.

stevesimmons• 8 months ago

A nice Easter egg in the Gemini 3 docs [1]:

    If you are transferring a conversation trace from another model, ... to bypass strict validation in these specific scenarios, populate the field with this specific dummy string:

    "thoughtSignature": "context_engineering_is_the_way_to_go"

[1] https://ai.google.dev/gemini-api/docs/gemini-3?thinking=high...

bijant• 8 months ago

It's an artifact of the problem that they don't show you the reasoning output but need it for further messages so they save each api conversation on their side and give you a reference number. It sucks from a GDPR compliance perspective as well as in terms of transparent pricing as you have no way to control reasoning trace length (which is billed at the much higher output rate) other than switching between low/high but if the model decides to think longer "low" could result in more tokens used than "high" for a prompt where the model decides not to think that much. "thinking budgets" are now "legacy" and thus while you can constrain output length you cannot constrain cost. Obviously you also cannot optimize your prompts if some red herring makes the LLM get hung up on something irrelevant only to realize this in later thinking steps. This will happen with EVERY SINGLE prompt if it's caused by something in your system prompt. Finding what makes the model go astray can be rather difficult with 15k token system prompts or a multitude of MCP tools, you're basically blinded while trying to optimize a black box. Obviously you can try different variations of different parts of your system prompt or tool descriptions but just because they result in less thinking tokens does not mean they are better if those reasoning steps where actually beneficial (if only in edge cases) this would be immediately apparent upon inspection but hard/impossible to find out without access to the full Chain of Thought. For the uninitiated, the reasons OpenAI started replacing the CoT with summaries, were A. to prevent rapid distillation as they suspected deepSeek to have used for R1 and B. to prevent embarrassment if App users see the CoT and find parts of it objectionable/irrelevant/absurd (reasoning steps that make sense for an LLM do not necessarily look like human reasoning). That's a tradeoff that is great with end-users but terrible for developers. As Open Weights LLMs necessarily output their full reasoning traces the potential to optimize prompts for specific tasks is much greater and will for certain applications certainly outweigh the performance delta to Google/OpenAI.

int_19h5• 8 months ago

I was under the impression that those reasoning outputs that you get back aren't references but simply raw CoT strings that are encrypted.

scrollop• 8 months ago

Here it makes a text based video editor that works:

https://youtu.be/MPjOQIQO8eQ?si=wcrCSLYx3LjeYDfi&t=797

mpeg2• 8 months ago

Well, it just found a bug in one shot that Gemini 2.5 and GPT5 failed to find in relatively long sessions. Claude 4.5 had found it but not one shot.

Very subjective benchmark, but it feels like the new SOTA for hard tasks (at least for the next 5 minutes until someone else releases a new model)

tylervigen4• 8 months ago

I am personally impressed by the continued improvement in ARC-AGI-2, where Gemini 3 got 31.1% (vs ChatGPT 5.1's 17.6%). To me this is the kind of problem that does not lend itself well to LLMs - many of the puzzles test the kind of thing that humans intuit because of millions of years of evolution, but these concepts do not necessarily appear in written form (or when they do, it's not clear how they connect to specific ARC puzzles).

The fact that these models can keep getting better at this task given the setup of training is mind-boggling to me.

The ARC puzzles in question: https://arcprize.org/arc-agi/2/

grantpitt• 8 months ago

Agreed, it also leads performance on arc-agi-1. Here's the leaderboard where you can toggle between arc-agi-1 and 2: https://arcprize.org/leaderboard

energy1237• 8 months ago

It leads on arc-agi-1 with Gemini 3.0 Deep Think, which uses "tool calls" according to google's post, whereas regular Gemini 3.0 Pro doesn't use "tool calls" for the same benchmark. I am unsure how significant this difference is.

stephc_int136• 8 months ago

What I would do if I was in the position of a large company in this space is to arrange an internal team to create an ARC replica, covering very similar puzzles and use that as part of the training.

Ultimately, most benchmarks can be gamed and their real utility is thus short-lived.

But I think this is also fair to use any means to beat it.

tylervigen4• 8 months ago

I agree that for any given test, you could build a specific pipeline to optimize for that test. I supposed that's why it is helpful to have many tests.

However, many people have worked hard to optimize tools specifically for ARC over many years, and it's proven to be a particularly hard test to optimize for. This is why I find it so interesting that LLMs can do it well at all, regardless of whether tests like it are included in training.

simpsond• 8 months ago

Humans study for tests. They just tend to forget.

AstroBen6• 8 months ago

Is "good at benchmarks instead of real world tasks" really something to optimize for? What does this achieve? Surely people would be initially impressed, try it out, be underwhelmed and then move on. That's not great for Google

riku_iki2• 8 months ago

internal team to create an ARC replica, covering very similar puzzles

they can target benchmark directly, not just replica. If google or OAI are bad actors, they already have benchmark data from previous runs.

Blamklmo• 8 months ago

Doesn't even matter at this point.

We have a global RL Pipeline on our hand.

If there is something new a LLM/AI model can't solve today, plenty of humans can't either.

But tomorrow every LLM/AI model can solve it and again plent of humans still can't.

Even if AGI is just the sum of companies adding more and more trainingdata, as long as this learning pipeline becomes faster and easier to train with new scenarios, that will start to bleed out humans in the loop.

benlivengood• 8 months ago

That's ok; just start publishing your real problems to solve as "AI benchmarks" and then it'll work in ~6 months.

nbardy• 8 months ago

This isn’t gaming the benchmark though. If training on similar data generalizes that’s called learning. Training on the exact set is memorization.

There is for a fact teams creating puzzles to RL against as training environments. As it’s beneficial to RL training and in particular compute efficient if you schedule the environment difficulty throughout training. There was a great recent paper on this. Creating environment data that generalizes outside the environment is a challenging engineering task and super valuable whether it looks like AGC AGI or not.

Also ARC AGI is general enough that if you create similar data you’re just creating generic visual puzzle data. Should all visual puzzle data be off limits ?

tylervigen4• 8 months ago

This comment was moved from another thread. The original thread included a benchmark chart with ARC performance: https://blog.google/products/gemini/gemini-3/#gemini-3

HarHarVeryFunny3• 8 months ago

There's a good chance Gemini 3 was trained on ARG-AGI problems, unless they state otherwise.

knowriju• 8 months ago

ARC-AGI has a hidden private test suite, right ? No model will have access to that set.

ld4nt33• 8 months ago

Its almost certain that it was, but the purpose of this puzzle benchmark is that it shouldn't really be possible just to be memorized by the amount of variations that can be created and other criteria detailed in it.

m3kw94• 8 months ago

that looks great, but we all care how it translate to real world problems like programming where it isn't really excelling by 2x.

jordanpg• 8 months ago

What is Gemini 3 under the hood? Is it still just a basic LLM based on transformers? Or are there all kinds of other ML technologies bolted on now? I feel like I've lost the plot.

meowface3• 8 months ago

I am very ignorant in this field but I am pretty sure under the hood they are all still fundamentally built on the transformer architecture, or at least innovations on the original transformer architecture.

anilgulecha• 8 months ago

It's a mixture-of-experts model. Basically N smaller model pieces put together, and when inference occurs, only 1 is active at a time. Each model piece would be tuned/good in one area.

becquerel• 8 months ago

The industry is still seeing how far they can take transformers. We've yet to reach a dollar value where it stops being worth pumping money into them.

dankobgd• 8 months ago

every day, new game changer

hubraumhugo• 8 months ago

No gemini-3-flash yet, right? Any ETA on that mentioned? 2.5-flash has been amazing in terms of cost/value ratio.

8note2• 8 months ago

ive found gemini 2.5-flash works better (for.agentic coding) than pro, too

casey2• 8 months ago

The first paragraph is pure delusion. Why do investors like delusional CEOs so much? I would take it as a major red flag.

clusterhacks2• 8 months ago

I wish I could just pay for the model and self-host on local/rented hardware. I'm incredibly suspicious of companies totally trying to capture us with these tools.

lfx2• 8 months ago

Technically you can!

I haven't seen it in the box yet, and pricing is unknown https://cloud.google.com/blog/products/ai-machine-learning/r...

clusterhacks2• 8 months ago

That's interesting. While I suspect the pricing will lean heavily into enterprise sales rather than personal licenses, I personally like the idea buying models that I then own and control. Any steps from companies that make that more possible is great.

slackerIII• 8 months ago

What's the easiest way to set up automatic code review for PRs for my team on GitHub using this model?

esafak3• 8 months ago

https://github.com/marketplace/gemini-code-assist

colechristensen• 8 months ago

Ask it.

If it's good enough to be useful on your code base, it better be good enough to instruct you on how to use it.

How easy it is depends on whether or not they've built that kind of thing in

qustrolabe• 8 months ago

Out of all other companies Google provide the most generous free access so far. I bet this gives them plenty of data to train even better models

serjester• 8 months ago

It's disappointing there's no flash / lite version - this is where Google has excelled up to this point.

aoeusnth12• 8 months ago

Maybe they're slow rolling the announcements to be in the news more

coffeebeqn• 8 months ago

Most likely. And/or they use the full model to train the smaller ones somehow

icapybara• 8 months ago

Anyone know how Gemini CLI with this model compares to Codex and Claude Code?

dwringer2• 8 months ago

Well, I tried a variation of a prompt I was messing with in Flash 2.5 the other day in a thread about AI-coded analog clock faces. Gemini Pro 3 Preview gave me a result far beyond what I saw with Flash 2.5, and got it right in a single shot.[0] I can't say I'm not impressed, even though it's a pretty constrained example.

Please generate an analog clock widget, synchronized to actual system time, with hands that update in real time and a second hand that ticks at least once per second. Make sure all the hour markings are visible and put some effort into making a modern, stylish clock face. Please pay attention to the correct alignment of the numbers, hour markings, and hands on the face.

[0] https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...

thegrim33• 8 months ago

"Allow access to Google Drive to load this Prompt."

.... why? For what possible reason? No, I'm not going to give access to my privately stored file share in order to view a prompt someone has shared. Come on, Google.

LiamPowell• 8 months ago

You don't want to give Google access to files you've stored in Google Drive? It's also only access to an application specific folder, not all files.

lxgr• 8 months ago

Because most likely (at least according to Hanlon's razor) they somehow decided that using Google Drive as the only persistent storage backing AI studio was a reasonable UX decision.

It probably makes some sense internally in big tech corporation logic (no new data storage agreements on top of the ones the user has already agreed to when signing up for Drive etc.), but as a user, I find it incredibly strange too – especially since the text chats are in some proprietary format I can't easily open on my local GDrive replica, but the images generated or uploaded just look like regular JPEGs and PNGs.

dragonwriter3• 8 months ago

I'm assuming because AI Studio persisted, including shared, prompts are stored in Drive, and prompt sharing is implemented on top of Drive file sharing, so if AI Studio doesn't have access to Drive it doesn't have access to the shared prompt.

dyauspitr2• 8 months ago

Having seen the page the other day this is pretty incredible. Does this have the same 2000 token limit as the other page?

dwringer2• 8 months ago

This isn't using the same prompt or stack as the page from that post the other day; on aistudio it builds a web app across a few different files. It's still fairly concise but I don't think it's that much so.

