Gemini 3.0 spotted in the wild through A/B testing

I agree with you, I consistently find Gemini 2.5 Pro better than Claude and GPT-5 for the following cases:

* Creative writing: Gemini is the unmatched winner here by a huge margin. I would personally go so far as to say Gemini 2.5 Pro is the only borderline kinda-sorta usable model for creative writing if you squint your eyes. I use it to criticize my creative writing (poetry, short stories) and no other model understands nuances as much as Gemini. Of course, all models are still pretty much terrible at this, especially in writing poetry.

* Complex reasoning (e.g. undergrad/grad level math): Gemini is the best here imho by a tiny margin. Claude Opus 4.1 and Sonnet 4.5 are pretty close but imho Gemini 2.5 writes more predictably correct answers. My bias is algebra stuff, I usually ask things about commutative algebra, linear algebra, category theory, group theory, algebraic geometry, algebraic topology etc.

On the other hand Gemini is significantly worse than Claude and GPT-5 when it comes to agentic behavior, such as searching a huge codebase to answer an open ended question and write a refactor. It seems like its tool calling behavior is buggy and doesn't work consistently in Copilot/Cursor.

Overall, I still think Gemini 2.5 Pro is the smartest overall model, but of course you need to use different models for different tasks.

Yeah it’s really good. A few weeks ago, some third party script was messing with click events of my react buttons so I figured I should just add a mousedown even to capture the click before the other script. It was late at night and I was exhausted so I wanted to do a quick and dirty approach of simulating a click after a few ms after the mousedown even. So I told Gemini my plan and asked it to tell me the average time in ms for a click event in order to simulate it… and I was shocked when it straight up refused and told me instead to trigger the event on mouseup in combination with mousedown (on mouse down set state and on mouse up check the state and trigger the event). This was of course a much better solution. I was shocked at how it understood the problem perfectly and instead of giving me exactly what I asked for it gave me the right way to go about it.

I prefer it too, but I find it a bit too wordy. It loves to build narratives. I think this is a common theme with all of Google’s LLMs. Gemma 27B is by far the best in its class for article generation.

I find Claude and Gemini to be wildly inferior to ChatGPT when it comes to doing searches to establish grounding. Gemini seems to do a handful of searches and then make shit up, where ChatGPT will do dozens or even hundreds of searches - and do searches based on what it finds in earlier ones.

Agreed, and its larger context window is fantastic. My workflow:

- Convert the whole codebase into a string

- Paste it into Gemini

- Ask a question

People seem to be very taken with "agentic" approaches were the model selects a few files to look at, but I've found it very effective and convenient just to give the model the whole codebase, and then have a conversation with it, get it to output code, modify a file, etc.

For pure text responses, agree 100%. Gemini falls way short on tool/function calling, and it's not very token-efficient for those of us using the API. But if they can fix those two things or even just get them in the same ballpark like they did with flash and flash-lite, it would easily become my primary model.

> consistently found Gemini to be better than ChatGPT, Claude and Deepseek

I used Pro Mode in ChatGPT since it was available, and tried Claude, Gemini, Deepseek and more from time to time, but none of them ever get close to Pro Mode, it's just insanely better than everything.

So when I hear people comparing "X to ChatGPT", are you testing against the best ChatGPT has to offer, or are you comparing it to "Auto" and calling it a day? I understand people not testing their favorite models against Pro Mode as it's kind of expensive, but it would really help if people actually gave some more concrete information when they say "I've tried all the models, and X is best!".

(I mainly do web dev, UI and UX myself too)

It's definitely not just you. Gemini is the only one that's consistently done anything actually useful for me on the kinds of problems I work on (which don't have a whole lot of boilerplate code). Unlike the other models it occasionally catches real errors in complex reasoning chains.

> The longer a chat goes, it gets worse very quickly.

This has been the same for every single LLM I've used, ever, they're all terrible at that.

So terrible that I've stopped going beyond two messages in total. If it doesn't get it right at the first try, its more and more unlikely to get it right for every message you add.

Better to always start fresh, iterate on the initial prompt instead.

Gemini 3.0 isn't broadly available inside Google. There's are "Gemini for Google" fine-tuned versions of 2.5 Pro and 2.5 Flash, but there's been no broad availability of any 3.0 models yet.

Source: I work at Google (on payments, not any AI teams). Opinions mine not Google's.

Hate to spoil this excitement, but we at Google do not have Gemini 3 available to us for use in Vibecoding.

Which should surprise no one. LLMs are reaching diminishing returns, unless we find a way to build GPUs more cheaply.

This was cool: https://codepen.io/ChetasLua/pen/yyezLjN

Somewhat amusing 4th wall breaking if you open Python from the terminal in the fake Windows. Examples: 1. If you try to print something using the "Python" print keyword, it opens a print dialog in your browser. 2. If you try to open a file using the "Python" open keyword, it opens a new browser tab trying to access that file.

That is, it's forwarding the print and open calls to your browser.

Bet on it!

https://manifold.markets/ItsMe/gemini-3-releases-october-22