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RobinL
- Anyone have any idea why it says 'confidential'?

- Anyone actually able to use it? I get 'You've reached your rate limit. Please try again later'. (That said, I don't have a paid plan, but I've always had pretty much unlimited access to 2.5 pro)

[Edit: working for me now in ai studio]

sd9
How long does it typically take after this to become available on https://gemini.google.com/app ?

I would like to try the model, wondering if it's worth setting up billing or waiting. At the moment trying to use it in AI Studio (on the Free tier) just gives me "Failed to generate content, quota exceeded: you have reached the limit of requests today for this model. Please try again tomorrow."

netdur
On gemini.google.com, I see options labeled 'Fast' and 'Thinking.' The 'Thinking' option uses Gemini 3 Pro
mil22
It's available to be selected, but the quota does not seem to have been enabled just yet.

"Failed to generate content, quota exceeded: you have reached the limit of requests today for this model. Please try again tomorrow."

"You've reached your rate limit. Please try again later."

Update: as of 3:33 PM UTC, Tuesday, November 18, 2025, it seems to be enabled.

informal007
It seem that Google doesn't prepare well to release Gemini 3 but leak many contents, include the model card early today and gemini 3 on aistudio.google.com
guluarte
it is live in the api

> gemini-3-pro-preview-ais-applets

> gemini-3-pro-preview

__jl__
API pricing is up to $2/M for input and $12/M for output

For comparison: Gemini 2.5 Pro was $1.25/M for input and $10/M for output Gemini 1.5 Pro was $1.25/M for input and $5/M for output

dktp
It's interesting that grounding with search cost changed from

* 1,500 RPD (free), then $35 / 1,000 grounded prompts

to

* 1,500 RPD (free), then (Coming soon) $14 / 1,000 search queries

It looks like the pricing changed from per-prompt (previous models) to per-search (Gemini 3)

GodelNumbering
And of course they hiked the API prices

Standard Context(≤ 200K tokens)

Input $2.00 vs $1.25 (Gemini 3 pro input is 60% more expensive vs 2.5)

Output $12.00 vs $10.00 (Gemini 3 pro output is 20% more expensive vs 2.5)

Long Context(> 200K tokens)

Input $4.00 vs $2.50 (same +60%)

Output $18.00 vs $15.00 (same +20%)

xnx
If the model solves your needs in fewer prompts, it costs less.
aliljet
When will this be available in the cli?
[deleted]
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skerit
Not the preview crap again. Haven't they tested it enough? When will it be available in Gemini-CLI?
prodigycorp
I'm sure this is a very impressive model, but gemini-3-pro-preview is failing spectacularly at my fairly basic python benchmark. In fact, gemini-2.5-pro gets a lot closer (but is still wrong).

For reference: gpt-5.1-thinking passes, gpt-5.1-instant fails, gpt-5-thinking fails, gpt-5-instant fails, sonnet-4.5 passes, opus-4.1 passes (lesser claude models fail).

This is a reminder that benchmarks are meaningless – you should always curate your own out-of-sample benchmarks. A lot of people are going to say "wow, look how much they jumped in x, y, and z benchmark" and start to make some extrapolation about society, and what this means for others. Meanwhile.. I'm still wondering how they're still getting this problem wrong.

edit: I've a lot of good feedback here. I think there are ways I can improve my benchmark.

t0mas88
Google reports a lower score for Gemini 3 Pro on SWEBench than Claude Sonnet 4.5, which is comparing a top tier model with a smaller one. Very curious to see whether there will be an Opus 4.5 that does even better.
CjHuber
Interesting that they added an option to select your own API key right in AI studio‘s input field. I sincerely hope the times of generous free AIstudio usage are not over
ponyous
Can’t wait to test it out. Been running a tons of benchmarks (1000+ generations) for my AI to CAD model project and noticed:

- GPT-5 medium is the best

- GPT-5.1 falls right between Gemini 2.5 Pro and GPT-5 but it’s quite a bit faster

Really wonder how well Gemini 3 will perform

Der_Einzige
When will they allow us to use modern LLM samplers like min_p, or even better samplers like top N sigma, or P-less decoding? They are provably SOTA and in some cases enable infinite temperature.

Temperature continues to be gated to maximum of 0.2, and there's still the hidden top_k of 64 that you can't turn off.

I love the google AI studio, but I hate it too for not enabling a whole host of advanced features. So many mixed feelings, so many unanswered questions, so many frustrating UI decisions on a tool that is ostensibly aimed at prosumers...

ttul
My favorite benchmark is to analyze a very long audio file recording of a management meeting and produce very good notes along with a transcript labeling all the speakers. 2.5 was decently good at generating the summary, but it was terrible at labeling speakers. 3.0 has so far absolutely nailed speaker labeling.
thedelanyo
Reading the introductory passage - all I can say now is, Ai is here to stay.
wohoef
Curious to see it in action. Gemini 2.5 has already been very impressive as a study buddy for courses like set theory, information theory, and automata. Although I’m always a bit skeptical of these benchmarks. Seems quite unlikely that all of the questions remain out of their training data.