Taek• 8 months ago

No, and also the other page was pure HTML and CSS. This clock is using React and Javascript, so it's not a fair comparison.

pmarreck3• 8 months ago

holy shit! This is actually a VERY NICE clock!

stalfie3• 8 months ago

The subtle "wiggle" animation that the second hand makes after moving doesn't fire when it hits 12. Literally unwatchable.

apetresc• 8 months ago

In its defence, the code actually specifically calls that edge case out and justifies it:

    // Calculate rotations
    // We use a cumulative calculation logic mentally, but here simple degrees work because of the transition reset trick or specific animation style.
    // To prevent the "spin back" glitch at 360->0, we can use a simple tick without transition for the wrap-around,
    // but for simplicity in this specific React rendering, we will stick to standard 0-360 degrees.
    // A robust way to handle the spin-back on the second hand is to accumulate degrees, but standard clock widgets often reset.

skipnup• 8 months ago

The Swiss and German railway clocks actually work the same way and stop for (half a?) second while the minute handle progresses.

https://youtu.be/wejbVtj4YR0

scotty79• 8 months ago

Fixed with prompt "Second hand doesn't shake when it lands on 12, fix it." and 131 seconds. With a bunch of useState()-s and a useEffet()

skybrian• 8 months ago

It looks quite nice, though to nitpick, it has “quartz” and “design & engineering” for no reason.

wongarsu• 8 months ago

Just like actual cheap but not bottom of the barrel clocks

xnx9• 8 months ago

This is cool. Gemini 2.5 Pro was also capable of this. Gemini was able to recreate famous piece of clock artwork in July: https://gemini.google.com/app/93087f373bd07ca2

"Against the Run": https://www.youtube.com/watch?v=7xfvPqTDOXo

farazbabar• 8 months ago

https://ai.studio/apps/drive/1yAxMpwtD66vD5PdnOyISiTS2qFAyq1... <- this is very nice, I was able to make seconds smooth with three iterations (it used svg initially which was jittery, but eventually this).

kjgkjhfkjf2• 8 months ago

This is quite likely to be in the training data, since it's one of the projects in Wes Bos's free 30 days of Javascript course[0].

[0] https://javascript30.com/

baxtr• 8 months ago

I was under the impression for this to work like that, training data needs to be plenty. One project is not enough since it’s too "sparse".

But maybe this example was used by many other people and so it proliferated?

pmarreck3• 8 months ago

https://ai.studio/apps/drive/1oGzK7yIEEHvfPqxBGbsue-wLQEhfTP...

I made a few improvements... which all worked on the first try... except the ticking sound, which worked on the second try (the first try was too much like a "blip")

malfist2• 8 months ago

That is not the same prompt as the other person was using. In particular this doesn't provide the time to set the clock to, which makes the challenge a lot simpler. This also includes javascript.

