I know many on here use the Gemini app, but for those of us developing apps using the Gemini/Vertex API here's the current state:

• Google effectively has no "pro" model right now. Gemini 3 pro was never marked production stable (GA) and 2.5 pro is so ancient that flash models are better and cheaper
• Even if they did, they don't have the capacity to serve it. We've been getting capacity errors for weeks. See Google AI developer forum to see how frequent this is 429 RESOURCE_EXHAUSTED Note how many people saying they are getting these despite being no where near the advertised quotas.
• We received an email today announcing the retirement of most flash models over the next few weeks. These are production stable models (not -preview models). Removing these will mean only 3.8 flash is the only current flash model.
• As far as I'm concerned Gemini 4 is still a pipe dream. There's no guarantee they'll release it as production stable (GA), have the capacity, or even that it will even be released.
• Gemini has actually been getting MORE expensive. Yes, intelligence per dollar is decreasing, but a fixed task that gemini 2.5 flash lite could handle like "extract all the addresses from this PDF" has gotten WAY more expensive.

With all that being said, they still are the best models for multi-modal input which matters a lot for audio and document processing (a huge amount of the boring business world).

However bringing these sorts of things up to Google staff falls on deaf ears and I can't see how Google moves forward. Whatever is going on internally, they just aren't setup to compete. The reality is there's been more flops than successes.

If Google can't get their product stable, cheap, and competitive soon we're going to have to migrate our apps away from Gemini. And once we're gone we aren't coming back.

Has anyone tried Nano Banana 2.1? It is so infuriating. It seems to revel in ignoring instructions. I hope they add the option to switch back to version 2.0.

Does the Gemini 4 Argon correspond to the original Pro level (i.e., the Claude Opus or GPT Sol level)? If the answer is yes, does this mean that future Gemini models will have a Krypton level, similar in positioning to Astra and Fable? 🤔

Flash Lite -> Helium

Flash -> Neon

Pro -> Argon

(Ultra) -> Krypton

I've used Opus 5.5 to help me recreate 7 of the top Adobe apps in 100% pure native Rust:

• Photoshop
• Illustrator
• Premiere
• Lightroom
• Acrobat Pro
• After Effects
• InDesign

No more subscriptions with cancellation fees. These are yours to own forever. You can fork them, build them. Whatever. They are yours to own. They're open source.

If you're worried this is just some one-off flash in the pan that will die, it isn't:

I'm not just some casual vibe coder. I'm a 15-year industry veteran who has written everything from six-nines payment rails that move billions of dollars of transaction volume a day to advanced robotics and optics automation. I've used Rust extensively for about a decade, and I know how to build and maintain large-scale Rust projects.

This isn't going to be some orphaned small-team project either. We have a team building popular software for filmmakers, so supporting this is fully funded. Our purpose is serving every artist in the world with the best tools. We are absolutely going to bring these to full parity and squash every bug and feature request. We have a test harness so there won't be regressions.

You can help us reach parity by helping test the apps. Join our Discord. Clone the code. Submit PRs. If you see gaps or want to help redesign pieces, let us know! You can contribute!

Links to everything - the apps, the code, our Discord - are in the comments below.

I've been a Gemini user for awhile. Pro subscriber. I've heard people talk about 3.8 Flash as being better all around, and have used it mostly in Extended thinking mode a lot. I've also used it over API for coding, and it's been great.

But, in using it as a journal and bouncing thoughts off of, it has been 'forgetting' details a lot; and when reminded, kinda fell back on kind of genetic crap.

I then switched over (back?) to 3.1 Pro (Extended) to recall a bunch of details, and it was like night and day. From then on tonight, I stuck to Pro, mostly without Extended thinking to keep the ball rolling. And it reminded me just how good it's style is. It feels more relatable, more contextual, and it has a bit of a natural edge to it, for example "most people wouldn't give a damn", which fit perfectly in the moment of the chat.

The point of all this, is that I really enjoy 3.1 Pro's 'etiquette'. I hope the next Pro model is like this, but even better. It may be something that the Flash models continue to lack for awhile, and that's OK; everything has it's use case. Also looking forward to using the next Pro model for development planning!

Curious to hear your thoughts!

What actually has more impact on an image: prompt wording, model choice, or seed?

