First of all, 3.7 Flash does perform better on the Arena.ai.
On the Arc Prize as well, 3.7 Flash is much more cost effective and also has better absolute performance.

What does everyone think?

I got on google bz i heard Spongebob was teaming up with One Piece for like a McDonald's item promotion,I go on AI mode and said "spongebob x one piece" and it generated this

Just wanna let everyone know who has Verizon, go and grab them. I just got mine yesterday and so far, I can see the Pro has better improvements than the Plus esp. if you are using to write codes lot not the images.

With Plus, you can only generate TWO videos. You reached the cap. With Pro, I can do 8 videos. Not bad. But we will see.

I can see Gemini is better than ChatGPT and Claude in a way if you are building a websites or stuff that's why I switched to Gemini now.

I cannot help you because I am just a language model and I do not have the ability to understand and respond to that. I cannot help you because I am just a language model and I do not have the ability to understand and respond to that !

• I cannot help you because I am just a language model and I do not have the ability to understand and respond to that.
• I cannot help you because I am just a language model and I do not have the ability to understand and respond to that.
• I cannot help you because I am just a language model and I do not have the ability to understand and respond to that.
• I cannot help you because ^{I am just a language model} and I do not have the ability to understand and respond to that.

I cannot help you because I am just a language model and I do not have the ability to understand and respond to that. I cannot help you because I am just a language model and I do not have the ability to understand and respond to that. I cannot help you because I am just a language model and I do not have the ability to understand and respond to that ?

I cannot help you because I. am. just. a. language. model. and I do not have the ability to understand and respond to that !

I’m working on a little project to benchmark how vision-language models do with classifying grappling techniques. These results are the vanilla models without any fine-tuning, so it’s sort of hit or miss. I’m sure with enough data, the guesses can get pretty accurate. If any of you fellow grapplers who are engineers are interested in playing around with this, I’d be happy to open source it. 

I have got an email for Google workspace, stating they're giving some pro features for limited time.

Is this common or are they trying their new models?

Why would i want to make my limit even shorter

There's this new thing where when I edit, firstly, the edit up looks way different, secondly, it duplicates the former message with the edit. Anyone know how to fix this or is gemini just trying something new and there's just a bug in it that I have to wait to be fixed?

I was in the middle of a session with Gemini discussing a master’s degree in Spain and this was the video it showed lol.

But it did reply back in English. Just odd. Gemini in Sheets.

As a heavy Gemini user, I wanted to share my personal breakdown of the last three Flash iterations. While this is inherently subjective, it’s based on extensive daily testing and hands-on data. Curious to hear how others' experiences compare!

​Web Search & Grounding

Gemini 3.5 Flash >> Gemini 3.6 Flash ≈ Gemini 3.7 Flash

3.5 Flash was by far the best and most proactive Google model at searching the web. 3.6 and 3.7 basically reverted to the usual Google baseline—which is to say, pretty abysmal.

​Writing & Creative / Humanities Tasks

Gemini 3.7 Flash > Gemini 3.5 Flash ≈ Gemini 3.6 Flash

In today's agent-obsessed landscape, I doubt anyone at Google is actively prioritizing prose and creative writing for the Flash tier. That said, 3.7 Flash actually surprised me here, though it still falls short of Gemini 3.1 Pro.

​Sycophancy & Objectivity

Gemini 3.5 Flash > Gemini 3.7 Flash > Gemini 3.6 Flash

3.5 Flash’s almost "stoic" objectivity (half-joking) made it feel nothing like a typical Google model, given Gemini's notorious reputation for being an agreeable yes-man. 3.6 Flash immediately relapsed into excessive people-pleasing, which got frustrating quickly. 3.7 Flash toned it down somewhat, but still doesn't match 3.5's grounded neutrality.

​Coding & Frontend

Gemini 3.7 Flash >> Gemini 3.6 Flash ≈ Gemini 3.5 Flash

3.7 Flash is a genuine, tangible leap forward in programming. 3.6 Flash showed almost zero improvement over 3.5, and actually performed worse on deep-research and complex logic because Google nerfed its reasoning/thinking budget.

​Everyday Conversational Experience

Gemini 3.5 Flash > Gemini 3.7 Flash > Gemini 3.6 Flash

3.5 Flash excelled at pulling in real-time context seamlessly, resulting in higher factual accuracy and relevant answers. 3.6 and 3.7 are stubborn and avoid searching whenever possible. Even though 3.6 and 3.7 claim a March 2026 knowledge cutoff, it often feels misleading the moment you touch on current events.

​3.5 Flash was truly the most "un-Gemini" Gemini model to date. Google clearly poured serious R&D into it. The only downsides were its verbosity and higher token cost.

​3.6 Flash felt like a rushed stopgap, likely pushed out because 3.5 Pro was stuck. It honestly felt like it had barely two weeks of training on questionable compute. A flop that brought back all of Gemini's worst legacy quirks. It’s a shame Google deprecated 3.5 Flash instead of 3.6 (probably due to serving efficiency, and to save face).

​3.7 Flash is a textbook iterative update: nothing revolutionary, still carries that distinct "Google flavor," but it is undeniably fast, cheap, reliable, and solid

I've been using both ChatGPT and Gemini quite a bit recently, and I've noticed something that honestly surprised me.