The prompt the other person was using is:

``` Create HTML/CSS of an analog clock showing ${time}. Include numbers (or numerals) if you wish, and have a CSS animated second hand. Make it responsive and use a white background. Return ONLY the HTML/CSS code with no markdown formatting. ```

Which is much more difficult.

For what it's worth, I supplied the same prompt as the OG clock challenge and it utterly failed, not only generating a terrible clock, but doing so with a fair bit of typescript: https://ai.studio/apps/drive/1c_7C5J5ZBg7VyMWpa175c_3i7NO7ry...

irthomasthomas8• 8 months ago

URL not found :(

kldg• 8 months ago

in defense of 2.5 (Pro, at least), it was able to generate for me a metric UNIX clock as a webpage which I was amused by. it uses kiloseconds/megaseconds/etc. there are 86.4ks/day. The "seconds" hand goes around 1000 seconds, which ticks over the "hour" hand. Instead of saying 4am, you'd say it's 14.

as a calendar or "date" system, we start at UNIX time's creation, so it's currently 1.76 gigaseconds AUNIX. You might use megaseconds as the "week" and gigaseconds more like an era, e.g. Queen Elizabeth III's reign, persisting through the entire fourth gigasecond and into the fifth. The clock also displays teraseconds, though this is just a little purple speck atm. of course, this can work off-Earth where you would simply use 88.775ks as the "day"; the "dates" a Martian and Earthling share with each other would be interchangeable.

I can't seem to get anyone interested in this very serious venture, though... I guess I'll have to wait until the 50th or so iteration of Figure, whenever it becomes useful, to be able to build a 20-foot-tall physical metric UNIX clock in my front yard.

siva7• 8 months ago

I have my own private benchmarks for reasoning capabilities on complex problems and i test them against SOTA models regularly (professional cases from law and medicine). Anthropic (Sonnet 4.5 Extended Thinking) and OpenAI (Pro Models) get halfway decent results on many cases while Gemini Pro 2.5 struggled (it was overconfident in its initial assumptions). So i ran these benchmarks against Gemini 3 Pro and i'm not impressed. The reasoning is way more nuanced than their older model but it still makes mistakes which the other two SOTA competitor models don't make. Like it forgets in a law benchmark that those principles don't apply in the country from the provided case. It seems very US centric in its thinking whereas Anthropic and OpenAI pro models seem to be more aware around the context of assumed culture from the case. All in - i don't think this new model is ahead of the other two main competitors - but it has a new nuanced touch and is certainly way better than Gemini 2.5 pro (which is more telling how bad actually that one was for complex problems).

MaxL93• 8 months ago

It seems very US centric in its thinking

I'm not surprised. I'm French and one thing I've consistently seen with Gemini is that it loves to use Title Case (Everything is Capitalized Except the Prepositions) even in French or other languages where there is no such thing. A 100% american thing getting applied to other languages by the sheer power of statistical correlation (and probably being overtrained on USA-centric data). At the very least it makes it easy to tell when someone is just copypasting LLM output into some other website.

mpalmer2• 8 months ago

Title Case (Everything is Capitalized Except the Prepositions)

If this is an American thing I'm happy to disown/denounce it; it's my least favorite pattern in Gemini output.

irthomasthomas8• 8 months ago

I asked it to summarize an article about the Zizians which mentions Yudkowsky SEVEN times. Gemini-3 did not mention him once. Tried it ten times and got zero mention of Yudkowsky, despite him being a central figure in the story. https://xcancel.com/xundecidability/status/19908286970881311...

Also, can you guess which pelican SVG was gemini 3 vs 2.5? https://xcancel.com/xundecidability/status/19908113191723213...

gregsadetsky6• 8 months ago

Interesting, yeah! Just tried "summarize this story and list the important figures from it" with Gemini 2.5 Pro and 3 and they both listed 10 names each, but without including Yudkowsky.

Asking the follow up "what are ALL the individuals mentioned in the story" results in both models listing ~40 names and both of those lists include Yudkowsky.

briga2• 8 months ago

Maybe it has guard rails against such things? That would be my main guess on the Zizian one.

stickfigure2• 8 months ago

He's not a central figure in the narrative, he's a background character. Things he created (MIRI, CFAR, LessWrong) are important to the narrative, the founder isn't. If I had to condense the article, I'd probably cut him out too. Summarization is inherently lossy.

irthomasthomas8• 8 months ago

  > Eliezer Yudkowsky is a central figure in the article, mentioned multiple times as the intellectual originator of the community from which the "Zizians" splintered. His ideas and organizations are foundational to the entire narrative.

alach11• 8 months ago

This is a really impressive release. It's probably the biggest lead we've seen from a model since the release of GPT-4. Seems likely that OpenAI rushed out GPT-5.1 to beat the Gemini 3 release, knowing that their model would underperform it.

m3kw94• 8 months ago

If it ain't quantum leap, new models are just "OS updates".

sunaookami• 8 months ago

Gemini CLI crashes due to this bug: https://github.com/google-gemini/gemini-cli/issues/13050 and when applying the fix in the settings file I can't login with my Google account due to "The authentication did not complete successfully. The following products are not yet authorized to access your account" with useless links to completely different products (Code Assist).

Antigravity uses Open-VSX and can't be configured differently even though it says it right there (setting is missing). Gemini website still only lists 2.5 Pro. Guess I will just stick to Claude.

bityard• 8 months ago

Whether you’re an experienced developer or a vibe coder

I absolutely LOVE that Google themselves drew a sharp distinction here.

rafaquintanilha2• 8 months ago

You realize this is copy to attract more people to the product, right?

jstummbillig4• 8 months ago

How could they.

WXLCKNO• 8 months ago

Valve could learn from Google here

pflenker• 8 months ago

Since then, it’s been incredible to see how much people love it. AI Overviews now have 2 billion users every month.

Come on, you can’t be serious.

muzani• 8 months ago

This is so disingenuous that it hurts the credibility of the whole thing.

XCSme• 8 months ago

How's the pelican?

briga2• 8 months ago

Every big new model release we see benchmarks like ARC and Humanity's Last Exam climbing higher and higher. My question is, how do we know that these benchmarks are not a part of the training set used for these models? It could easily have been trained to memorize the answers. Even if the datasets haven't been copy pasted directly, I'm sure it has leaked onto the internet to some extent.

But I am looking forward to trying it out. I find Gemini to be great as handling large-context tasks, and Google's inference costs seem to be among the cheapest.

stephc_int136• 8 months ago

Even if the benchmark themselves are kept secret, the process to create them is not that difficult and anyone with a small team of engineers could make a replica in their own labs to train their models on.

Given the nature of how those models work, you don't need exact replicas.

poemxo• 8 months ago

It's amazing to see Google take the lead while OpenAI worsens their product every release.

vivzkestrel2• 8 months ago

has anyone managed to use any of the AI models to build a complete 3D fps game using web GL or open GL?

kridsdale32• 8 months ago

I made a webgl copy of wolfenstein with prompt engineering in browser-based "Make a website" tool that was gemini-powered.

vivzkestrel2• 8 months ago

mind sharing what tool that was that lets you run gemini on the browser in interactive mode to make games?

lairv2• 8 months ago

Out of curiosity, I gave it the latest project euler problem published on 11/16/2025, very likely out of the training data

Gemini thought for 5m10s before giving me a python snippet that produced the correct answer. The leaderboard says that the 3 fastest human to solve this problem took 14min, 20min and 1h14min respectively

Even thought I expect this sort of problem to very much be in the distribution of what the model has been RL-tuned to do, it's wild that frontier model can now solve in minutes what would take me days

orly013• 8 months ago

Wow. Sounds pretty impressive.

qsort4• 8 months ago

To be fair a lot of the impressive Elo scores models get are simply due to the fact that they're faster: many serious competitive coders could get the same or better results given enough time.

But seeing these results I'd be surprised if by the end of the decade we don't have something that is to these puzzles what Stockfish is to chess. Effectively ground truth and often coming up with solutions that would be absolutely ridiculous for a human to find within a reasonable time limit.

nerdsniper3• 8 months ago

I’d love if anyone could provide examples of such AND(“ground truth”, “absolutely ridiculous”) solutions! Even if they took clever humans a long time to create.

I’m curious to explore such fun programming code. But I’m also curious to explore what knowledgeable humans consider to be both “ground truth” as well as “absolutely ridiculous” to create within the usual time constraints.

vjerancrnjak• 8 months ago

How are they faster? I don’t think any ELO report actually comes from participating at a live coding contest on previously unseen problems.

thomasahle4• 8 months ago

I tried it with gpt-5.1 thinking, and it just searched and found a solution online :p

lairv2• 8 months ago

Is there a solution to this exact problem, or to related notions (renewal equation etc.)? Anyway seems like nothing beats training on test

thomasahle4• 8 months ago

I also used Gemini 3 Pro Preview. It finished it 271s = 4m31s.

Sadly, the answer was wrong.

It also returned 8 "sources", like stackexchange.com, youtube.com, mpmath.org, ncert.nic.in, and kangaroo.org.pk, even though I specifically told it not to use websearch.

Still a useful tool though. It definitely gets the majority of the insights.

Prompt: https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...

JBiserkov2• 8 months ago

The requested prompt does not exist or you do not have access. If you believe the request is correct, make sure you have first allowed AI Studio access to your Google Drive, and then ask the owner to share the prompt with you.

pennaMan• 8 months ago

It also returned 8 "sources"

well, there's your problem. it behaves like a search summary tool and not like a problem solver if you enable google search

TechDebtDevin5• 8 months ago

Why is this sad. You should bw rooting for these LLMs to be as bad as possible..

nomilk• 8 months ago

Terrence Tao claims [0] contributions by the public are counter-productive since the energy required to check a contribution outweighs its benefit:

(for) most research projects, it would not help to have input from the general public. In fact, it would just be time-consuming, because error checking

Since frontier LLMs make clumsy mistakes, they may fall into this category of 'error-prone' mathematician whose net contributions are actually negative, despite being impressive some of the time.

[0] https://www.youtube.com/watch?v=HUkBz-cdB-k&t=2h59m33s

id• 8 months ago

gpt-5.1 gave me the correct answer after 2m 17s. That includes retrieving the Euler website. I didn't even have to run the Python script, it also did that.

sedatk• 8 months ago

Just to clarify the context for future readers: the latest problem at the moment is #970: https://projecteuler.net/problem=970

tails4e3• 8 months ago

I just had chatgpt explain that problem to me (I was unfamiliar with the mathematical background). It showed how to solve closed form answers for H(2) and H(3) and then numerical solutions using RK4 for higher values. Truly impressive, and it explained the derivations beautifully. There are few maths experts I've encountered who could have hand-held me through it as good.

j2kun• 8 months ago

Did it search the web?

rbjorklin• 8 months ago

Your post made me curious to try a problem I have been coming back to ever since ChatGPT was first released: https://open.kattis.com/problems/low

I have had no success using LLM's to solve this particular problem until trying Gemini 3 just now despite solutions to it existing in the training data. This has been my personal litmus test for testing out LLM programming capabilities and a model finally passed.

kenjackson• 8 months ago

ChatGPT solves this problem now as well with 5.1. Time for a new litmus test.

irthomasthomas8• 8 months ago

Are you sure it did not retrieve the answer using websearch?

bumling• 8 months ago

I asked Grok to write a Python script to solve this and it did it in slightly under ten minutes, after one false start where I'd asked it using a mode that doesn't think deeply enough. Impressive.

jamilton• 8 months ago

Yeah, LLMs used to not be up to par for new Project Euler problems, but GPT-5 was able to do a few of the recent ones which I tried a few weeks ago.

bgwalter2• 8 months ago

Does it matter if it is out of the training data? The models integrate web search quite well.

What if they have an internal corpus of new and curated knowledge that is constantly updated by humans and accessed in a similar manner? It could be active even if web search is turned off.

They would surely add the latest Euler problems with solutions in order to show off in benchmarks.

NaomiLehman5• 8 months ago

you can disable search.

just create a different problem if you don't believe it.

panarky2• 8 months ago

[flagged]

legel• 8 months ago

Thanks for reporting these metrics and drawing the conclusion of an underlying breakthrough in search.

In his Nobel Prize winning speech, Demis Hassabis ends by discussing how he sees all of intelligence as a big tree-like search process.

https://youtube.com/watch?v=YtPaZsasmNA&t=1218

vitorgrs• 8 months ago

I usually ask a simple question that ALL the models get wrong: List of mayor of my city [Londrina]. ALL the models (offine) get wrong. And I mean, all the models. The best that I could, it's o3 I believe, saying it couldn't give a good answer for that, and told to access the city website.

Gemini 3 somehow is able to give a list of mayors, including details on who got impeached, etc.

This should be a simple answer, because all the data is on wikipedia, that certainly the models are trained on, but somehow most models don't manage to give that answer right, because... it's just a irrelevant city in a huge dataset.

But somehow, Gemini 3 did it.

