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Posted by MallocVoidstar 15 hours ago

Gemini 3.1 Pro(blog.google)
Preview: https://console.cloud.google.com/vertex-ai/publishers/google...

Card: https://deepmind.google/models/model-cards/gemini-3-1-pro/

620 points | 743 commentspage 6
vinhnx 14 hours ago|
Model card https://deepmind.google/models/model-cards/gemini-3-1-pro/
0xcb0 11 hours ago||
I'm trying to find the information, is this available on the Gemini CLI script, or is this just the web front-end where I can use this new model?
alwinaugustin 6 hours ago||
I use gemini if i need to write something in my native language- Malayalam or translation. it works very well in writing in Indian regional languages.
fdefitte 11 hours ago||
The benchmark jumps are impressive but the real question is whether Gemini can stop being so aggressively helpful. Every time I use it for coding it refactors stuff I didn't ask it to touch. Claude has the opposite problem where it sometimes does too little. Feels like nobody has nailed the "do exactly what I asked, nothing more" sweet spot yet.
panarchy 12 hours ago||
I had it make a simple HTML/JS canvas game (think flappy bird) and while it did some things mildly better (and others noticeably worse) it still fell into the exact same traps as earlier models. It also had a lot of issues generating valid JS at parts and asking it what the code should be just made it endlessly generate the same exact incorrect code.
pRusya 12 hours ago||
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.

siliconc0w 8 hours ago||
Google has a hugely valuable dataset of changes from decades of changes from top tier software engineers but it's so proprietary they can't use it to train their external models.
onlyrealcuzzo 13 hours ago||
We've gone from yearly releases to quarterly releases.

If the pace of releases continues to accelerate - by mid 2027 or 2028 we're headed to weekly releases.

rubicon33 13 hours ago|
But actual progress seems to be slower. These modes are releasing more often but aren’t big leaps.
gallerdude 13 hours ago|||
We used to get one annual release which was 2x as good, now we get quarterly releases which are 25% better. So annually, we’re now at 2.4x better.
minimaxir 13 hours ago||||
Due to the increasing difficulty of scaling up training, it appears the gains are instead being achieved through better model training which appears to be working well for everyone.
wahnfrieden 13 hours ago|||
GPT 5.3 (/Codex) was a huge leap over 5.2 for coding
rubicon33 8 hours ago||
Eh, sure, but marginally better if not the same as Claude 4.6, which itself was a small bump over Claud 4.5
mark_l_watson 14 hours ago||
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.

throwaway2027 14 hours ago||
Seconded. Gemini used to be trash and I used Claude and Codex a lot but gemini-3-flash-preview punches above it's weight, it's decent and I rarely if ever run into any token limit either.
verdverm 12 hours ago||
Thirded, I've been using gemini-3-flash to great effect. Anytime I have something more complicated, I give it to pro & flash to see what happens. Coin flip if flash is nearly equivalent (too many moving vars to be analytical at this point)
PlatoIsADisease 14 hours ago|||
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.

mark_l_watson 12 hours ago||
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.
nurettin 14 hours ago||
I like to ask claude how to prompt smaller models for the given task. With one prompt it was able to make a low quantized model call multiple functions via json.
zokier 13 hours ago|
> Last week, we released a major update to Gemini 3 Deep Think to solve modern challenges across science, research and engineering. Today, we’re releasing the upgraded core intelligence that makes those breakthroughs possible: Gemini 3.1 Pro.

So this is same but not same as Gemini 3 Deep Think? Keeping track of these different releases is getting pretty ridiculous.

WarmWash 13 hours ago||
Deep Think is a few 3.1 models working together. It was suspected last week that Deep Think was composed using the new 3.1 model.
verdverm 13 hours ago||
3.1 == model

deep think == turning up thinking knob (I think)

deep research == agent w/ search

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