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Gemini 3.1 Pro

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Re: Gemini 3.1 Pro

#271

Post by TiredOfLife »

paride5745 wrote: post #200
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…

Another reason to use Gemini then. Less impact on gamers…

TPUs still use ram and chip production capacity

Re: Gemini 3.1 Pro

#272

Post by Barbing »

alpineman wrote: post #235
Murfalo wrote: post #212

I like to think that all these pelican riding a bicycle comments are unwittingly iteratively creating the optimal cyclist pelican as these comment threads are inevitably incorporated in every training set.

More like half of Google's AI team is hanging out on HN, and they can optimise for that outcome to get a good rep among the dev community.

See: fish in bike front basket

Re: Gemini 3.1 Pro

#273

Post by mark_l_watson »

PlatoIsADisease wrote: post #33
mark_l_watson wrote: post #9

Fine, I guess. The only commercial API I use to any great extent is gemini-3-flash-preview: cheap, fast, great for tool use and with agentic libraries. The 3.1-pro-preview is great, I suppose, for people who need it. Off topic, but I like to run small models on my own hardware, and some small models are now very good for tool use and with agentic libraries - it just takes a little more work to get good results.

What models are you running locally? Just curious. I am mostly restricted to 7-9B. I still like ancient early llama because its pretty unrestricted without having to use an abliteration.

I experimented with many models on my 16G and 32G Macs. For less memory, qwen3:4b is good, for the 32B Mac, gpt-oss:20b is good. I like the smaller Mistral models like mistral:v0.3 and rnj-1:latest is a pretty good small reasoning model.

Re: Gemini 3.1 Pro

#274

Post by jbellis »

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.

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)

Re: Gemini 3.1 Pro

#275

Post by 0_____0 »

emp17344 wrote: post #254
0_____0 wrote: post #194

Earlier quoted context omitted.

next time you host a party, have people try to draw a bicycle on your whiteboard (you have a whiteboard in your house right? you should, anyway...) human adults are generally quite bad at drawing them, unless they spend a lot of time actually thinking about bicycles as objects

What’s your point? Yes, humans fail sometimes, as do AI models. Are you trying to imply that, in light of this, AI is now as capable as human beings? If so, that conclusion doesn’t follow logically.

it's not a loaded point, i just think it's funny that humans typically cannot one-shot this. and it will make your friends laugh

Re: Gemini 3.1 Pro

#276

Post by pRusya »

I'm using gemini.google.com/app with AI Pro subscription. "Something went wrong" in FF, works in Chrome.

Below is one of my test prompts that previous Gemini models were failing. 3.1 Pro did a decent job this time.

> use c++, sdl3. use SDL_AppInit, SDL_AppEvent, SDL_AppIterate callback functions. use SDL_main instead of the default main function. make a basic hello world app.

Re: Gemini 3.1 Pro

#277

Post by suddenlybananas »

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…

They probably had time to toss that example in the training soup.

Re: Gemini 3.1 Pro

#278

Post by jbellis »

spankalee wrote: post #199

I hope this works better than 3.0 Pro I'm a former Googler and know some people near the team, so I mildly root for them to at least do well, but Gemini is consistently the most frustrating model I've used for development. It's stunningly good at reasoning, design, and generating the raw code, but it just falls over a lot when actually trying to get things done, especially compared to Claude Opus. Within VS Code Copi…

yeah, g3p is as smart or smarter as the other flagships but it's just not reliable enough, it will go into "thinking loops" and burn 10s of 1000s of tokens repeating itself.

https://blog.brokk.ai/gemini-3-pro-preview-not-quite-baked/

hopefully 3.1 is better.

Re: Gemini 3.1 Pro

#279

Post by embedding-shape »

neya wrote: post #268
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 This has not been my experience. I do Elixir primarily and Gemini has helped build some really cool products and massive refactors along the way. And it would even pick up security issues and potential optimizations along the way What HAS been an issue constantly though was randomly the model will absolutely not respond at all and some rand…

Out of curiosity, do you have any public projects (with public source code) you've made exclusively with Gemini, so one could take a look? I've tried a bunch of times to use Gemini to at least finish something small but I always end up sufficiently frustrated to abort it as the instruction-following seems so bad.

Re: Gemini 3.1 Pro

#280

Post by [deleted] »

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.

[deleted]
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