Edit: Just asked "Cool places to visit in Londrina" (In portuguese), and it was also 99% right, unlike other models, who just create stuff. The only thing wrong here, it mentioned sakuras in a lake... Maybe it confused with Brazilian ipês, which are similar, and indeed the city it's full of them.

It seems to have a visual understanding, imo.

rafaelmn• 8 months ago

It tells me that the benchmark is probably leaking into training data, and going to the benchmark site :

Model was published after the competition date, making contamination possible.

Aside from eval on most of these benchmarks being stupid most of the time, these guys have every incentive to cheat - these aren't some academic AI labs, they have to justify hundreds of billions being spent/allocated in the market.

Actually trying the model on a few of my daily tasks and reading the reasoning traces all I'm seeing is same old, same old - Claude is still better at "getting" the problem.

Der_Einzige2• 8 months ago

You clearly AI generated this comment.

thomasahle4• 8 months ago

From my understanding, Google put online the largest RL cluster in the world not so long ago. It's not surprising they do really well on things that are "easy" to RL, like math or SimpleQA

red75prime3• 8 months ago

To succeed this well in math, you can't just do better probabilistic generation, you need verifiable search.

You say "probabilistic generation" like it's some kind of a limitation. What is exactly the limiting factor here? [(0.9999, "4"), (0.00001, "four"), ...] is a valid probability distribution. The sampler can be set to always choose "4" in such cases.

coldtea• 8 months ago

This is not an incremental advance. It is a step change. This indicates a new discovery, not just more data or more compute.

To succeed this well in math, you can't just do better probabilistic generation, you need verifiable search.

You need to verify what you're doing, detect when you make a mistake, and backtrack to try a different approach.

Loos like AI slop

calmoo• 8 months ago

Your comment is AI generated

dbbk• 8 months ago

Aren't you just describing tool calls?

Xss3• 8 months ago

This comment was written by an AI specifically instructed to be more concise than usual.

ivape• 8 months ago

So when does the developer admit defeat? Do we have a benchmark for that yet?

bgwalter2• 8 months ago

According to a bunch of philosophers (https://ai-2027.com/), doom is likely imminent. Kokotajlo was on Breaking Points today. Breaking Points is usually less gullible, but the top comment shows that "AI" hype strategy detection is now mainstream (https://www.youtube.com/watch?v=zRlIFn0ZIlU):

AI researcher: "Just another trillion dollars. This time we'll reach superintelligence, I swear."

lofaszvanitt4• 8 months ago

The problem is these models are optimized to solve the benchmarks, not real world problems.

motbus3• 8 months ago

We need to wait and see. According to Google they have solved AI 10 years ago with Google Duo but somehow they keep smashing records despite being the worst coding tool until Gemini 2.5. Google internal benchmarks are irrelevant

NaomiLehman5• 8 months ago

definitely uses a lot of tooling. From "thinking":

I'm now writing a Python script to automate the summation computation. I'm implementing a prime sieve and focusing on functions for Rm and Km calculation [...]

mistercheph2• 8 months ago

If using through the chat interface are these models not doing some RAG?

blubber• 8 months ago

Is this a problem for which the (human) solution is well documented an known and was learned during the training phase? Or is it a novel problem?

I personally think anthropomorphizing LLMs is a bad idea.

yomismoaqui2• 8 months ago

From an initial testing of my personal benchmark it works better than Gemini 2.5 pro.

My use case is using Gemini to help me test a card game I'm developing. The model simulates the board state and when the player has to do something it asks me what card to play, discard... etc. The game is similar to something like Magic the Gathering or Slay the Spire with card play inspired by Marvel Champions (you discard cards from your hand to pay the cost of a card and play it)

The test is just feeding the model the game rules document (markdown) with a prompt asking it to simulate the game delegating the player decisions to me, nothing special here.

It seems like it forgets rules less than Gemini 2.5 Pro using thinking budget to max. It's not perfect but it helps a lot to test little changes to the game, rewind to a previous turn changing a card on the fly, etc...

pgroves• 8 months ago

I was hoping Bash would go away or get replaced at some point. It's starting to look like it's going to be another 20 years of Bash but with AI doodads.

__MatrixMan__• 8 months ago

Nushell scratches the itch for me 95% of the time. I haven't yet convinced anybody else to make the switch, but I'm trying. Haven't yet fixed the most problematic bug for my useage, but I'm trying.

What are you doing to help kill bash?

energy1237• 8 months ago

Impressive. Although the Deep Think benchmark results are suspicious given they're comparing apples (tools on) with oranges (tools off) in their chart to visually show an improvement.

syedshahmir7214• 8 months ago

I think from last few releases of these models from all companies, I have not observed much improvements in the response of these models. Their claims and launches are a little over hyped.

nextworddev2• 8 months ago

It’s over for Anthropic. That’s why Google’s cool with Claude being on Azure.

Also probably over for OpenAI

nighwatch• 8 months ago

I just tested the Gemini 3 preview as well, and its capabilities are honestly surprising. As an experiment I asked it to recreate a small slice of Zelda , nothing fancy, just a mock interface and a very rough combat scene. It managed to put together a pretty convincing UI using only SVG, and even wired up some simple interactions.

It’s obviously nowhere near a real game, but the fact that it can structure and render something that coherent from a single prompt is kind of wild. Curious to see how far this generation can actually go once the tooling matures.

crawshaw• 8 months ago

Has anyone who is a regular Opus / GPT5-Codex-High / GPT5 Pro user given this model a workout? Each Google release is accompanied by a lot of devrel marketing that sounds impressive but whenever I put the hours into eval myself it comes up lacking. Would love to hear that it replaces another frontier model for someone who is not already bought into the Gemini ecosystem.

film42• 8 months ago

At this point I'm only using google models via Vertex AI for my apps. They have a weird QoS rate limit but in general Gemini has been consistently top tier for everything I've thrown at it.

Anecdotal, but I've also not experienced any regression in Gemini quality where Claude/OpenAI might push iterative updates (or quantized variants for performance) that cause my test bench to fail more often.

gordonhart• 8 months ago

Matches my experience exactly. It's not the best at writing code but Gemini 2.5 Pro is (was) the hands-down winner in every other use case I have.

This was hard for me to accept initially as I've learned to be anti-Google over the years, but the better accuracy was too good to pass up on. Still expecting a rugpull eventually — price hike, killing features without warning, changing internal details that break everything — but it hasn't happened yet.

Szpadel• 8 months ago

I gave it a spin with instructions that worked great with gpt-5-codex (5.1 regressed a lot so I do not even compare to it).

Code quality was fine for my very limited tests but I was disappointed with instruction following.

I tried few tricks but I wasn't able to convince it to first present plan before starting implementation.

I have instructions describing that it should first do exploration (where it tried to discover what I want) then plan implementation and then code, but it always jumps directly to code.

this is bug issue for me especially because gemini-cli lacks plan mode like Claude code.

for codex those instructions make plan mode redundant.

m3kw94• 8 months ago

just say "don't code yet" at the end. I never use plan mode because plan mode is just a prompt anyways.

Narciss2• 8 months ago

I've been working with it, and so far it's been very impressive. Better than Opus in my feels, but I have to test more, it's super early days

mewpmewp22• 8 months ago

What I usually try to test with is try to get them do full scalable SaaS application from scratch... It seemed very impressive in how it did the early code organization using Antigravity, but then at some point, all of sudden it started really getting stuck and constantly stopped producing and I had to trigger continue, or babysit it. I don't know if I could've been doing something better, but that was just my experience. Seemed impressive at first, but otherwise at least vs Antigravity, Codex and Claude Code scale more reliably.

Just early anecdote from trying to build that 1 SaaS application though.

mmaunder• 8 months ago

Yes. I am. It is spectacular in raw cognitive horsepower. Smarter than gpt5-codex-high but Gemini CLI is still buggy as hell. But yes, 3 has been a game changer for me today on hardcore Rust, CUDA and Math projects. Unbelievable what they’ve accomplished.

eknkc• 8 months ago

Looks like it is already available on VSCode Copilot. Just tried a prompt that was not returning anything good on Sonnet 4.5. (Did not spend much time though, but the prompth was already there on the chat screen so I switched the model and sent it again)

Gemini 3 worked much better and I actually committed the changes that it created. I don't mean its revolutionary or anything but it provided a nice summary of my request and created a decent simple solution. Sonnet had created a bunch of overarching changes that I would not even bother reviewing. Seems nice. Will probably use it for 2 weeks until someone else releases a 1.0001x better model.

flyinglizard• 8 months ago

You were probably stuck at some local model minima avoidable by simply changing the model to something else.

zone4112• 8 months ago

Sets a new record on the Extended NYT Connections benchmark: 96.8 (https://github.com/lechmazur/nyt-connections/).

Grok 4 is at 92.1, GPT-5 Pro at 83.9, Claude Opus 4.1 Thinking 16K at 58.8.

Gemini 2.5 Pro scored 57.6, so this is a huge improvement.

dudeinhawaii• 8 months ago

Gemini has been so far behind agentically it's comical. I'll be giving it a shot but it has a herculean task ahead of itself. It has to not only be "good enough" but a "quantum leap forward".

That said, OpenAI was in the same place earlier in the year and very quickly became the top agentic platform with GPT-5-Codex.

The AI crowd is surprisingly not sticky. Coders quickly move to whatever the best model is.

Excited to see Gemini making a leap here.

catigula3• 8 months ago

Claude is still a better agent for software professionals though it is less capable, so there isn't nothing to having the incumbent advantage.

lifty• 8 months ago

Not my experience. Codex is the top coding model in my experience and has been since it’s out. Makes fewer mistakes and understands better my intentions.

ryandrake• 8 months ago

I don't even know what the fuck "agentic" is or why the hell I would want it all over my software. So tired of everything in the computing world today.

esafak3• 8 months ago

Prompting, planning, iteration, coding, and tool use over an entire code base until a problem is solved.

ur-whale3• 8 months ago

So tired of everything in the computing world today.

That's actually sad, and if you're - like I am - long in the tooth in computer land, you should definitely try agentic in CLI mode.

I haven't been that excited to play with a computer in 30 years.

SchemaLoad4• 8 months ago

As far as I can tell, it just means giving the LLM the ability to run commands, read files, edit files, and run in a loop until some goal is achieved. Compared to chat interfaces where you just input text and get one response back.

aerhardt• 8 months ago

Combining structured outputs with search is the API feature I was looking for. Honestly crazy that it wasn’t there to start with - I have a project that is mostly Gemini API but I’ve had to mix in GPT-5 just for this feature.

I still use ChatGPT and Codex as a user but in the API project I’ve been working on Gemini 2.5 Pro absolutely crushed GPT-5 in the accuracy benchmarks I ran.

As it stands Gemini is my de facto standard for API work and I’ll be following very closely the performance of 3.0 in coming weeks.

syspec2• 8 months ago

I have "unlimited" access to both Gemini 2.5 Pro and Claude 4.5 Sonnet through work.

From my experience, both are capable and can solve nearly all the same complex programming requests, but time and time again Gemini spits out reams and reams of code so over engineered, that totally works, but I would never want to have to interact with.

When looking at the code, you can't tell why it looks "gross", but then you ask Claude to do the same task in the same repo (I use Cline, it's just a dropdown change) and the code also works, but there's a lot less of it and it has a more "elegant" feeling to it.

I know that isn't easy to capture in benchmarks, but I hope Gemini 3.0 has improved in this regard

jmkni• 8 months ago

I can relate to this, it's doing exactly what I want, but it ain't pretty.

It's fine though if you take the time to learn what it's doing and write a nicer version of it yourself

poyu• 8 months ago

    but I would never want to have to interact with

That is its job security ;)

eitally• 8 months ago

I have had a similar experience vibe coding with Copilot (ChatGPT) in VSCode, against the Gemini API. I wanted to create a dad joke generator and then have it also create a comic styled 4 cel interpretation of the joke. Simple, right? I was able to easily get it to create the joke, but it repeatedly failed on the API call for the image generation. What started as perhaps 100 lines of total code in two files ended up being about 1500 LOC with an enormous built-in self-testing mechanism ... and it still didn't work.

plaidfuji• 8 months ago

I have the same experience with Gemini, that it’s incredibly accurate but puts in defensive code and error handling to a fault. It’s pretty easy to just tell it “go easy on the defensive code” / “give me the punchy version” and it cleans it up

joegibbs• 8 months ago

Yes the defensive code is something that most models seem to struggle with - even Claude 4.5 Sonnet, even after explicitly prompting it not to - still adds pointless null checks and fallbacks in scripting languages where that something being null won't have any problems apart from an error being logged. I get this particularly when writing Angelscript for Unreal. This isn't surprising since as a niche language there's a lack of training data and the syntax is very similar to Unreal C++, which does crash to desktop when accessing a null reference.

