I'm not at all an industry pundit. But I suspect there's a reason we're not seeing leading models from Google recently.

Judging from my own frustrating attempts to use Gemini for vibe-coding, it seems like Google is badly over-sold (i.e., under-provisioned).

From all those promos giving away their pro-level subscription with phones; spinning up a mid-level subscription to undercut other providers and (probably most significantly) putting AI queries into ever search response because their flagship search product had become useless; they're promising a lot more processing to customers than they can reliably deliver.

The recent iterations seem to be intended not to push the capabilities forward, but to deliver capabilities at the current level while consuming less resources. That will allow them to maintain their trajectory until (I'm expecting) they get the huge infusion of extra compute resources from Space X later this year.

If I'm right, then I expect we should see Google start pushing forward again (rather than more of this lateral stuff) by the end of the year.

Official announcement

https://blog.google/innovation-and-ai/models-and-research/ge...

This model is not for builders and engineers. DeepSWE score of 49% is behind gpt 5.4 and muse spark. It's clearly intended to be an efficient model for google gemini usage.

What is interesting is how this is announced before any Gemini Pro progress. From the outside it seems as though Google cannot keep up with other frontier models.

I assumed google would lean into the efficiency stuff more and try to eat the easy 80% of workloads, winning market share on volume instead of frontier if they were not able to produce frontier level models.

They're very well equipped to be the volume discount store of inference.

I find their models are pretty good for answering every day questions, and with their large user base, I’m sure they’re getting lots of usage.

Model card: https://storage.googleapis.com/deepmind-media/Model-Cards/Ge...

It's available in Antigravity as well -

  Gemini 3.6 Flash (High)
  Gemini 3.6 Flash (Medium)
  Gemini 3.6 Flash (Low)
  Gemini 3.5 Flash (Medium)
  Gemini 3.5 Flash (High)
  Gemini 3.5 Flash (Low)
  Gemini 3.1 Pro (Low)
  Gemini 3.1 Pro (High)
  Claude Sonnet 4.6 (Thinking)
  Claude Opus 4.6 (Thinking)
  GPT-OSS 120B (Medium)

I would be fine lauding Gemini models if the only benefit of them was superior understanding of intent (read between the lines). I don't need it to code because other models are tuned for that explicitly, but I would like a model that is tuned to produce less mechanical output.

It is both less intelligent and more expensive than GLM-5.2, while being closed weight.

I think there is another angle here - maybe, just maybe google doesn't want to release a pro/stronger model sooner because of two reasons- 1) they're afraid they'll have to get their hands dirty in a certain war?? 2) what's the benefit of being on top of this chart?

so I think they're just focussed on releasing whatever helps their bottomline (improving search?). its not like anthropic and openai are making a lot of money being on the top of charts! this might just be my crazy pills talking though.

Flash 3.5 does OK for various tasks. It's not super smart but is a workhorse and if 3.6 one is better than it, that's a positive for me.

Most conversation is taking place in this thread: https://news.ycombinator.com/item?id=48993414

I just saw it in agy and started using it without asking any questions. I did not notice any major difference.

https://blog.google/innovation-and-ai/models-and-research/ge...

at least openai had the guts to call code red and improve.

releasing a model worse than luna is pretty bad. Its clear that internally they did not decide coding was a thing until relatively recently.

It’s frankly embarrassing at this point. I’ve got free access through buying a Pixel phone and it’s not even worth using as it’s a waste of my time. Here’s my experience so far using it for basic sysadmin Linux type stuff.

Gemini 3.1 Pro just feels a generation behind, from when models would miss easy things and make bad assumptions. Its not actively detrimental in bad way but the opportunity cost vs using something like Opus to be productive is large.

Gemini 3.5 Flash is the most annoying model I have ever used. It loves to respond in ALL CAPS like “LOOK AT THAT” for no apparent reason. I realize it’s a flash model but I will give it a basic list of tasks and the output will simply vomit “Now I will X” “Now I will Y” “Now I will Z” over and over again filling my screen with garbage. It’s also no smarter than 3.1 Pro and consumes just as many tokens as 3.1 Pro, it’s really pointless without a newer Pro model in place.

where is gemini-3.5-pro ??

I've heard almost nothing about Gemini in my circles, are they still in the race to build AGI?

I know that Flash is obviously no Opus or Fable. That being said, when I want a very quick response, my go-to is Gemini Flash. It's just really damn fast and generally tends to be accurate enough.

Why isn't there an official annoucement? And is pro dead haha?

Is this supposed to be a replacement for 2.5 flash?

I don't like how it compared itself to 5.6 Luna instead of Sol, and still losing on some metrics. You will not see me using this over even 5.6 Sol-light

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