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Gemini 3 Deep Think

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Re: Gemini 3 Deep Think

#71
post #53

Arc-AGI-2: 84.6% (vs 68.8% for Opus 4.6) Wow. https://blog.google/innovation-and-ai/models-and-research/ge...

https://arcprize.org/leaderboard $13.62 per task - so we need another 5-10 years for the price to run this to become reasonable? But the real question is if they just fit the model to the benchmark.

That's not a long time in the grand scheme of things.

Re: Gemini 3 Deep Think

#72

According to benchmarks in the announcement, healthily ahead of Claude 4.6. I guess they didn't test ChatGPT 5.3 though. Google has definitely been pulling ahead in AI over the last few months. I've been using Gemini and finding it's better than the other models (especially for biology where it doesn't refuse to answer harmless questions).

Google models and CLI harness feels behind in agentic coding compared OpenAI and Antrophic

Re: Gemini 3 Deep Think

#73
post #70

I can't shake of the feeling that Googles Deep Think Models are not really different models but just the old ones being run with higher number of parallel subagents, something you can do by yourself with their base model and opencode.

And after i do that, how do i combine the output of 1000 subagents into one output? (Im not being snarky here, i think it's a nontrivial problem)

Re: Gemini 3 Deep Think

#74

Not trained for agentic workflows yet unfortunately - this looks like it will be fantastic when they have an agent friendly one. Super exciting.

Its really weird how you all are begging to be replaced by llms, you think if agentic workflows get good enough you're going to keep your job? Or not have your salary reduced by 50%?

If Agents get good enough it's not going to build some profitable startup for you (or whatever people think they're doing with the llm slot machines) because that implies that anyone else with access to that agent can just copy you, its what they're designed to do... launder IP/Copyright. Its weird to see people get excited for this technology.

None of this good. We are simply going to have our workforces replaced by assets owned by Google, Anthropic and OpenAI. We'll all be fighting for the same barista jobs, or miserable factory jobs. Take note on how all these CEOs are trying to make it sound cool to "go to trade school" or how we need "strong American workers to work in factories".

Re: Gemini 3 Deep Think

#75
post #68

Earlier quoted context omitted.

Yes, but benchmarks like this are often flawed because leading model labs frequently participate in 'benchmarkmaxxing' - ie improvements on ARC-AGI2 don't necessarily indicate similar improvements in other areas (though it does seem like this is a step function increase in intelligence for the Gemini line of models)

Isn’t the point of ARC that you can’t train against it? Or doesn’t it achieve that goal anymore somehow?

* that you weren't supposed to be able to

Re: Gemini 3 Deep Think

#76
post #39

The pelican riding a bicycle is excellent . I think it's the best I've seen. https://simonwillison.net/2026/Feb/12/gemini-3-deep-think/

Highly disagree.

I was expecting something more realistic... the true test of what you are doing is how representative is the thing in relation to the real world. E.g. does the pelican look like a pelican as it exists in reality? This cartoon stuff is cute but doesnt pass muster in my view.

If it doesn't relate to the real world, then it most likely will have no real effect on the real economy. Pure and simple.

Re: Gemini 3 Deep Think

#77

Earlier quoted context omitted.

Arc-AGI (and Arc-AGI-2) is the most overhyped benchmark around though. It's completely misnamed. It should be called useless visual puzzle benchmark 2. It's a visual puzzle, making it way easier for humans than for models trained on text firstly. Secondly, it's not really that obvious or easy for humans to solve themselves! So the idea that if an AI can solve "Arc-AGI" or "Arc-AGI-2" it's super smart or even "AGI" is…

The puzzles are calibrated for human solve rates, but otherwise I agree.

My two elderly parents cannot solve Arc-AGI puzzles, but can manage to navigate the physical world, their house, garden, make meals, clean the house, use the TV, etc.

I would say they do have "general intelligence", so whatever Arc-AGI is "solving" it's definitely not "AGI"

Re: Gemini 3 Deep Think

#78

Earlier quoted context omitted.

Here's a good thread over 1+ month, as each model comes out https://bsky.app/profile/pekka.bsky.social/post/3meokmizvt22... tl;dr - Pekka says Arc-AGI-2 is now toast as a benchmark

If you look at the problem space it is easy to see why it's toast, maybe there's intelligence in there, but hardly general.

the best way I've seen this describes is "spikey" intelligence, really good at some points, those make the spikes

humans are the same way, we all have a unique spike pattern, interests and talents

ai are effectively the same spikes across instances, if simplified. I could argue self driving vs chatbots vs world models vs game playing might constitute enough variation. I would not say the same of Gemini vs Claude vs ... (instances), that's where I see "spikey clones"

Re: Gemini 3 Deep Think

#79

Less than a year to destroy Arc-AGI-2 - wow.

It's a useless meaningless benchmark though, it just got a catchy name, as in, if the models solve this it means they have "AGI", which is clearly rubbish.

Arc-AGI score isn't correlated with anything useful.

Re: Gemini 3 Deep Think

#80
post #40
post #39

The pelican riding a bicycle is excellent . I think it's the best I've seen. https://simonwillison.net/2026/Feb/12/gemini-3-deep-think/

It's worth noting that you mean excellent in terms of prior AI output. I'm pretty sure this wouldn't be considered excellent from a "human made art" perspective. In other words, it's still got a ways to go! Edit: someone needs to explain why this comment is getting downvoted, because I don't understand. Did someone's ego get hurt, or what?

Indeed. And when you factor in the amount invested... yeah it looks less impressive. The question is how much more money needs to be invested to get this thing closer to reality? And not just in this instance. But for any instance e.g. a seahorse on a bike.
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