SXX7• 8 months ago

Static Pelican is boring. First attempt:

Generate SVG animation of following:

1 - There is High fantasy mage tower with a top window a dome

2 - Green goblin come in front of tower with a torch

3 - Grumpy old mage with beard appear in a tower window in high purple hat

4 - Mage sends fireball that burns goblin and all screen is covered in fire.

Camera view must be from behind of goblin back so we basically look at tower in front of us:

https://codepen.io/Runway/pen/WbwOXRO

Rudybega2• 8 months ago

Holy crap. That's actually kind of incredible for a first attempt.

sosodev3• 8 months ago

Wow, that's very impressive

SXX7• 8 months ago

After few more attempts longer animation with a story from my gamedev inspired mind:

https://codepen.io/Runway/pen/zxqzPyQ

PS: but yeah thats attempt #20 or something.

fatty_patty89• 8 months ago

Seizure warning for the above link

edit: flashing lights at the end seem to be mostly becauseo f darkreader extension

fromwilliam• 8 months ago

This is honestly incredible

nyantaro1• 8 months ago

we are so cooked

arjie• 8 months ago

This is bloody magical. I cannot believe it.

hollowturtle11• 8 months ago

Wow looks like total shit and eventually very hard to take on and actually improve it, given the convoluted code it generated, YET people are impressed. What world are we living in...

mclau153• 8 months ago

we are returning to flash animations after 20 years

KingMob3• 8 months ago

Nature is healing!

But seriously, we lost a lot when Flash was killed. It was an era of accessible animation and games like Newgrounds and Homestar Runner, that had no ready replacement.

udkl• 8 months ago

This reminded me of https://youtube.com/playlist?list=PLSq76P-lbX8VQmtv7gcAPkqlj...

catigula3• 8 months ago

The problem with experiencing LLM releases nowadays is that it is no longer trivial to understand the differences in their vast intelligences so it takes awhile to really get a handle on what's even going on.

jennyholzer3• 8 months ago

boooooooooooooo

jennyholzer3• 8 months ago

"AI" benchmarks are and have consistently been lies and misinformation. Gemini is dead in the water.

ilaksh• 8 months ago

okay since Gemini 3 is AI mode now, I switched from the free perplexity back to google as being my search default.

DanMcInerney• 8 months ago

A 50% increase over ChatGPT 5.1 on ARC-AGI2 is astonishing. If that's true and representative (a big if), it lends credence to this being the first of the very consistent agentically-inclined models because it's able to follow a deep tree of reasoning to solve problems accurately. I've been building agents for a while and thus far have had to add many many explicit instructions and hardcoded functions to help guide the agents in how to complete simple tasks to achieve 85-90% consistency.

puttycat• 8 months ago

Where is this figure taken from?

machiaweliczny3• 8 months ago

I think it's due to improvements in vision basically, the arc agi 2 is very visual

machiaweliczny3• 8 months ago

Vision is very far from solved IMO, simple modifications to inputs results in high differences still, lines aren't recognized etc..

zone4112• 8 months ago

Sets a new record on the Extended NYT Connections: 96.8. Gemini 2.5 Pro scored only 57.6. https://github.com/lechmazur/nyt-connections/

CephalopodMD• 8 months ago

What I'm getting from this thread is that people have their own private benchmarks. It's almost a cottage industry. Maybe someone should crowd source those benchmarks, keep them completely secret, and create a new public benchmark of people's private AGI tests. All they should release for a given model is the final average score.

JacobiX2• 8 months ago

Tested it on a bug that Claude and ChatGPT Pro struggled with, it nailed it, but only solved it partially (it was about matching data using a bipartite graph). Another task was optimizing a complex SQL script: the deep-thinking mode provided a genuinely nuanced approach using indexes and rewriting parts of the query. ChatGPT Pro had identified more or less the same issues. For frontend development, I think it’s obvious that it’s more powerful than Claude Code, at least in my tests, the UIs it produces are just better. For backend development, it’s good, but I noticed that in Java specifically, it often outputs code that doesn’t compile on the first try, unlike Claude.

skrebbel• 8 months ago

it nailed it, but only solved it partially

Hey either it nailed it or it didn't.

joaogui12• 8 months ago

Probably figured out the exact cause of the bug but not how to solve it

JacobiX2• 8 months ago

Yes; they nailed the root case but the implementation is not 100% correct

AstroBen6• 8 months ago

First impression is I'm having a distinctly harder time getting this to stick to instructions as compared to Gemini 2.5

mrinterweb• 8 months ago

Hit the Gemini 3 quota on the second prompt in antigravity even though I'm a pro user. I highly doubt I hit a context window based on my prompt. Hopefully, it is just first day of near general availability jitters.

BoorishBears6• 8 months ago

So they won't release multimodal or Flash at launch, but I'm guessing people who blew smoke up the right person's backside on X are already building with it

Glad to see Google still can't get out of its own way.

BoorishBears6• 8 months ago

I don't want to be one of those assholes who only calls out when they were right: I was very wrong

oceanplexian• 8 months ago

Suspicious that none of the benchmarks include Chinese models even they scored higher on the benchmarks than the models they are comparing to?

recitedropper11• 8 months ago

Who wants to bet they benchmaxxed ARC-AGI-2? Nothing in their release implies they found some sort of "secret sauce" that justifies the jump.

Maybe they are keeping that itself secret, but more likely they probably just have had humans generate an enormous number of examples, and then synthetically build on that.

No benchmark is safe, when this much money is on the line.

HarHarVeryFunny3• 8 months ago

I'd also be curious what kind of tools they are providing to get the jump from Pro to Deep Think (with tools) performance. ARC-AGI specialized tools?

sosodev3• 8 months ago

Here's some insight from Jeff Dean and Noam Shazeer's interview with Dwarkesh Patel https://youtu.be/v0gjI__RyCY&t=7390

When you think about divulging this information that has been helpful to your competitors, in retrospect is it like, "Yeah, we'd still do it," or would you be like, "Ah, we didn't realize how big a deal transformer was. We should have kept it indoors." How do you think about that?
Some things we think are super critical we might not publish. Some things we think are really interesting but important for improving our products; We'll get them out into our products and then make a decision.

recitedropper11• 8 months ago

I'm sure each of the frontier labs have some secret methods, especially in training the models and the engineering of optimizing inference. That said, I don't think them saying they'd keep a big breakthrough secret would be evidence in this case of a "secret sauce" on ARC-AGI-2.

If they had found something fundamentally new, I doubt they would've snuck it into Gemini 3. Probably would cook on it longer and release something truly mindblowing. Or, you know, just take over the world with their new omniscient ASI :)

horhay• 8 months ago

They ran the tests themselves only on semi-private evals. Basically the same caveat as when o3 supposedly beat ARC1

testfrequency• 8 months ago

I continue to not use Gemini as I can’t have my data not trained but also have chat history at the same time.

Yes, I know the Workspaces workaround, but that’s silly.

alksdjf89243• 8 months ago

Pretty obvious how contaminated this site is with goog employees upvoting nonsense like this.

_2d303• 8 months ago

Gemini 3 is crushing my personal evals for research purposes.

I would cancel my ChatGPT sub immediately if Gemini had a desktop app and may still do so if it continues to impress my as much as it has so far and I will live without the desktop app.

It's really, really, really good so far. Wow.

Note that I haven't tried it for coding yet!

ethmarks7• 8 months ago

Genuinely curious here: why is the desktop app so important?

I completely understand the appeal of having local and offline applications, but the ChatGPT desktop app doesn't work without an internet connection anyways. Is it just the convenience? Why is a dedicated desktop app so much better than just opening a browser tab or even using a PWA?

Also, have you looked into open-webui or Msty or other provider-agnostic LLM desktop apps? I personally use Msty with Gemini 2.5 Pro for complex tasks and Cerebras GLM 4.6 for fast tasks.

_2d303• 8 months ago

I have a few reasons for the preference:

(1) The ability to add context via a local apps integration into OS level resources is big. With Claude, eg, I hit Option-SPC which brings up a prompt bar. From there, taking a screenshot that will get sent my prompt is as simple as dragging a bounding box. This is great. Beyond that, I can add my own MCP connectors and give my desktop app direct access to relevant context in a way that doesn't work via web UI. It may also be inconvenient to give context to a web UI in some case where, eg, I may have a folder of PDFs I want it to be able to reference.

(2) Its own icon that I can CMD-TAB to is so much nicer. Maybe that works with a PWA? Not really sure.

(3) Even if I can't use an LLM when offline, having access to my chats for context has been repeatedly valuable to me.

I haven't looked at provider-agnostic apps and, TBH, would be wary of them.

energy1237• 8 months ago

I would personally settle for a web app that isn't slow. The difference in speed (latency, lag) between ChatGPT's fast web app and Gemini's slow web app is significant. AI Studio is slightly better than Gemini, but try pasting in 80k tokens and then typing some additional text and see what happens.

realty_geek2• 8 months ago

I would like to try controlling my browser with this model. Any ideas how to do this. Ideally I would like something like openAI's atlas or perplexity's comet but powered by gemini 3.

ZeroCool2u• 8 months ago

Seems like their new Antigravity IDE specifically has this built in. https://antigravity.google/docs/browser

realty_geek2• 8 months ago

Wow, that is awesome.

xnx9• 8 months ago

Gemini CLI can also control a browser: https://github.com/ChromeDevTools/chrome-devtools-mcp

I_am_tiberius3• 8 months ago

I still need a google account to use it and it always asks me for a phone verification, which I don't want to give to google. That prevents me from using Gemini. I would even pay for it.

gpm2• 8 months ago

I would even pay for it.

Is it just me or is it generally the case that to pay for anything on the internet you have to enter credit card information including a phone number.

I_am_tiberius3• 8 months ago

You never have to add your phone number in order to pay.

senfiaj• 8 months ago

Haven't used Gemini much, but when I used, it often refused to do certain things that ChatGPT did happily. Probably because it has many things heavily censored. Obviously, a huge company like Google is under much heavier regulations than ChatGPT. Unfortunately this greatly reduces its usefulness in many situations despite that Google has more resources and computational power than OpenAI.

simonw4• 8 months ago

Here are my notes and pelican benchmark, including a new, harder benchmark because the old one was getting too easy: https://simonwillison.net/2025/Nov/18/gemini-3/

libraryofbabel• 8 months ago

I was interested (and slightly disappointed) to read that the knowledge cutoff for Gemini 3 is the same as for Gemini 2.5: January 2025. I wonder why they didn't train it on more recent data.

Is it possible they use the same base pre-trained model and just fine-tuned and RL-ed it better (which, of course, is where all the secret sauce training magic is these days anyhow)? That would be odd, especially for a major version bump, but it's sort of what having the same training cutoff points to?

simonw4• 8 months ago

The model card says: https://storage.googleapis.com/deepmind-media/Model-Cards/Ge...

This model is not a modification or a fine-tune of a prior model.

I'm curious why they decided not to update the training data cutoff date too.

skylurk2• 8 months ago

They've been training for months to draw that pelican, just for you to move the goalposts.

oblio5• 8 months ago

It's a pelican on a bike, not a goalpost. And bikes move. Well, pelicans move, too.

mtrovo• 8 months ago

It's interesting that you mentioned on a recent post that saturation on the pelican benchmark isn't a problem because it's easy to test for generalization. But now looking at your updated benchmark results, I'm not sure I agree. Have the main labs been climbing the Pelican on a bike hill in secret this whole time?

Thrymr• 8 months ago

Considering how many other "pelican riding a bicycle" comments there are in this thread, it would be surprising if this was not already incorporated in the training data. If not now, soon.

Workaccount28• 8 months ago

I don't think the big labs would waste their time on it. If a model is great at making the pelican but sucks at all other svg it becomes obvious. But so far the good pelicans are strong indicators of good general SVG ability.

Unless training on the pelican increases all SVG ability, then good job.

torginus• 8 months ago

Considering how important this benchmark has become to the judgement of state of the art AI models, I imagine each AI lab has a dedicated 'pelican guy', a a highly accomplished and academically credentialed person, who's working around the clock on training the model to make better and better SVG pelicans on bikes.

AstroBen6• 8 months ago

Pelican guy may be one of the last jobs to be automated

simonw4• 8 months ago

That would mean my dastardly scheme has finally come to fruition: https://simonwillison.net/2025/Nov/13/training-for-pelicans-...

tkgally3• 8 months ago

I updated my benchmark of 30 pelican-bicycle alternatives that I posted here a couple of weeks ago:

https://gally.net/temp/20251107pelican-alternatives/index.ht...

There seem to be one or two parsing errors. I'll fix those later.

hbbio2• 8 months ago

You should add ChatGPT.

I tried the first one and 5 Pro gives this: https://imgur.com/a/EhYroCE

Retr0id2• 8 months ago

it’s been incredible to see how much people love it. AI Overviews now have 2 billion users every month

Do regular users know how to disable AI Overviews, if they don't love them?

jeron• 8 months ago

it's as low tech as using adblock - select element and block

Retr0id2• 8 months ago

Blocking the UI elements probably won't stop you from contributing to Google's usage stats.