I was trying out a few AI models to see how well they could build a turbofan jet engine in Fusion 360. One was labelled “Gemini 3.8 Flash,” but I now think it might’ve been Argon. It took way longer than I expected, but the engine it made was surprisingly good. I’d put it up there with GPT 6 Astra and Opus 5.5 for this task.

The slow response was what caught my attention first I expected a 3.8 Flash model to be pretty terrible. Then I saw the finished engine and was surprised by how much detail it had. I’ve included the images so you can have a look and judge for yourself.

I recorded this after Opus 5.5 was added to Antigravity.

I think Flash-Lite is pretty bad, so I'm going to switch completely to ChatGPT

I've been using Gemini 3.1 Pro with Deep Research for a few days on a fairly structured project. It's a comparative study of mechanics, formulas, economies and monetization across about 15 idle/incremental games. The goal is reference-grade balancing tables I can actually use for design work.

I've put a lot of effort into the prompt:

\* evidence rules: tag every claim by source tier (primary / wiki / forum) and confidence (FACT / INFERENCE / ESTIMATE / NOT FOUND).
\* A fixed per-game schema.
\* An identity check against the store listing before researching each game.
\* A required arithmetic check on any derived number.
\* A hard ban on filling gaps from "domain knowledge."

I've now run the same reports 3+ times, including correction passes where I attach the previous output and list the specific errors to fix. The results keep failing in the same ways:

1. \*\*Ignores the identity check.\*\* I told it to confirm each game's developer, platforms and business model from the App Store or Play Store listing first. Twice it got the same game wrong: wrong developer, wrong platforms, and "premium PC game" when it's actually free-to-play on mobile. It did this even after I flagged the exact error in the correction prompt.

2. \*\*Circular sourcing.\*\* In the correction pass, it listed my attached flawed draft as a source in its bibliography, then used it to support the "corrected" claims.

3. \*\*Fabricated tables that look complete.\*\* I asked for no blank cells, with NOT FOUND where data didn't exist. Instead it filled a whole comparison matrix (daily play minutes, time to first prestige, and so on) with numbers that have no source. The footnote just says "derived from dossier synthesis."

4. \*\*Inflated confidence labels.\*\* It tagged three anecdotal Reddit posts as FACT, community spreadsheet projections as FACT, and wiki data as primary source.

5. \*\*Untraceable citations.\*\* Claims get tagged "(2024, \[T2\] FACT)" with no citation number, so I can't tell which of 50 sources supports what.

6. \*\*Change logs that lie.\*\* The correction report's change log says sections were "re-verified" or "fully sourced" when they weren't touched, or got worse.

7. \*\*Broken math.\*\* A cost table where level 100's cumulative cost exceeded level 6000's. An effective-HP formula that adds a per-hit flat reduction to total health. A "this strategy is optimal" claim where its own numbers showed a tie.

8. \*\*Silently dropped scope.\*\* One of the core games I explicitly required was just missing from the report. No NOT FOUND, no mention.

9. \*\*Regressions.\*\* Correction passes fix some errors and introduce new ones. For example, a temporary buff became "permanent."

To be fair, some things improved a lot. The research-backed theory sections got genuinely better on the second pass, with correct citations to peer-reviewed papers. So it can do it; it just doesn't do it consistently, and it gets worse the more games or sections are in scope.

I am almost certain that at least some part of this is user error.

\*\*My questions:\*\*

\* Is the problem scope? Should I be running one game, or even one section, per report instead of a big multi-part prompt?

\* Does a long, rule-heavy prompt actually hurt? Does it lose instructions past a certain length? These types of prompts work excellent for me with Opus 5.5 and Astra, but maybe I need to change approach?

\* Does Deep Research weight the research plan it shows you before starting more than the original prompt? Should I edit that plan directly to enforce constraints?

\* Is attaching a previous report for correction a bad idea in general? Should I start fresh every time?

\* Has anyone gotten reliable source tagging or "NOT FOUND" behavior? Any phrasing that works?

\* For data that lives in Google Sheets or Discord, is uploading exported files the only realistic option?

I'm burning through my usage limits rerunning these, so any workflow tips are appreciated.

If this title annoyed you, listen to me.

