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Gemini 3.1 Pro

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Re: Gemini 3.1 Pro

#531

Post by moffkalast »

andrewmutz wrote: post #218
mijoharas wrote: post #205

Gemini 3 is still in preview (limited rate limits) and 2.5 is deprecated (still live but won't be for long).[0] Are Google planning to put any of their models into production any time soon? Also somewhat funny that some models are deprecated without a suggested alternative(gemini-2.5-flash-lite). Do they suggest people switch to Claude? [0] https://ai.google.dev/gemini-api/docs/deprecations

I agree completely. I don't know how anyone can be building on these models when all of them are either deprecated or not actually released yet. As someone who has production systems running on the deprecated models, this situation really causes me grief.

Well let me use llama.cpp to run worlds-smallest-violin-Q8.gguf

When you build on something that can be rugpulled at any moment, that's really kind of on you.

Re: Gemini 3.1 Pro

#532

Post by amluto »

minimaxir wrote: post #23

Price is unchanged from Gemini 3 Pro: $2/M input, $12/M output. https://ai.google.dev/gemini-api/docs/pricing Knowledge cutoff is unchanged at Jan 2025. Gemini 3.1 Pro supports "medium" thinking where Gemini 3 did not: https://ai.google.dev/gemini-api/docs/gemini-3 Compare to Opus 4.6's $5/M input, $25/M output. If Gemini 3.1 Pro does indeed have similar performance, the price difference is notable.

Now compare the monthly plans for business users who want the CLI agent but who don’t want the models trained on their data.

OpenAI: no big deal — sign up, pick your number of seats, and you’re all set.

Anthropic: also no big deal but there’s an obnoxious minimum purchase.

Google: first you have to try to figure out what the product is called. Then you need to figure out how to set the correct IAM rules. Then you have to sign up and pay for it. Maybe you succeed. Maybe you give up after an hour or two of cursing. Gemini is, of course, completely unable to help. (OpenAI clearly has not trained their models on how to operate their tools. Google’s models hallucinate Google’s product offerings so outrageously that I’m not sure I could tell. I haven’t asked Claude about Claude Code.)

At least the monthly pricing is similar once you get over the hurdles.

Re: Gemini 3.1 Pro

#533

Post by kakugawa »

alphabetting wrote: post #393
karmasimida wrote: post #362

Earlier quoted context omitted.

Gemini just doesn’t do even mildly well in agentic stuff and I don’t know why. OpenAI has mostly caught up with Claude in agentic stuff, but Google needs to be there and be there quickly

the agentic benchmarks for 3.1 indicate Gemini has caught up. the gains are big from 3.0 to 3.1. For example the APEX-Agents benchmark for long time horizon investment banking, consulting and legal work: 1. Gemini 3.1 Pro - 33.2% 2. Opus 4.6 - 29.8% 3. GPT 5.2 Codex - 27.6% 4. Gemini Flash 3.0 - 24.0% 5. GPT 5.2 - 23.0% 6. Gemini 3.0 Pro - 18.0%

In mid-2024, Anthropic made the deliberate decision to stop chasing benchmarks and focus on practical value. There was a lot of skepticism at the time, but it's proven to be a prescient decision.

Re: Gemini 3.1 Pro

#534

Post by knollimar »

robotpepi wrote: post #445
jeffybefffy519 wrote: post #440

Someone needs to make an actual good benchmark for LLM's that matches real world expectations, theres more to benchmarks than accuracy against a dataset.

this reminds me of that joke of someone saying "it's crazy that we have ten different standards for doing this", and then there're 11 standards

Xkcd 927

Re: Gemini 3.1 Pro

#535

Post by w10-1 »

rjh29 wrote: post #466
davidguetta wrote: post #162

Implementation and Sustainability Hardware: Gemini 3 Pro was trained using Google’s Tensor Processing Units (TPUs). TPUs are specically designed to handle the massive computations involved in training LLMs and can speed up training considerably compared to CPUs. TPUs often come with large amounts of high-bandwidth memory, allowing for the handling of large models and batch sizes during training, which can lead to bet…

I assume that's a Gemini LLM response? You can tell Gemini is bullshitting when it starts using "often" or "usually" - like in this case "TPUs often come with large amounts of memory". Either they did or they didn't. "This (particular) mall often has a Starbucks" was one I encountered recently.

It's not bullshit (i.e., intended) but probabilities all the way down, as Hume reminded us: from observations, you can only say the sun will likely rise in the east. You'd need to stand behind a theory of the world to say otherwise (but we were told "attention is all you need"...)

Re: Gemini 3.1 Pro

#536

Post by moffkalast »

mullingitover wrote: post #158
embedding-shape wrote: post #73

Earlier quoted context omitted.

It's an excellent demonstration of the main issue I have with the Gemini family of models, they always go "above and beyond" to do a lot of stuff, even if I explicitly prompt against it. In this case, most of the SVG ends up consisting not just of a bike and a pelican, but clouds, a sun, a hat on the pelican and so much more. Exactly the same thing happens when you code, it's almost impossible to get Gemini to not do…

> it's almost impossible to get Gemini to not do "helpful" drive-by-refactors Just asking "Explain what this service does?" turns into [No response for three minutes...] +729 -522

I've seen Kimi do this a ton as well, so insufferable.

Re: Gemini 3.1 Pro

#537

Post by girvo »

sunaookami wrote: post #463
jbellis wrote: post #274

Earlier quoted context omitted.

still no minimal reasoning in G3.1P :( (this is why Opus 4.6 is worth the price -- turning off thinking makes it 3x-5x faster but it loses only a small amount of intelligence. nobody else has figured that out yet)

Thinking is just tacked on for Anthropic's models and always has been so leaving it off actually produces better results everytime.

What about for analysis/planning? Honestly I've been using thinking, but if I don't have to with Opus 4.6 I'm totally keen to turn it off. Faster is better.

Re: Gemini 3.1 Pro

#538

Post by AlphaAndOmega0 »

suddenlybananas wrote: post #307
AlphaAndOmega0 wrote: post #297

Earlier quoted context omitted.

Previous models from competitors usually got that correct, and the reasoning versions almost always did. This kind of reflexive criticism isn't helpful, it's closer to a fully generalized counter-argument against LLM progress, whereas it's obvious to anyone that models today can do things they couldn't do six months ago, let alone 2 years back.

I'm not denying any progress, I'm saying that reasoning failures that are simple which have gone viral are exactly the kind of thing that they will toss in the training data. Why wouldn't they? There's real reputational risks in not fixing it and no costs in fixing it.

Given that Gemini 3 Pro already did solid on that test, what exactly did they improve? Why would they bother?

I double checked and tested on AI Studio, since you can still access the previous model there:

>You should drive. >If you walk there, your car will stay behind, and you won't be able to wash it.

Thinking models consistently get it correct and did when the test was brand new (like a week or two ago). It is the opposite of surprising that a new thinking model continues getting it correct, unless the competitors had a time machine.

Re: Gemini 3.1 Pro

#540

Post by girvo »

quotemstr wrote: post #299
mullingitover wrote: post #158

Earlier quoted context omitted.

> it's almost impossible to get Gemini to not do "helpful" drive-by-refactors Just asking "Explain what this service does?" turns into [No response for three minutes...] +729 -522

What. You don't have yours ask for edit approval?

The depressing truth is most I know just run all these tools in /yolo mode or equivalents.

Because your coworkers definitely are, and we're stack ranked, so it's a race (literally) to the bottom. Just send it...

(All this actually seems to do is push the burden on to their coworkers as reviewers, for what it's worth)

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