Dquiroga3• 8 months ago

I asked Gemini to write "a comment response to this thread. I want to start an intense discussion".

Gemini 3:

The cognitive dissonance in this thread is staggering.

We are sitting here cheering for a model that effectively closes the loop on Google’s total information dominance, while simultaneously training our own replacements.

Two things in this thread should be terrifying, yet are being glossed over in favor of "look at the pelican SVG":

1. *The Model Card Leak:* As user `rvz` pointed out, the leaked model card implies training on "user data... in accordance with Google's relevant terms of service." Given the recent terms updates, this essentially confirms that Gemini 3 is likely refined on the corpus of Gmail and Drive data that they’ve been hoarding for decades. We are cheering for a product sold back to us at a 60% markup (input costs up to $2.00/M) that was built on our own private correspondence.

2. *The "Agentic" Trap:* Everyone praising how `Gemini 3` solves complex bugs one-shot or handles entire PRs is missing the macro view. We aren’t looking at a productivity tool; we are looking at the devaluation of the software engineer. When the entry barrier drops to "can you prompt a seminal agent," the economic value of what we do on this forum evaporates.

Google has successfully gamified us into feeding the very beast that will make the "14-minute human solve time" (referenced by `lairv`) irrelevant. We are optimizing for our own obsolescence while paying a monopoly rent to do it.

Why is the sentiment here "Wow, cool clock widget" instead of "We just handed the keys to the kingdom to the biggest ad-tech surveillance machine in history"?

jaapz• 8 months ago

Gotta hand it to gemini, those are some top notch points

Dquiroga3• 8 months ago

yeah hahahahah, it made me think!

fwip2• 8 months ago

The "Model card leak" point is worth negative points though, as it's clearly a misreading of reality.

BoorishBears6• 8 months ago

We are cheering for a product sold back to us at a 60% markup (input costs up to $2.00/M) that was built on our own private correspondence.

That feels like something between a hallucination and an intentional fallacy that popped up because you specifically said "intense discussion". The increase is 60% on input tokens from the old model, but it's not a markup, and especially not "sold back to us at X markup".

I've seen more and more of these kinds of hallucinations as these models seem to be RL'd to not be a sycophant, they're slowly inching into the opposite direction where they tell small fibs or embellish in a way that seems like it's meant to add more weight to their answers.

I wonder if it's a form of reward hacking, since it trades being maximally accurate for being confident, and that might result in better rewards than being accurate and precise

Dquiroga3• 8 months ago

60% probably felt like a lot to Gemini. However, I liked the doomerism and how google was using our data to train its models.

Nonetheless, Gemini 3 failed this test. It failed to start a discussion. Its points were shallow, and too aiesque.

markdog123• 8 months ago

I asked it to analyze my tennis serve. It was just dead wrong. For example, it said my elbow was bent. I had to show it a still image of full extension on contact, then it admitted, after reviewing again, it was wrong. Several more issues like this. It blamed it on video being difficult. Not very useful, despite the advertisements: https://x.com/sundarpichai/status/1990865172152660047

strange_quark• 8 months ago

I’ve never seen such a huge delta between advertised capabilities and real world experience. I’ve had a lot of very similar experiences to yours with these models where I will literally try verbatim something shown in an ad and get absolutely garbage results. Do these execs not use their own products? I don’t understand how they are even releasing this stuff.

BoorishBears6• 8 months ago

The default FPS it's analyzing video at is 1, and I'm not sure the max is anywhere near enough to catch a full speed tennis serve.

markdog123• 8 months ago

Ah, I should have mentioned it was a slow motion video.

The default FPS it's analyzing video at is 1

Source?

t_minus_40• 8 months ago

is there even a puzzle or math problem gemini 3 cant solve?

kachapopopow3• 8 months ago

It's joeover for openai and antrophic. I have been using it for 3 hours now for real work and gpt-5.1 and sonnet 4.5 (thinking) does not come close.

the token efficiency and context is also mindblowing...

it feels like I am talking to someone who can think instead of a **rider that just agrees with everything you say and then fails doing basic changes, gpt-5.1 feels particulary slow and weak in real world applications that are larger than a few dozen files.

gemini 2.5 felt really weak considering the amount of data and their proprietary TPU hardware in theory allowing them way more flexibility, but gemini 3 just works and it truly understands which is something I didn't think I'd be saying for a couple more years.

beezlewax• 8 months ago

Can't wait til Gemini 4 is out!

mparis• 8 months ago

I've been playing with the Gemini CLI w/ the gemini-pro-3 preview. First impressions are that its still not really ready for prime time within existing complex code bases. It does not follow instructions.

The pattern I keep seeing is that I ask it to iterate on a design document. It will, but then it will immediately jump into changing source files despite explicit asks to only update the plan. It may be a gemini CLI problem more than a model problem.

Also, whoever at these labs is deciding to put ASCII boxes around their inputs needs to try using their own tool for a day.

People copy and paste text in terminals. Someone at Gemini clearly thought about this as they have an annoying `ctrl-s` hotkey that you need to use for some unnecessary reason.. But they then also provide the stellar experience of copying "a line of text where you then get | random pipes | in the middle of your content".

Codex figured this out. Claude took a while but eventually figured it out. Google, you should also figure it out.

Despite model supremacy, the products still matter.

dr_dshiv• 8 months ago

Make a pelican riding a bicycle in 3d: https://gemini.google.com/share/def18e3daa39

Amazing and hilarious

xnx9• 8 months ago

Similar hilarious results (one shot): https://aistudio.google.com/apps/drive/1XA4HdqQK5ixqi1jD9uMg...

vlmrun-admin2• 8 months ago

https://www.youtube.com/watch?v=cUbGVH1r_1U

side by side comparison of gemini with other models

vlmrun-admin2• 8 months ago

https://www.youtube.com/watch?v=cUbGVH1r_1U

Everyone is talking about the release of Gemini 3. The benchmark scores are incredible. But as we know in the AI world, paper stats don't always translate to production performance on all tasks.

We decided to put Gemini 3 through its paces on some standard Vision Language Model (VLM) tasks – specifically simple image detection and processing.

The result? It struggled where I didn't expect it to.

Surprisingly, VLM Run's Orion (https://chat.vlm.run/) significantly outperformed Gemini 3 on these specific visual tasks. While the industry chases the "biggest" model, it’s a good reminder that specialized agents like Orion are often punching way above their weight class in practical applications.

Has anyone else noticed a gap between Gemini 3's benchmarks and its VLM capabilities?

acoustics2• 8 months ago

Don't self-promote without disclosure.

jdthedisciple• 8 months ago

What I'd prefer over benchmarks is the answer to a simple question:

What useful thing can it demonstrably do that its predecessors couldn't?

Ridius• 8 months ago

Keep the bubble expanding for a few months longer.

BugsJustFindMe• 8 months ago

The Gemini AI Studio app builder (https://aistudio.google.com/apps) refuses to generate python files. I asked it for a website, frontend and python back end, and it only gave a front end. I asked again for a python backend and it just gives repeated server errors trying to write the python files. Pretty shit experience.

thrownaway561• 8 months ago

yea great.... when will I be able to have it dial a number on my google pixel? Seriously... Gemini absolutely sucks on pixel since it can't interact with the phone itself so it can't dial numbers.

sylware• 8 months ago

Trained models should be able to use formal tools (for instance a logical solver, a computer?).

Good. That said, I wonder if those models are still LLMs.

falcor845• 8 months ago

I love it that there's a "Read AI-generated summary" button on their post about their new AI.

I can only expect that the next step is something like "Have your AI read our AI's auto-generated summary", and so forth until we are all the way at Douglas Adams's Electric Monk:

The Electric Monk was a labour-saving device, like a dishwasher or a video recorder. Dishwashers washed tedious dishes for you, thus saving you the bother of washing them yourself; video recorders watched tedious television for you, thus saving you the bother of looking at it yourself. Electric Monks believed things for you, thus saving you what was becoming an increasingly onerous task, that of believing all the things the world expected you to believe.

- from "Dirk Gently's Holistic Detective Agency"

davedigerati• 8 months ago

Excellent reference Tried to name an AI project at work Electric Monk but too 'controversial'

Had to change to Electric Mentor....

mikepurvis• 8 months ago

SMBC had a pretty great take on this: https://www.smbc-comics.com/comic/summary

AstroBen6• 8 months ago

This feels too real to laugh at

SchemaLoad4• 8 months ago

There was another comic where one worker uses AI to turn their prompt in to a verbose email, then on the receiver side they use AI to turn the verbose email in to a short summary.

tonyhart73• 8 months ago

after outsource developer job, we can outsource all of manager job and leaving CEO with AI agentic code as its servant

aussieguy12343• 8 months ago

Not sure what you mean here, but the only real jobs at risk from AI right now are middle/upper management.

Not a single engineer has ever been laid off because of AI. Any company claiming this is the case is trying to cover up bad decisions.

"Were automating with AI" sounds better to investors than "We over hired and now need to downsize" or "We made some bad market bets, now need to free up cash flow"

xeonmc• 8 months ago

Now let’s hope that it will also save labour on resolving cloud infrastructure downtimes too.

egeozcan2• 8 months ago

I'm afraid they will finish "The Salmon of Doubt" with AI and sell it to the future generations with a very small disclaimer, stating it's inspired by Douglas Adams.

The possibility was already a topic in the series "Mozart in the jungle" where they made a robot which supposedly finished the Requiem piece by Mozart.

wartywhoa23• 8 months ago

I can only expect that the next step is something like "Have your AI read our AI's auto-generated summary"

That's basicaly "The Washing Machine Tragedy" by Stanislav Lem in a nutshell.

otikik• 8 months ago

… agentic …

Meh, not interested already

taikahessu• 8 months ago

Boring. Tried to explore sexuality related topics, but Alphabet is stuck in some Christianity Dark Ages.

Edit: Okay, I admit I'm used to dealing with OpenAI models and it seems you have to be extra careful with wording with Gemini. Once you have right wording like "explore my own sexuality" and avoid certain words, you can get it going pretty interestingly.

oezi2• 8 months ago

Probably invested a couple of billion into this release (it is great as far as I can tell), but can't bring proper UI to AI Studio for long prompts and responses (e.g. it animates new text being generated even though you just return to the tab which was finished generating).

qingcharles• 8 months ago

Somebody "two-shotted" Mario Bros NES in HTML:

https://www.reddit.com/r/Bard/comments/1p0fene/gemini_3_the_...

agentifysh• 8 months ago

my only complaint is i wish the SWE and agentic coding would have been better to justify the 1~2x premium

gpt-5.1 honestly looking very comfortable given available usage limits and pricing

although gpt-5.1 used from chatgpt website seems to be better for some reason

Sonnet 4.5 agentic coding still holding up well and confirms my own experiences

i guess my reaction to gemini 3 is a bit mixed as coding is the primary reason many of us pay $200/month for

iib• 8 months ago

As soon as I found out that this model launched, I tried giving it a problem that I have been trying to code in Lean4 (showing that quicksort preserves multiplicity). All the other frontier models I tried failed.

I used the pro version and it started out well (as they all did), but it couldn't prove it. The interesting part is that it typoed the name of a tactic, spelling it "abjel" instead of "abel", even though it correctly named the concept. I didn't expect the model to make this kind of error, because they all seems so good at programming lately, and none of the other models did, although they did some other naming errors.

I am sure I can get it to solve the problem with good context engineering, but it's interesting to see how they struggle with lesser represented programming languages by themselves.

davide_benato• 8 months ago

I would love to see how Gemini 3 can solve this particular problem. https://lig-membres.imag.fr/benyelloul/uherbert/index.html

It used to be an algorithmic game for a Microsoft student competition that ran in the mid/late 2000. The game invents a new, very simple, recursive language to move the robot (herbert) on a board, and catch all the dots while avoiding obstacles. Amazingly this clone's executable still works today on Windows machines.

The interesting thing is that there is virtually no training data for this problem, and the rules of the game and the language are pretty clear and fit into a prompt. The levels can be downloaded from that website and they are text based.

What I noticed last time I tried is that none of the publicly available models could solve even the most simple problem. A reasonably decent programmer would solve the easiest problems in a very short amount of time.

keepamovin• 8 months ago

I don't wan't to shit on the much anticipated G3 model, but I have been using it for a complex single page task and find it underwhelming. Pro 2.5 level, beneath GPT 5.1. Maybe it's launch jitters. It struggles to produce more than 700 lines of code in a single file (aistudio). It struggles to follow instructions. Revisions omit previous gains. I feel cheated! 2.5 Pro has been clearly smarter than everything else for a long time, but now 3 seems not even as good as that, in comparison to the latest releases (5.1 etc). What is going on?

bilsbie• 8 months ago

Is there a way to use this without being in the whole google ecosystem? Just make a new account or something?

mtremsal• 8 months ago

