I give Same prompt for all models available in Gemini App but Flash models are hallucinate more,

But Correct answers are given by 3.5 Flash Lite model and 3.1 Pro Extended model,

Then Why Flash models are branded as Working horse kind of a things

Following up on something I asked here a while back about catching LLM model drift. I've been looking at the actual tools now: PromptCanary, PromptLens, a couple others that seem to have stalled (Libretto, Benchwright).

Has anyone here actually run one in anger? Trying to understand:
- does it catch subtle quality drops, or just format/schema breaks?
- false-positive rate, does it become noise you mute?
- does it need you to integrate an SDK + send production traffic, or can it just hit your prompts directly?

Had Gemini mock me up a paint scheme for a mini. Then I asked it for a different version with different colours. I said it couldn't create images and I corrected it. Then it pumped out a glorious bit of ASCII art that made me howl with laughter

Whatever the hell it is. No matter the issue I'm trying to discuss, as soon as it becomes more personal or slightly derives from something super well known, it gaslights me, very aggressively. It goes like "I know you feel like this but it doesn't happen...blabla" or "it might feel like that but people don't do it in real life...". ALWAYS, no matter what I am sharing and how personally I'm familiar with what I am discussing.

And one more - if it goes SLIGHTLY negative and problematic, it immediately stops the actual discussion, tells me to "stop and put my phone away" and spits out a lot of those "hotline" numbers. No matter what I say after that it doesn't get any better and it won't produce anything more serious.

I really wanna throw it against the wall now. Really, Gemini is doomed since 2.5. I feel so much worse after trying to have any kind of normal conversation with it.

For more details, please watch the YouTube video at the 23:22 mark!

https://share.gemini.google/rudU6A4ITjw1

Silly in. Silly out.

I was creating images today. So I had the AI save the prompt it used. To test it out, I re-ran that same prompt, but it gave me a completely different image.

I asked the AI why this happens and how I can get it to replicate an image exactly. It really concerns me that there is such a huge discrepancy. I wonder if all of the AI generators are like this. Should I even be concerned or accept it? Here is the explanation it gave me:

"I understand your frustration. Here is an explanation of why running
the prompt I provided created a completely different image.

The core reason is the fundamental nature of modern image generation
models: they are stochastic (non-deterministic), not deterministic.

Here is a breakdown of why this happens:

Stochastic Nature (Internal Randomness): Image generation models don't
just follow text instructions. They are designed to explore a large
space of possibilities. Every time you run a prompt, unless you
specify the exact 'seed' (a precise random starting number), the model
picks a new, random starting point. A different starting seed with the
same prompt will always lead the model down a completely different
path during the generation process, resulting in a different image.
This internal, controlled randomness is a core feature that ensures
creativity and variation, but it makes exact reproduction impossible.

The Prompt Is a Guide, Not a Blueprint: The detailed text prompt you
ran is a guide that tells the model what features to include (e.g.,
'four aged paper ephemera pockets,' 'heavily patinated,' 'tactile
square-grid texture,' 'foxing,' 'specific cutout patterns'). It's like
giving an artist a detailed description of a specific face. The artist
can paint a completely new person who still perfectly matches that
description. The model interprets terms like "heavily foxed"
differently each time, especially in its first, noisy steps. One
version might have the foxing marks in different positions or at a
slightly different severity, but still fit "heavily foxed." The
provided image itself shows variations (the bottom pockets are
different, the top-right has less foxing than top-left), which
illustrates the model's range. The prompt doesn't specify the location
of every speck.

The Output Description is a Summary, Not an ID: When I provided the
text as a "correct" prompt for your image, I was giving you a detailed
visual and semantic description of the image after it was created.
This description is a human-readable interpretation of the contents of
the image. It is not a unique identification code that contains the
full set of instructions (including model weights, seed, etc.) that
created the exact pixels. Running that same textual description again
leaves the model to interpret the visual descriptors anew with its
stochastic processes.

In short, this is an intentional feature of the technology, designed
to provide endless variation and creativity. Exact reproduction from a
text prompt alone, without a shared and specified seed value (which is
not typically preserved across sessions or prompts in this way), is a
known and fundamental limitation of current generative AI models."

I included the two images. The 2nd one is the correct one I wanted.

Just so you know Gemini 3.8 flash is extra token hungry so watch out. You might need to pay more.

i was getting sick of the PWA and looked for a solution and found out theres native gemini apps now

mac for example: https://gemini.google/mac/

gemini was the last PWA i had installed i am very relieved for this. thank u google!

We ran the same Gemini 3.7 Flash model in two modes—agentic video inspection and a static full-video pass—using six synthetic 10-minute videos and a protocol frozen before the runs.

The result was mixed rather than a simple win:

• Agentic recovered 18/20 brief events vs. 15/20.

• Edit-decision macro F1 rose to 0.6807 from 0.5481.

