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Gemini 3.1 Pro

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Re: Gemini 3.1 Pro

#511

Post by dumpsterdiver »

foz wrote: post #411
s3p wrote: post #325

Earlier quoted context omitted.

Don't get me started on the thinking tokens. Since 2.5P the thinking has been insane. "I'm diving in to the problem", "I'm fully immersed" or "I'm meticulously crafting the answer"

This is part of the reason I don't like to use it. I feel it's hiding things from me, compared to other models that very clearly share what they are thinking.

To be fair, considering that the CoT exposed to users is a sanitized summary of the path traversal - one could argue that sanitized CoT is closer to hiding things than simply omitting it entirely.

Re: Gemini 3.1 Pro

#513

Post by ainch »

tasuki wrote: post #397
energy123 wrote: post #321

Earlier quoted context omitted.

Francois Chollet accuses the big labs of targeting the benchmark, yes. It is benchmaxxed.

Didn't the same Francois Chollet claim that this was the Real Test of Intelligence? If they target it, perhaps they target... real intelligence?

He's always said ARC is a necessary but not sufficient condition for testing intelligence afaik

Re: Gemini 3.1 Pro

#514

Post by ainch »

esafak wrote: post #17

Has anyone noticed that models are dropping ever faster, with pressure on companies to make incremental releases to claim the pole position, yet making strides on benchmarks? This is what recursive self-improvement with human support looks like.

It's becoming impossible to keep up - in the last week or so we've had: Gemini 3 Deep Think, Gemini 3.1 Pro, Claude Sonnet 4.6, GPT-5.3-Codex Spark, GLM-5, Minimax-2.5, Step 3.5 Flash, Qwen 3.5 and Grok 4.20.

and I'm sure others I've missed...

Re: Gemini 3.1 Pro

#516

Post by bayindirh »

onlyrealcuzzo wrote: post #464
Macha wrote: post #431

Earlier quoted context omitted.

> Agentic workflows are a VERY small percentage of all LLM usage at the moment. As that market becomes more important, Google will pour more resources into it. I do wonder what percentage of revenue they are. I expect it's very outsized relative to usage (e.g. approximately nobody who is receiving them is paying for those summaries at the top of search results)

> (e.g. approximately nobody who is receiving them is paying for those summaries at the top of search results) Nobody is paying for Search. According to Google's earnings reports - AI Overviews is increasing overall clicks on ads and overall search volume.

So, apparently switching to Kagi continues to pay in dividends, elegantly.

No ads, no forced AI overview, no profit centric reordering of results, plus being able to reorder results personally, and more.

Re: Gemini 3.1 Pro

#517

Post by sushisource »

embedding-shape wrote: post #319
1024core wrote: post #260

It got the car wash question perfectly: You are definitely going to have to drive it there—unless you want to put it in neutral and push! While 200 feet is a very short and easy walk, if you walk over there without your car, you won't have anything to wash once you arrive. The car needs to make the trip with you so it can get the soap and water. Since it's basically right next door, it'll be the shortest drive of you…

GPT-OSS-120b, a (downloadable) model released more than half a year ago also gets that right, I'm not sure this is such a great success. > Would you like me to check the local weather forecast to make sure it's not going to rain right after you wash it? Regardless of what I do, the days I decide to wash my car, it ALWAYS rains the day after, even if I look at the weather report and it says sunny. Cute that Gemini thi…

> Regardless of what I do, the days I decide to wash my car, it ALWAYS rains the day after

Undeniable universal truth. I sometimes find myself making plans based on the fact that the most annoying possible outcome is also the most likely one.

Re: Gemini 3.1 Pro

#518

Post by Aachen »

embedding-shape wrote: post #319
1024core wrote: post #260

It got the car wash question perfectly: You are definitely going to have to drive it there—unless you want to put it in neutral and push! While 200 feet is a very short and easy walk, if you walk over there without your car, you won't have anything to wash once you arrive. The car needs to make the trip with you so it can get the soap and water. Since it's basically right next door, it'll be the shortest drive of you…

GPT-OSS-120b, a (downloadable) model released more than half a year ago also gets that right, I'm not sure this is such a great success. > Would you like me to check the local weather forecast to make sure it's not going to rain right after you wash it? Regardless of what I do, the days I decide to wash my car, it ALWAYS rains the day after, even if I look at the weather report and it says sunny. Cute that Gemini thi…

Non car person here. Why does that matter? It's not like rain means you didn't have to go to the wash, it rains often enough here that there wouldn't be car wash places left near me but there are plenty

Re: Gemini 3.1 Pro

#519

Post by culi »

esafak wrote: post #17

Has anyone noticed that models are dropping ever faster, with pressure on companies to make incremental releases to claim the pole position, yet making strides on benchmarks? This is what recursive self-improvement with human support looks like.

I feel like they're actually dropping slower. Chinese models are dropping right before lunar new year as seems to be an emerging tradition.

A couple of western models have dropped around the same time too but I don't think the "strides on benchmarks" are that impressive when you consider how much tokens are being spent to make those "improvements". E.g. Gemini 3.1 Pro's ARC-AGI-2 score went from 33.6% to 77.1% buuut their "cost per task" also increased by 4.2x. It seems to be the same story for most of these benchmark improvements and similar for Claude model improvements.

I'm not convinced there's been any substantial jump in capabilities. More likely these companies have scaled their datacenters to allow for more token usage

Re: Gemini 3.1 Pro

#520

Post by culi »

emp17344 wrote: post #29
esafak wrote: post #17

Has anyone noticed that models are dropping ever faster, with pressure on companies to make incremental releases to claim the pole position, yet making strides on benchmarks? This is what recursive self-improvement with human support looks like.

Remember when ARC 1 was basically solved, and then ARC 2 (which is even easier for humans) came out, and all of the sudden the same models that were doing well on ARC 1 couldn’t even get 5% on ARC 2? Not convinced these benchmark improvements aren’t data leakage.

Look at the ARC site. The scores of these models is plotted against their "cost per task". All of these huge jumps come along with massive increases in cost per task. Including Gemini 3.1 Pro which increased by 4.2x
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