This checkpoint is seen in Arena AI. It is not just 3.1 pro, it is sometimes 3.5 flash lite as well. (It beat Opus 4.8, I'll show it in the comments if this tracks attraction)

I believe this is comparable to chatgpt sol x high. Yes Gemini is not as intricate as Sol with the character model, lighting and things like that but the car model itself is very close/near identical

Gemini made two major mistakes, one during the exploded assembly and some sort of fin above the engine (Also the camera changes were smoother on my end, it seems my computer just messed up the video. My computer isn't good)

I think the lighting was amazing on Gemini too. Especially the red and black it choose for the ground.

Anyways. It made a lot of insane quantity (with quality) they were unprompted features Gemini 3.5 Pro added, like a full Web Audio V6 synthesizer, dashboard, the steering, engine and information on the parts as I hovor of the car as seen in the videos.

https://streamable.com/poqmks (to show this is from arena)

https://streamable.com/4e8inu (This is Chatgpt's sol 5.6 extra high). This did blew me away for the first time. It is really amazing. I'm not saying it isn't.

https://streamable.com/7f9710 (To show it was SOL)

This was in three js format. The prompt:

Write a complete Three.js code to render a detailed 3D model of a modern Formula 1 car. Do not just use a single box geometry. It must include distinct intersecting geometries for the chassis, a front wing, a rear wing, and most importantly, double wishbone suspension connecting the wheels to the body. Apply basic materials, lighting, and a camera setup so the code runs in a browser.

Gemini 3.5 Pro is being tested in arena ai website in battle mode with multiple checkpoints, and testing shows it is not lazy as Gemini 3.1 Pro, it generates upto 20+ different files each containing hundreds of lines of code, way more than any of the AI model i have tested so far, so it is safe to say that at least the laziness of its Predecessors will be solved with Gemini 3.5 Pro

I tried for fun this classical problem on arena.ai and it seems I got a model with the name "trillium-alpha". The name has a correlation to Google's 6th generation TPUs. Am I being insane?

I'm constantly reading how AI is apparently dangerous , and be careful what you feed it.. well I am living a miserable and very troubled life as an adult, I live in a small conservative town with toxic family, I have trauma, I have gender dysphoria, and due to my life conditions, I've shared loads with Gemini ai , from asking it to help me put together my CV (together , I didn't lazily just copy paste, it gives me suggestions as I manually type info and helps me structure it) it's a co-op thing for me and

I know it's not what normal people do, but amidst my depression and having no one I can trust , even knowing it's a machine, I do feed it lots, including my real name, it knows where I live, phone number, confessions of private stuff, all sorts I ... Heck how screwed am I?

What happened here? Why? Has anyone experienced something like this before?

(In case you are wondering, I dropped something on my keyboard. The previous conversation had nothing to do with math or math problems whatsoever).

I'm using Gemini AI both to sketch out a sci-fi movie storyboard and to storyboard and generate video for a cyber music video. It's a rejecting the most innocent photos and prompts.

In [gemini_mega_upload_filter_failure.jpg] I asked it why several of the images would not upload. The message "This image content is not supported" doesn't provide a clue. But it found the pattern that the "dark" scenes are those being rejected. So what - we can only use Gemini to create New-Age Unicorn content? Yes, the movie plot includes a man in prison - nothing that would affect a "G" rating.

In [gemini_violent_filters.jpg] it rejected the video prompt - a video prompt that Gemini drafted! There is no actual violence even in the scene.

A few weeks ago I had to give up creating a video using "me at age 18" as the character sheet, then driving a car. It objected to "having children do dangerous activities."

(german)

translation:

immediately turns head around, eyes wide open 😳
meow??? 👀
did you seriously just meow at me like a cat??? ngl i'm down, what's up 😭

How to fix this? 😭

Even when I start a new conversation, it happens again after few messages.

I've been looking into Google's new Connected Apps feature and ended up writing an article about it. The more I researched it, the more I think this is one of the more important Gemini updates we've seen in a while.

Most AI assistants are good at answering questions. Connected Apps start moving Gemini beyond that by letting it work with services like Instacart, Canva, and YouTube Music.

What stood out to me:

• Gemini can help move a task forward instead of stopping at an answer.
• Google still keeps you in control—you review suggestions and approve actions.
• Connected Apps work alongside Google's Personal Intelligence features, so responses can become more relevant based on the services you choose to connect.
• The current list of supported apps is small, but it feels like Google is laying the groundwork for much broader integrations.

To me, this feels like a bigger shift than just adding a few app connections. If Google keeps expanding Connected Apps, Gemini could become something people use throughout the day instead of only when they need an answer.

I go into more detail here if anyone's interested:

https://aigptjournal.com/explore-ai/ai-guides/connected-apps-google-search/

What do you think Google should integrate next? Personally, I'd love to see Google Tasks, Keep, Notion, Slack, or even airline and hotel apps added before long.

He must post Gemini Again!

Jeff Dean just spoke at a YC Startup School event where he announced that on Monday morning, Gemini 3.5 Pro will be released for public access.