If you mean the "consumer ecosystem", then Gemini 3 should be available as an API through Google's AI Vertex platform. If you don't even want a Google Cloud account, then I think the answer is no unless they announce a partnership with an inference cloud like cerebras.

tim3333• 8 months ago

You could probably do a new account. I have the odd junk google account.

DrNosferatu• 8 months ago

Anyone has any idea if/when it’s coming to paid Perplexity?

CMay• 8 months ago

I was sorting out the right way to handle a medical thing and Gemini 2.5 Pro was part of the way there, but it lacked some necessary information. Got the Gemini 3.0 release notification a few hours after I was looking into that, so I tried the same exact prompt and it nailed it. Great, useful, actionable information that surfaced actual issues to look out for and resolved some confusion. Helped work through the logic, norms, studies, standards, federal approvals and practices.

Very good. Nice work! These things will definitely change lives.

JohnKemeny• 8 months ago

This ad was brought to you by DeepMind™. Changing people's lives.

hekkle• 8 months ago

GOOGLE: "We have a new product".

REALITY: It's just 3 existing products rolled into one. One of which isn't even a Google product.

- Microsoft Code

- Gemeni

- Chrome Browser

smarx007• 8 months ago

Is it coming to Google Jules?

gabriel666smith• 8 months ago

Interestingly, Gemini 3 Pro Thinking clocks in at 2nd place - behind Horizon Alpha, but ahead of any actually-released model checkpoints - on the TvP Benchmark, with a score of 71.8%.

This blows Sonnet 4.5 (64.8%), GPT5.1 (58.7%) and Opus 4.1 (66.3%) away.

An example output:

'''

The cabin was cold. It smelled of pine needles and old dust. Bryan sat on the porch with a glass of scotch balanced on his knee. It was cheap scotch. He missed the good stuff, but he wasn't in Paris anymore, and he certainly wasn't in Beverly Hills.

He checked his watch. It was a bulky thing, black rubber. He checked the Glock on the table next to him. That was black, too.

"I told you," Bryan said. He wasn't talking to anyone. "I told you not to go into the woods."

He was thinking about Kim. He was always thinking about Kim. She was safe, probably. At a mall in Santa Monica. Or maybe a library. But it felt like she was gone. It always felt like she was gone.

The trees at the edge of the clearing shifted. There wasn't any wind. The air was heavy and humid, unusual for October. A bird stopped singing. Then the crickets stopped. It got very quiet.

Bryan took a sip of the scotch. It burned his throat. He liked the burn. It reminded him he was still there.

Three red dots appeared on his chest. They made a small triangle.

Bryan didn't look at them. He set the glass down on the railing. He picked up the phone. It was an old flip phone. He pressed a button.

"I don't know who you are," Bryan said into the phone. "I don't know what you want. If you are looking for ransom, I can tell you I don't have money."

The leaves rustled. A shape began to form out of the empty air. It looked like heat rising off the highway in August. It was tall. Much taller than a man.

"But what I do have," Bryan said, "are a very particular set of skills."

The shape solidified. It was ugly. It had skin like a lizard and dreadlocks that looked like heavy black cables. It wore a metal mask. It made a clicking sound. Click-click-click. Like a Geiger counter.

"Skills I have acquired over a very long career," Bryan said. He stood up. His knees popped. He felt the ache in his lower back. He was getting too old for this.

The thing roared. It wasn't a human sound. It was a wet, guttural noise.

"I will look for you," Bryan said. He put the phone in his pocket. "I will find you."

The creature raised a metal gauntlet. Two jagged blades slid out. They caught the moonlight.

"And I will kill you," Bryan said.

He raised the Glock and fired twice. Pop-pop.

The creature didn't fall. It took a step forward. Green blood, thick and glowing, leaked from its shoulder. It looked like antifreeze. The creature touched the wound, then looked at its hand. It seemed surprised.

Bryan didn't wait. He moved off the porch. He moved fast for a man his age. He went left, toward the woodpile. The creature fired a blast of blue light from its shoulder. It hit the porch swing. The swing exploded. Wood splinters rained down like confetti.

Bryan rolled behind the logs. He breathed in. He breathed out. He could hear the heavy footsteps crunching the dry leaves. Crunch. Crunch.

"You're big," Bryan whispered. "That makes you slow."

He grabbed a splitting maul from the stump. It was heavy. The handle was smooth hickory.

The creature came around the woodpile. It was scanning the trees. It didn't see Bryan down low. Bryan swung the maul. He put his hips into it. He swung it like he was chopping a cord of oak.

The blade hit the creature in the knee. There was a snap. A loud, wet snap.

The thing howled. It fell onto one knee.

Bryan dropped the maul. He stepped inside the creature’s reach. He knew exactly where to hit. The throat. The armpit. The soft spot under the ribs. He hit the creature three times, hard chops with the side of his hand. It was like hitting a brick wall, but he felt something give.

The creature swung its arm back. It hit Bryan in the chest.

Bryan flew backward. He hit the dirt. The wind went out of him. He lay there for a second, staring up at the stars. They looked very far away. He wondered if Lenore was looking at the same stars. Probably not. She was probably sleeping.

He sat up. His ribs hurt. Maybe broken.

The creature was trying to stand. It was clicking again. It tapped something on its wrist. A series of red symbols started flashing. They counted down.

Bryan knew a bomb when he saw one.

"No," Bryan said.

He tackled the thing. He didn't think about it. He just did it. He grabbed the creature’s arm. He twisted the wrist mechanism. He’d seen something like it in Baghdad once. Or maybe Istanbul. The memories ran together now.

He ripped the gauntlet loose. Wires sparked. He threw it as hard as he could into the darkness of the woods.

Three seconds later, there was a flash. A boom. A shockwave that shook the pine needles from the trees.

Silence came back.

The creature lay on the ground. It was breathing shallowly. The green blood was pooling under it. It took off its mask.

The face was hideous. Mandibles. Beady eyes. It looked at Bryan. It said something, a garbled copy of Bryan's own voice.

"...good luck..."

Then it died. It just stopped.

Bryan stood up. He dusted off his pants. He walked back to the porch. The swing was gone. The railing was scorched.

His glass of scotch was still sitting there, untouched. The ice hadn't even melted.

He picked it up. He took a drink. It still tasted cheap.

He took his phone out and looked at it. No service.

"Well," he said.

He went inside the cabin and locked the door. He sat on the couch and waited for the sun to come up. He hoped Kim would call. He really hoped she would call.

'''

visioninmyblood• 8 months ago

Really exciting results on paper. But truly interesting to see what data this has been trained on. There is a thin line between accuracy improvements and the data used from users. Hope the data used to train was obtained with consent from the creators

raffkede2• 8 months ago

Seems to be the first model that one-shots my secret benchmark about nested SQLite and it did it in 30s,

osn93637393• 8 months ago

Out of interest. Does it one shot it every time?

raffkede2• 8 months ago

Will try again just tried once in the phone a few hours ago, other models were able to do quite a lot but usually missing some stuff this time it managed nested navigation quite well, lot of stuff missing for sure I just tested the basics with the play button in AI studio

hamasho• 8 months ago

I just googled latest LLM models and this page appears at the top. It looks like Gemini Pro 3 can score 102% in high school math tests.

jpkw• 8 months ago

Hoping someone here may know the answer to this, but do any of the benchmarks that exist currently account for false answers in any meaningful way, other than it would in a typical test (ie, if I give any answer at all it is better than saying "I don't know" as the answer I give at least has a chance of being correct(which in the real world is bad))? I want an LLM that tells me when it doesn't know something. If it gives me an accurate response 90% of the time and an inaccurate one 10% of the time, it is less useful than one that gives me an accurate answer 10% of the time and tells me "I don't know" the other 90%.

terandle• 8 months ago

https://artificialanalysis.ai/evaluations/omniscience

rocqua2• 8 months ago

Those numbers are too good to expect. If 90% right 10% wrong is the baseline would you take as an improvement:

- 80% right 18% I don't know 2% wrong - 50%/48%/2% - 10%/90%/0% - 80%/15%/5%

The general point being that to reduce wrong answers you will need to accept some reduction in right answers if you want the change to only be made through trade-offs. Otherwise you just say "I'd like a better system" and that is rather obvious.

Personally I'd take like 70/27/3. Presuming the 70% of right answers aren't all the trivial questions.

fwip2• 8 months ago

I think you may have misread. They stated that they'd be willing to go from 90% correct to 10% correct for this tradeoff.

energy1237• 8 months ago

OpenAI uses SimpleQA to assess hallucinations

davidpolberger• 8 months ago

This is wild. I gave it some legacy XML describing a formula-driven calculator app, and it produced a working web app in under a minute:

https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...

I spent years building a compiler that takes our custom XML format and generates an app for Android or Java Swing. Gemini pulled off the same feat in under a minute, with no explanation of the format. The XML is fairly self-explanatory, but still.

I tried doing the same with Lovable, but the resulting app wouldn't work properly, and I burned through my credits fast while trying to nudge it into a usable state. This was on another level.

zarzavat• 8 months ago

This is exactly the kind of task that LLMs are good at.

They are good at transforming one format to another. They are good at boilerplate.

They are bad at deciding requirements by themselves. They are bad at original research, for example developing a new algorithm.

codespin• 8 months ago

They are good at transforming one format to another. They are good at boilerplate.

You just described 90% of coding

arnorhs• 8 months ago

+/-

They are bad at deciding requirements by themselves.

What do you mean by requirements here? In my experience the frontier models today are pretty good at figuring out requirements, even when you don't explicitly state them.

They are bad at original research

Sure, I don't have any experience with that, so I'll trust you on that.

for example developing a new algorithm.

This is just not correct. I used to think so, but I was trying to come up with a pretty complicated pattern matching, multi-dimensional algorithm (I can't go into the details) - it was something that I could figure out on my own, and was half way through it, but decided to write up a description of it and feed it to gemini 2.5 pro a couple of months ago, and I was stunned.

It came up with a really clever approach and something I had previously been convinced the models weren't very good at it.

In hindsight, since they are getting so good at math in general, there's probably some overlap, but you should revisit your views on this.

Your 'bad at' list is missing a few things though:

- Calculations (they can come up with how to calculate or write a program to calculate from given data, but they are not good at calculating in their responses)

- Even though the frontier models are multi-modal, they are still bad at visualizing html/css - or interpreting what it would look like

- Same goes for visualizing/figuring out visual errors in graphics programming such as games programming or 3d modeling (z-index issues, orientation etc)

xpe2• 8 months ago

Figuring out detailed requirements requires a lot of contact with reality. Specific details about not only the technical surface area but also the organizational and financial constraints. An AI model with the appropriate context would probably do well. It seems one of the things humans do much better at the moment is distill the big picture across a long period of time.

cognitive-gl• 8 months ago

Wild

ogig2• 8 months ago

I just gave it a short description of a small game I had an idea for. It was 7 sentences. It pretty much nailed a working prototype, using React, clean css, Typescript and state management. It event implemented a Gemini query using the API for strategic analysis given a game state. I'm more than impressed, I'm terrified. Seriously thinking of a career change.

brcmthrowaway• 8 months ago

To what?

apparent• 8 months ago

VC (vibe coding).

osn93637393• 8 months ago

Can you share the code?

rkozik19893• 8 months ago

No because this story didn't happen.

ogig2• 8 months ago

https://ai.studio/apps/drive/1E-aYovHHoY8jrF6bsl_AZ8VszIN66N...

The initial prompt was, in case people doesn't want to log in:

Make a turn based chess like game. Instead of normal chess board use an hexagonal grid. Make the board diagonal shaped. Instead of traditional chess pieces we are going to use spaceship designs. Each spaceship has unique abilities that influence the board or their own skill. For 2 players, turn based. Show me what you got.

WhyOhWhyQ5• 8 months ago

I just spent 12 hours a day vibe coding for a month and a half with Claude (which has equal swe benchmarks at gemini 3). I started out terrified but eventually I realized that these are just remarkably far away from actually replacing a real software engineer. For prototypes they're amazing, but when you're just straight vibe coding you get stuck in a hell where you don't want to or can't efficiently really check what's going on under the hood but it's not really doing the thing you want.

Basically these tools can you you to a 100k LOC project without much effort, but it's not going to be a serious product. A serious product requires understanding still.

wraptile2• 8 months ago

I find it funny to find this almost exact same post in every new model release thread. Yet here we are - spending the same amount of time, if not more, finishing the rest of the owl.

cafebabbe• 8 months ago

Seems like the whole world forgot what this job was really about :/

King-Aaron• 8 months ago

it’s been incredible to see how much people love it. AI Overviews now have 2 billion users every month

"Incredible"! When they insert it into literally every google request without an option to disable it. How incredibly shocking so many people use it.

zen_boy• 8 months ago