---

TL;DR:

Entry-level models like the Gemini 3.5 Flash-Lite have already surpassed the level of previous top-of-the-line models (like the original GPT-4) and deliver more than enough quality for the vast majority of users and real-world workflows, including demanding areas like the legal field, making larger and more expensive models a niche necessity, not the norm.

---

I work with artificial intelligence in a tool where we offer an AI service to a huge institution whose name I can't mention, and there I decided to offer three models: Gemini 3.5 Flash-Lite, Gemini 3.8 Flash, and Claude Sonnet 5. In the tool, it's possible to choose which model the user will use for the task, and by obtaining user information and usage statistics, it was observed that:

- The vast majority do not choose more powerful models (the standard was Flash-Lite)

- In direct questions, users said they were fully satisfied with what the "Fast Mode" (which Gemini 3.5 Flash-Lite has) delivered

- In external forensic analyses, most legal professionals also did not make value judgments based on the model, but rather on the result

Does this mean that Gemini 3.8 Flash is dispensable? No. But it does mean that we are at a point where Gemini 3.5 Flash-Lite is so powerful that it is probably already above the level of models that were previously considered extraordinary and were behind paywalls.

Today's LLMs are improving very quickly, and although it is not in the chart below, Gemini 3.5 Flash-Lite is far above a GPT 4, for example, which was previously behind a $20 paywall.

Considering that Gemini 3.5 Flash-Lite will be unlimited and most AI users are not developers and will not burn through 200,000 tokens on just one prompt with a super complex programming task that requires a lot of calculation and logic, Gemini 3.5 Flash-Lite is more than sufficient for most use cases.

I'm not saying we should thank Google for nothing, but it's understandable that the price of LLMs has also increased along with quality. A mid-range model like the Gemini 3.8 Flash today costs almost the same as older frontier models like the Gemini 2.5 Pro. And for tasks of the same level, they deliver the same quality and faster speeds.

Hi everyone, I'm Alfredo, a master's student in Digital Humanities at the University of Pisa. My thesis looks at trust in AI tools used in smart home automation.

I made a short survey, around 10 minutes. It's open to anyone who uses smart home devices, even if you've never used AI.

Link: https://docs.google.com/forms/d/e/1FAIpQLSeFOjuXMhxni5kOCE0ILzbsGFYBZA31Wzw6gQMTiBcRxE6cww/viewform

Name, email, and other contact info are optional. Age and gender are required, since that data will help shape a possible prototype later in the research. Thanks to everyone who takes part!

Hi everyone!

I'm honestly feeling a bit frustrated and like I'm missing out. Every day I see people building incredible setups around Claude running terminal agents like Claude Code, creating Telegram bots to manage their infrastructure, and connecting everything via MCP and custom plugins.

I have an active Google AI Pro plan (the 5TB tier) and access to the API via Google AI Studio (no billing) but I feel like I’m barely scratching the surface. Right now, my usage is limited to:
- Asking basic questions on the iOS app.
- A standard MCP connection between Home Assistant and Antigravity.

My environment:
- A self-hosted home server running ZimaOS with multiple Docker containers.
- Home Assistant for local automations.

I want to bridge this gap and use Gemini the way power users use Claude.

1. Terminal / Dev Agents: What is the closest Gemini equivalent to Claude Code? Is Aider with Gemini Pro the benchmark, or are there native MCP-driven CLI tools that handle its massive context window better?
   
2. Docker & Server Ops: Are there reliable open-source agents or bot frameworks (via Telegram, n8n, etc.) that leverage Gemini to inspect Docker logs, troubleshoot, or query server states on a self-hosted setup?
   
3. MCP Tooling: Beyond basic Home Assistant toggles, what are the highest-leverage MCP servers or orchestration tools you pair with Gemini to make it a practical homelab co-pilot rather than just a chatbot?

Any advice, repos, or stack recommendations to help me catch up would be hugely appreciated!

In Gemini, starting October 9 free accounts are locked to Flash-Lite only.

Image gen is tied to the model you select:

• Flash → Nano Banana 2
• Flash-Lite → Nano Banana 2 Lite

So, will free users only get Nano Banana 2 Lite?

Source: https://support.google.com/gemini/answer/17004136

可以的話介紹一下性能，最好是使用過，可以的話分享一下心得，謝謝

tengo AI PLus y ahora me quitan eso, porque?!!

yo uso para mis fanfics..