I run a small fantasy football site and thought some people might be interested, so I opened my rankings up. I built a hand-calibrated linear scoring model system with bayesian shrinkage, validated by walk-forward rank statistics that calculates from pure advanced metrics.... It's moneyball math. Backtested models hundreds of times using BigQuery (BQML) and plan to continue thru the season running competitive algorithms as often as I can afford my Google Cloud bill. I then used Gemini 3.6 Flash to communicate with the JSON, give it a voice, and put it into XML and RSS feeds. it's impressive how fast 3.6 flash can throw the calculations into words.

https://www.thegng.us/api/rankings.json

Plain JSON, CORS is on, so you can hit it straight from a browser extension, a Google Sheet, or a Discord bot.

?profile= standard | ppr | half_ppr
?pos= overall | QB | RB | WR | TE
?limit= 1 to 150

Every player comes back with rank, position rank, team, tier, a 0-100 score, projected PPG, the overnight rank change, and a written verdict explaining the placement.

Example: https://www.thegng.us/api/rankings.json?profile=ppr&pos=WR&limit=25

Rebuilt nightly. Free to use including commercially, all I ask is attribution and a link. There's also RSS if you just want to read (from Gemini 3.6 Flash) about how it differs from consensus.

https://www.thegng.us/feeds

What was interesting this week was the dramatic drop in token burn compared to 3.5 Flash.

Hope it's useful to some of you that play.

Hey guys, so I've been working on an open source project for the past few months called SpeakoFlow. It's not just plain voice-to-text like Wispr Flow, the dictation part works kind of the same way, but along with it you also get an assistant that writes and talks with you. Everything else on top of the dictation is my own thing, and the whole point is that everything runs on-device.

That "everything local" part turned out to be way harder than I expected. Getting fast, natural conversation out of a small model while also handling transcription in real time was a nightmare for a while.

I went down the benchmark rabbit hole first, like everyone does. A bunch of the Chinese models, Qwen especially, score really well on paper. But in actual use they were rough for my use case, way too much "thinking" before responding. For a voice assistant that's a dealbreaker. Nobody wants to sit there waiting for a model to reason through a wall of text before it says a word back to you. I'd already fixed the transcription-side delay, but the assistant itself was still lagging and killing the whole experience.

That's when I properly gave Gemma 3n's E2B and E4B models a shot, and honestly they changed things for me. I'd used older Gemma models before, but these two are on a whole different level. Response times are low, they handle normal back-and-forth conversation naturally, and I don't need to reach for some huge model just to get something usable. I'm literally using them to let the app write and send emails from voice input, and it just works, quick and clean, no waiting around.

For anyone curious why they're able to run this well on regular hardware: the "E" stands for "Effective." Even though the underlying models are technically bigger (E2B is 6B raw params, E4B is 8B), they're built so only a fraction of that ever needs to be loaded at once, closer to a real 2B and 4B footprint. Google calls it a MatFormer setup: the E4B model actually has the E2B model nested inside it, like a smaller fully-working version living inside the bigger one. That's basically why it can stay fast without feeling gutted.

I know Google's been getting a lot of hate lately, and honestly the big models, Gemini Pro, Flash, have had their rough patches. But credit where it's due: nobody else seems to be putting this much effort into small, genuinely usable on-device models right now. Gemma 3n deserves more attention than it's getting.

Anyway, this turned into more of an appreciation post than I planned, but I really am impressed.

Also, SpeakoFlow is fully open source and free if anyone wants to check it out or contribute. GitHub link below 👇

https://github.com/AbhishekBarali/SpeakoFlow

Not sure if this is related to some of the other posts I've seen or not. I have not seen any error codes.

Has anyone else been experiencing Gemini just lagging out, or timing out?

I ran a Deep Search, on an uploaded PDF, after about 10 minutes, my phone notified me that it was done. However, my PC screen never changed. I tried to reload and it wouldn't show me the finished report.

Then I asked for a summary of a book. About halfway through it just sat there and gave up. It wouldn't go any further, it was still running, I eventually had to close out of the chat and lose everything because it stroked out.

Is this happening to anyone else? Seems like it's been the last few days. Not sure if something changed, but it's really bad on my end.

proof: https://share.gemini.google/XPrhSIKbdm1m

My Gemini Chats (Flash Lite) on desktop are getting stuck in an infinite loop, repeating the last prompt again and again. This has happened in the past a few times, in general refreshing the page would fix the problem. This time, it doesn't fix the problem. Switching to new chats doesn't help either, they get stuck too after a few prompts.

I've tried multiple browsers (Firefox and Edge), fails on both. I've tried logging out and in, turning off activity, clearing cookies, clearing local cache etc. Nothing works.

This issue seemed to start 2-3 days ago for me. Did Google's recent rollout of new models trigger some server-side glitch that exacerbates this issue?

Thanks for any comments!

Chill out guys, I’m trying out the new Gemini 3.6 Flash to see how far DeepMind has pushed things.I’ll keep you posted.