From my experience, this thing is crazy fast.

Spawn 10 on the same problem and have them debate to reach a consensus, you’ll get Fable-like results but 100x faster.

Really, what's up with Gemini still not supporting connectors/MCPs/plugins/whatever-they're-called-this-month on web? It makes it a non-starter for any kind of serious use.

Their naming scheme is confusing. Branding has never been Google's strong suit and their marketing copy is pretty bottom-of-the-barrel[0]. Anthropic has a pretty clear set of models but Gemini decided to rebrand their Flash as Flash Lite (and presumably the future will see a Flash Lite Mini, a Flash Lite Mini Nano and a Flash Lite Mini Nano 3B) which confuses the pricing to high hell.

This plus the Vertex, AI Studio, Gemini, Antigravity. It's honestly too confusing to use. I need to use Gemini just to decide on which platform and which model to consider.

0: Famous Kurian Tweet: "We're announcing Duet AI for Google Workspace will now be Gemini for Google Workspace. Consumers and organizations of all sizes can access Gemini across the Workspace apps they know and love. We're introducing a new offering called Gemini Business, which lets organizations use generative AI in Workspace at a lower price point than Gemini Enterprise, which replaces Duet AI for Workspace Enterprise."

The mention of an "ambitious" gemini 4 pre-train signals to me that 3.5 pro is probably a lost cause.

That being said, it seems that Gemini is still the best image analysis model, so hopefully 3.6 flash builds on this even more.

Here's the issue:

GLM 5.2 is better, also cheaper, and almost as fast.

So essentially, a big L for Google. Combine this with them not being able to produce a frontier model this generation... hmm implications

Wow, Laguna S 2.1 (released today) just destroys Flash-Lite underly and completely. What a weak and embarrasing release from Google.

I have a side business selling custom fingerprint jewelry and I use gemini nano banana to clean up customer submitted fingerprint images. This was a step I used to do by hand at 10 - 15 minutes per image and nano banana is the first model that is able to do the task (it is astonishingly good at it). I can't wait to see what the next nano banana can do, hopefully its released soon.

Wow - Google does not even bother to show benchmarks of these models compared to the frontier and Chinese labs - only against previous versions. I'm not surprised. Having worked there for years it was amazing just how inwardly looking the company is.

Google seems to have anorexia when it comes to model intelligence. They have an internal hard constraint on price per token it seems, and they are trying to squeeze out intelligence with limited compute.

I wonder if there is something with their TPU cycles that makes them want to postpone training a new model. My guess is that they have been on the same base model for 6 months and they may have waited for the next gen TPUs to train Gemini 4, which greatly limits how much intelligence they can increase and forces them to do cost efficiency increases.

Unfortunately says more about how competitive 3.5 pro would be today at the frontier if they forgo it for 3.6 flash.