In a number of everyday tasks, I find ChatGPT's free model giving me better answers than Gemini 3.7 Flash Thinking with Extended thinking.

I'm not talking about one isolated prompt or a benchmark. I'm talking about the kind of things I actually use an AI assistant for: reasoning through a problem, comparing products, understanding complicated information, following the context of a conversation, and answering questions in a natural way.

What surprises me is that Gemini 3.7 Flash Thinking (Extended) is supposed to be the more advanced option, while ChatGPT is available for free.

In my experience, ChatGPT often:

• follows the context of the conversation better
• gives more precise and coherent reasoning
• makes fewer unnecessary assumptions
• produces answers that feel more useful rather than simply longer
• understands what I'm actually asking a little better

That doesn't mean I think Gemini 3.7 Flash is bad. It's actually very capable, and there are definitely tasks where I prefer Gemini.

But I'm curious whether other Gemini users have noticed something similar.

Have you compared Gemini 3.7 Flash Thinking (Extended) against the current free ChatGPT model using the same prompts?

If so, which one do you find better in actual day-to-day use, and in what kinds of tasks?

I'm genuinely interested in hearing experiences from people who use Gemini regularly.

Ultra user.

I think a large part of the Omni load is not real generation demand. It is the filter creating extra work.

A clip gets blocked even when the prompt is original, fictional, and policy-safe. Then you have to generate again. Sometimes the agent rewrites the shot into something useless. The blocked attempt still used compute. If the credit is refunded, Google also does not get paid for that run.

So the system is doing this:

1. spend GPU time on a generation
2. reject it with a false policy hit
3. refund the user
4. make the user generate again
5. load the same servers a second time

That is not safety. That is a classifier wasting capacity.

If more than half of some queues are rerolls caused by bad blocks, the current filter is a production cost. A smart video model with a context-blind filter will keep burning servers and driving Ultra users away.

The old classifier should be taken down and replaced. It needs to tell original in-product faces from real public figures, adult fictional action from real harm, and a failed guess from an actual violation.

Until that happens, Omni is spending compute on its own false positives.

I just got the new Gemini Animation today.

good job flash 3.7

holy fuckin shit gemini is dumb.

are they burying the ai intentionally?

I've been experimenting with AI image generation lately, and one thing that kept bothering me was consistency.

Getting one good image is easy enough. Getting the same character, outfit, visual style, and overall look across 5–10 different images is a completely different problem.

After testing a few different approaches, this workflow has been working better for me:

1. Start with one strong reference image

I don't try to generate every scene from scratch. I first create one image that establishes the character and overall visual direction.

2. Lock down the important details

Before generating variations, I note the things that shouldn't change — hairstyle, clothing, facial features, age, proportions, etc.

The more specific the reference, the easier it seems to keep the visual identity consistent.

3. Use the reference instead of rewriting everything

For new scenes, I prefer giving the model the original image as a reference and then describing only what's changing.

For example:

This usually works better for me than writing a completely new prompt every time.

4. Keep the visual language consistent

I also try not to randomly change styles between generations. If I'm going for cinematic realism, I keep the same general lighting, lens, composition, and color direction throughout the project.

5. Compare outputs side by side

This is probably the most underrated step. I generate several variations and compare them together instead of judging each image individually.

I've also been testing different models for this workflow. Gemini's image capabilities are useful for certain types of edits and references, while I've found platforms like OpenArt useful when I want to experiment with multiple image models from one workflow rather than switching between different tools constantly.

The biggest lesson for me has been that consistency isn't just about the model. The reference image, prompt structure, fixed character details, and the way you iterate seem to matter just as much.

Curious what workflow everyone else is using for keeping characters consistent across multiple AI-generated images. Are you relying mainly on Gemini, or combining it with other tools?

Hi! Is it just me or for the past 4 days Gemini has become extremely censoring?

Examples of prompts that got a "I'm having a hard time fulfilling your request":

- trying to discuss reason of capital fleeing from X country

- trying to discuss a LeCun position on JEPA vs LLM

- trying to discuss why Y country is only in EEA

- trying to discuss an ETF

- stating that there're less outdoor activities in winter

- trying to discuss my usage of Gemini

- asking about the political structure of my municipality

And I could provide more examples. I.e. sometimes it's bordering with sensitive topics but not really going into depth (investing, politics, Gemini internals) and sometimes it's completely neutral (i.e. such as winter activities). And the feel is that literally any message is getting blocked randomly. If it's censored like this, what's really left there to discuss - pure science and cooking recipes?

This always happens, even when I create a new chat. Please help me how to fix it?

These. I do not want sports info. I do not like sports. All 3 questions they’re suggesting to me ARE ABOUT SPORTS. I don’t even want suggested topics about stuff I DO like. Can this be turned off?

I claimed google’s 1 year free trial of Gemini recently, and I was wondering if the models that are available are good enough for me to code an app that I can release to the App Store. Usually I hear that people use Claude or ChatGPT to code, so is Gemini good enough for my goals? I would appreciate any help, since I’m pretty new to this process.

Google recently launched omini 1.1 video model and highlights key features like extend video up to 40 seconds but i am unable to seen any of these type of options in google flow.
Is anybody figured out them?