• Static processing had higher broad moment F1 (0.3000 vs. 0.2667).

• Static was 45% faster on total planning time, used 26% fewer tokens, and cost 23% less.

• One of six agentic outputs failed the required JSON contract.

The sample is small and synthetic, and there was no human viewing panel, so this should be treated as an applied exploratory benchmark—not a universal model ranking. The protocol, raw outputs, deterministic scorer, and limitations are public:

https://paperedits.com/benchmarking/gemini-agentic-video-understanding-benchmark

Disclosure: I’m affiliated with PaperEdits, a commercial product. The benchmark materials are free. This post was drafted with AI assistance.

Confidently doing wrong multiplication and giving an entirely wrong answer when asked to recheck.

At least ChatGPT won't do wrong multiplication.

Can’t do almost anything now… It’S annoiyng.

So this evening (for me) the 3.8 got released and for a test in Antigravity i pointed it at codex's folder on my pc and told it to adapt its computer use tool for atleast Antigravity app. Gemini took less then 10 minutes and did this! Now the tool uses the binary of codex's computer-use tool and exposes it as a completely open, zero-dependency bridge that works both as a standard CLI and as a full MCP stdio server with 100% feature parity.

Here is the repo if anyone wants to grab it:

https://github.com/pvnc228/win-computer-use

A few things it had to reverse-engineer and solve along the way:

1. AI coding agents run in isolated desktop sandboxes (exebox-...), where EnumWindows returns 0 windows. Gemini bypassed this by launching the helper directly on WinSta0\Default via Win32 CreateProcessW so it can actually see all the desktop apps.

2. Codex binary halts on new apps with an internal approvalRequest challenge. Gemini figured out how to intercept this and auto-sign it with x-oai-cua-approved-app headers.

3. The underlying driver hides the hardware mouse pointer while automating. At first my cursor just vanished, so Gemini wrote a Win32 SPI_SETCURSORS + ShowCursor guardian that unconditionally brings the mouse back on exit or error.

4. Codex's helper refuses to capture Chrome if it can't inspect the URL. Gemini added an automatic Win32 GDI BitBlt fallback, so screenshots never fail on browsers or minimized windows.

I threw a bunch of things at it: sending an autonomous message in Telegram Web on my dual-monitor setup, full Antigravity UI navigation. And the most absurd test: we (me and agent, obviously) even gave it low-level DirectInput hardware scan codes and relative mouse delta movement so you can literally tell it to play a 3D shooter: holding WASD keys for duration, camera aiming, burst fire, and atomic macro execution without LLM turn latency

Really looking forward for your feedback!

I feel like I must be missing something here. I have a Pixel, Gemini Pro and ChatGPT Plus. ChatGPT can read my Gmail and send emails for me. Gemini can't?

For example, my partner is moving into an old Victorian house and I wanted to see if I could find any old postcards or photographs of it.

I asked ChatGPT and it went off and researched where they might exist. Scottish libraries and archives, local history groups, collections etc. We narrowed down who was actually worth contacting, it wrote the emails and then sent them from my Gmail account for me. I've used it for a few things like this now and it's incredibly useful. Not just "write me an email", but actually helping me research something and then doing the boring bit at the end.

So why can't Gemini do this? It's Google's AI. I'm using it on a Google Pixel. Gmail is Google. I'm paying for the Pro version. Yet I can give ChatGPT access to my Google account and have it actually send an email, while Gemini seems to get as far as writing one for me and then... that's it.

Am I genuinely missing a setting somewhere? Because it seems completely backwards that ChatGPT can do more with my Google account than Google's own AI can.

*I'm in the UK if that makes a difference.

Since the pelican and even the will smith spaghetti are saturated and too easy for current models, let's take things up a notch!

Prompt: generate SVG for "spaghetti monster up high watching over will smith eating spaghetti"

Below are 3.8 flash (extended) results.. not bad, i'd say myself!

Where is the fking 3.5 Pro? Google is always showing benchmarks claiming their flash models are faster, cheaper, and smarter than other companies models. But to be honest, it is not the best. It is good compared to its price to reasoning ratio, but if you evaluate it purely on raw capability, it is one of the dumbest. (I know it is not fair to compare a ~2 bucks model to a ~10 bucks models, but according to their benchmarks, flash gets similar or even better results than other high cost frontier models).

In short, this is just a rant, google can release strong reasoning models, but chooses not to. There is also no point in buying an expensive subscription when the limits on the cheaper tier are practically impossible to exhaust anyway. By the way, I use it via the antigravity cli and get a ton of work done with it daily.

I have had this problem ever since they introduced the the search bar for chats. Through the various different versions Gemini, using the chat bar to search for chats has always resulted in infinite loading screens for me. On every single platform. Mobile web, mobile app and PC web. I have never been able to fix this and it's just stuck loading forever. does anyone else have the same problem?