Is the "thinking" dropdown option on gemini.google.com what the blog post refers to as Deep Think?

maczwei• 8 months ago

entity.ts is in types/entity.ts .it cant grasp that it should import it like "../types/entity" and instead it always writes "../types" i am using the https://aistudio.google.com/apps

kanodiaayush3• 8 months ago

I don't really understand the amount of ongoing negativity in the comments. This is not the first time a product has been near copied, and the experience for me is far superior to code in a terminal. It comes with improvements even though imperfect, and I'm excited for those! I've long wanted the ability to comment on code diffs instead of just writing things back down in chat. And I'm excited for the quality of gemini 3.0 pro; although I'm running into rate limits. I can already tell its something I'm going to try out a lot!

rvnx3• 8 months ago

It's not really good for real-life programming though, it invents lot of imaginary things, cannot respect its own instructions, forgets basic things (variable is called "bananaDance", then claims it is "bananadance", then later on "bananaDance" again).

It is good at writing something from scratch (like spitting out its training set).

Claude is still superior for programming and debugging. Gemini is better at daily life questions and creative writing.

kanodiaayush3• 8 months ago

yeah testing it out! good to know the above. My feel also is that claude is better so far.

chiragsrvstv• 8 months ago

Waiting for google to nuke this as well just like 2.5pro

eterm• 8 months ago

It seems there's a date conflict. The prompt claims it's 2025, but my internal clock says otherwise.
I'm now zeroing in on the temporal aspect. Examining the search snippets reveals dates like "2025-10-27," suggesting a future context relative to 2024. My initial suspicion was that the system time was simply misaligned, but the consistent appearance of future dates strengthens the argument that the prompt's implied "present" is indeed 2025. I am now treating the provided timestamps as accurate for a simulated 2025. It is probable, however, that the user meant 2024.

Um, huh? It's found search results for October 2025, but this has led it to believe it's in a simulated future, not a real one?

pclark• 8 months ago

I just want Gemini to access ALL my Google Calendars, not just the primary one. If they supported this I would be all in on Gemini. Does no one else want this?

petesergeant• 8 months ago

Still insists the G7 photo[0] is doctored, and comes up with wilder and wilder "evidence" to support that claim, before getting increasingly aggressive.

0: https://en.wikipedia.org/wiki/51st_G7_summit#/media/File:Pri...

kmeisthax2• 8 months ago

The most devastating news out of this announcement is that Vending-Bench 2 came out and it has significantly less clanker[0] meltdowns than the first one. I mean, seriously? Not even one run where the model tried to stock goods that hadn't arrived yet, only for it to eventually try and fail to shut down the business, and then e-mail the FBI about the $2 daily fee being deducted from the bot?

[0] Fake racial slur for a robot, LLM chatbot, or other automated system

auggierose• 8 months ago

Gemini 3 is the best vibe coding and agentic coding model we’ve ever built

Google goes full Apple...

elcapithanos• 8 months ago

AI overviews now have 2 billion users every month

More like 2 billion hostages

lofaszvanitt4• 8 months ago

A tad bit better, still has the same issues regarding unpacking and understanding complex prompts. I have a test of mine and now it performs a bit better, but still, it has zero understanding what is happening and for why. Gemini is the best of the best model out there, but with complex problems it just goes down the drain :(.

lofaszvanitt4• 8 months ago

Oh that corpulent fella with glasses who talks in the video. Look how good mannered he is, he can't hurt anyone. But Google still takes away all your data and you will be forced out of your job.

energy1237• 8 months ago

With the $20/m subscription, do we get it on "Low" or "High" thinking level?

primaprashant• 8 months ago

Created a summary of comments from this thread about 15 hours after it had been posted and had 814 comments with gemini-3-pro and gpt-5.1 using this script [1]:

- gemini-3-pro summary: https://gist.github.com/primaprashant/948c5b0f89f1d5bc919f90...

- gpt-5.1 summary: https://gist.github.com/primaprashant/3786f3833043d8dcccae4b...

Summary from GPT 5.1 is significantly longer and more verbose compared to Gemini 3 Pro (13,129 output tokens vs 3,776). Gemini 3 summary seems more readable, however, GPT 5.1 one has interesting insights missed by Gemini.

Last time I did this comparison at the time of GPT 5 release [2], the summary from Gemini 2.5 Pro was way better and readable than the GPT 5 one. This time the readability of Gemini 3 summary still seems great while GPT 5.1 feels a bit more improved but not there quite yet.

[1] https://gist.github.com/primaprashant/f181ed685ae563fd06c49d...

[2] https://news.ycombinator.com/item?id=44835029

misja111• 8 months ago

I asked Gemini to solve today's Countle puzzle (https://www.countle.org/). It got stuck while iterating randomly trying to find a solution. While I'm writing this it has been trying already for 5 minutes and the web page has become unresponsive.

I also asked it for the best play when in backgammon opponent rolls 6-1 (plays 13/7 8/7) and you roll 5-1. It starts alright with mentioning a good move (13/8 6/5) but continues to hallucinate with several alternative but illegal moves. I'm not too impressed.

iamA_Austin• 8 months ago

it started with OpenAI and Google took the competition damn seriously.

pk-protect-ai• 8 months ago

It is pointless to ask an LLM to draw an ASCII unicorn these days. Gemini 3 draws one of these (depending on the prompt):

https://www.ascii-art.de/ascii/uvw/unicorn.txt

However, it is amazing how far spatial comprehension has improved in multimodal models.

I'm not sure the below would be properly displayed on HN; you'll probably need to cut and paste it into a text editor.

Prompt: Draw me an ASCII world map with tags or markings for the areas and special places.

Temperature: 1.85

Top-P 0.98

Answer: Edit (replaced with URL) https://justpaste.it/kpow3

nprateem• 8 months ago

OMG they've obviously had a major breakthrough because now it can reply to questions with actual answers instead of shit blog posts.

rubymamis• 8 months ago

I gave it the task to recreate StackView.qml to be feel more native on iOS and it failed - like all other models...

Prompt:

Instead of the current StackView, I want you to implement a new StackView that will have a similar api with the differences that:

1. It automatically handles swiping to the previous page/item. If not mirrored, it should detect swiping from the left edge, if mirrored it should detect from the right edge. It's important that swiping will be responsive - that is, that the previous item will be seen under the current item when swiping - the same way it's being handled on iOS applications. You should also add to the api the option for the swipe to be detected not just from the edge, but from anywhere on the item, with the same behavior. If swiping is released from x% of current item not in view anymore than we should animate and move to the previous item. If it's a small percentage we should animate the current page to get back to its place as nothing happened. 2. The current page transitions are horrible and look nothing like native iOS transitions. Please make the transitions feel the same.

bluecalm2• 8 months ago

I've asked it (thinking 3) about the difference between Plus and Pro plans. First it thought I am asking for comparison between Gemini and ChatGPT as it claimed there is no "Plus" plan on Gemini. After I insisted I am on this very plan right now it apologized and told me it in fact exists. Then it told me the difference is that I got access to newer models with the Pro subscription. That is despite Google's own plan comparison page showing I get access to the Gemini 3 on both plans.

It also told me that on Plus I am most likely using "Flash" model. There is no "Flash" model in the dropdown to choose from. There is only "Fast" and "Thinking". It then told me "Fast" is just renamed Flash and it likely uses Gemini 2.5. On the product comparison page there is nothing about 2.5, it only mentions version 3 for both Plus and Pro plans. Of course on the dropdown menu it's impossible to see which model it is really using.

How can a normal person understand their products when their own super advanced thinking/reasoning model that took months to train on world's most advanced hardware can't?

It's amazing to me they don't see it as an epic failure in communication and marketing.

jacky2wong• 8 months ago

What I loved about this release was that it was hyped up by a polymarket leak with insider trading - NOT with nonsensical feel the AGI hype. Great model that's pushed the frontier of spatial reasoning by a long shot.

taf22• 8 months ago

I had asked earlier in the day for gpt 5.1 high to refactor my apex visualforce page into a lightning component and it really didn’t do much here - Gemini 3 pro crushed this task… very promising

gigatexal• 8 months ago

How does it do in coding tasks? I’ve been absolutely spoiled by Claude sonnet 4.5 thinking.

abixb• 8 months ago

Okay, Gemini 3.0 Pro has officially surpassed Claude 4.5 (and GPT-5.1) as the top ranked model based on my private evals (multimodal reasoning w/ images/audio files and solving complex Caesar/transposition ciphers, etc.).

Claude 4.5 solved it as well (the Caesar/transposition ciphers), but Gemini 3.0 Pro's method and approach was a lot more elegant. Just my $0.02.

tim3333• 8 months ago

Hassabis interview on Gemini 3, with Hard Fork (nyt podcast), also Josh Woodward https://youtu.be/rq-2i1blAlU?t=428 Some points -

Good at vibe coding 10:30 - step change where it's actually useful

AGI still 5-10 years. Needs reasoning, memory, world models.

Is it a bubble? - Partly 22:00

What's fun to do with Gemini to show the relatives? Suggested taking a selfie with the app and having it edit. 24:00 (I tried and said make me younger. Worked pretty well.)

Also interesting - apparently they are doing an agent to go through your email inbox and propose replies automatically 4:00. I could see that getting some use.

erikpukinskis• 8 months ago

Needs reasoning, memory, world models.

Is that all? So they just need to invent:

1. Thought

2. A mechanism for efficiently encoding and decoding arbitrary percepts

3. A formal model of the world

And then the existing large language models can handle the rest.

Yep, 5 years and a hundred billion dollars or so should do the trick.

mark_l_watson• 8 months ago

I had a fantastic ‘first result’ with Gemini 3 but a few people on social media I respect didn’t. Key takeaway is to do your own testing with your use cases. I feel like I am now officially biased re: LLM infrastructure: I am retired, doing personal research and writing, and I decided months ago to drop OpenAI and Anthropic infrastructure and just use Google to get stuff done - except I still budget about two hours a week to experiment with local models and Chinese models’ APIs.

taf22• 8 months ago

I just wish gemini could write well formatted code. I do like the solutions it comes up to and I know I can use a linter/formatter tool - but it would just be nice if when I openned gemini (cli) up and asked it to write a feature it didn't mix up the indenting so badly... somehow codex and claude both get this without any trouble...

AbstractH242• 8 months ago

Can someone ELI5 what the difference between AI Studio, Antigravity, and Colab is?

simlevesque2• 8 months ago

Ai studio is a web chat.

Antigravity is an IDE you install.

Colab is a place to run notebooks in the cloud.

AbstractH242• 8 months ago

Colab has significant Gemini functionality built in. How isn't it a combination of the first two?

Thanks for sorting all this out! Still exploring the first two, so I really don't know.

WhyOhWhyQ5• 8 months ago

Why doesn't this spell the death of OpenAI? Maybe someone with a better business sense can explain, but here's what I'm seeing:

OpenAI is going for the consumer-grade AI market, as opposed to a company like Anthropic making a specialized developer tool. Google can inject their AI tool in front of everybody in the world, and already have with Google AI search. All of these models are just going to reach parity eventually, but Google is burning cash compared to OpenAI burning debt. It seems like for consumer-grade purposes, AI use will just be free sooner or later (DeepSeek is free, Google AI search is free, students can get Gemini Pro for free for a year already). So all I'm seeing that OpenAI has is Sora, which seems like a business loser though I don't really understand it, and also ChatGPT seems to own the market of people roleplaying with chat bots as companions (which doesn't really seem like a multi-trillion dollar business but I could be wrong).

nextworddev2• 8 months ago

Yep. Except OpenAI is mainly burning LP money (saudis, softbank, pension funds)

thingsilearned• 8 months ago

I love that the recipe example is still being used as one of the main promising use cases for computers and now AGI. One day hopefully computers will solve that pressing problem...

espeed• 8 months ago

I paid for Gemini Pro. Am I getting Gemini 3 Pro (https://gemini.google.com)? "To be precise: You are currently interacting with Gemini 1.5 Pro." https://x.com/espeed/status/1991333475098718601

decide10002• 8 months ago

We hire a developer to build parsers for a complicated file format. It takes a week per parser. Gemini 3 is the first LLM that is able to create a parser from scratch, and it does it very well. Within a minute, 1-shot-right. I am blown away.

Frannky• 8 months ago

I tried it on a landing page. Very, very impressive.

VladimiOrlovsky2• 8 months ago

import decimal

def solve_kangaroo_limit(): # Set precision to handle the "digits different from six" requirement decimal.getcontext().prec = 50

    # For U(0,1), H(x) approaches 2x + 2/3 very rapidly (exponential decay of error)
    # At x = 10^6, the value is indistinguishable from the asymptote
    x = 10**6
    limit_value = decimal.Decimal(2) * x + decimal.Decimal(2) / decimal.Decimal(3)
    
    print(f"H({x}) ≈ {limit_value}")
    # Output: 2000000.66666666666666666666...

if __name__ == "__main__": solve_kangaroo_limit() ....p.s. for airheads=idiots: """decimal.Decimal(2) / decimal.Decimal(3)""" == 0.6666666666666666666666666666666666666666666666666666666666666666666666666 ... This is your Fukingly 'smart' computer???

VladimiOrlovsky2• 8 months ago

p.s. This is not on singular error, this is a good example of fundamental problems ... and a lot of lies. End of conversation.

Gemini 3

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