Going on baseless speculation, the lack of accompanying pro models with these flash releases either means: 1) the model is too big to be economical, 2) google doesn't have the compute to serve the big model, 3) their big model has too many alignment issues to serve to the public.

edit: looks like benchmarks are up on https://artificialanalysis.ai/models/gemini-3-6-flash. It's solidly middle-of-pack. However, if you want to be most fair to flash, look at the intelligence vs time per task and intelligence vs outputspeed benchmarks. This is a very fast model.

edit 2: I use antigravity from time to time and in my experience, 3.5 flash is an underrated model, so long as you know what it's good for. It's very good at frontend (much better than gpt 5.5) and it's fast, so it's a great tool for iteration. I expect 3.6 to be no different.

They literally forced me and my company out of Antigravity by phasing out AI Ultra subscription without any proper product follow-up. Antigravity IDE cannot even have poweruser subscriptions now from Google Workspace an Gemini Enterprise Agent Platform cannot be attached to Antigravity IDE.

Gemini Enterprise Agent Platform has an incredibly abysmal setup process, and if I want to limit spending per-user I have to create projects per user. The fact that you cannot activate Anthropic models on it if the billing still has free credits is almost a joke.

I was a big proponent of Google and Gemini, but they left us reeling with their abrupt product decisions. Forced us to buy $200 subscriptions directly from Anthropic/OpenAI.

It seemed for a time that Google had finally gotten the ball rolling, but I'm doubting that more and more as time passes. We'll see what happens with 3.5 pro I suppose.

https://tools.simonwillison.net/markdown-svg-renderer#url=ht...

2.5 Flash: $0.3 / $2.5

3.0 Flash: $0.5 / $3

3.5 Flash: $1.5 / $9

3.6 Flash: $1.5 / $7.5

---

2.5 Flash-Lite: $0.1 / $0.4

3.1 Flash-Lite: $0.25 / $1.5

3.5 Flash-Lite: $0.3 / $2.5

> Beyond today’s releases, Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready.

> We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress.

https://fy2zp1ri90.evvl.io/

I have a very price sensitive workload that used to run on flash 2.5 lite - it's deprecated now.

The replacement 3.1 flash lite is a lot more expensive, but now also has a sunset date.

3.5 flash lite is even more expensive.

So the price is rising and you have no choice but to keep paying more and more.

Anyone have any good alternatives?

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

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."

That said, the speed looks really good. I think it's competitive with Fireworks's GLM 5.2 Fast, although Fireworks is still cheaper.

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.

It's a one thing to research and improve the model, but if they ignore the ease of access and multi-availability of their models in different ways they are going to fall behind again.

1. Their AI efforts are very fundamental research oriented. They are really good at it.

2. Their productization sucks. The end products gets little attention compared to competition. It can be canceled at any time. You should never build anything around Google only APIs, AI or not.

Has anybody found any models better at image or audio analysis?

https://artificialanalysis.ai/models/gemini-3-6-flash?intell...

Rough patch for google ai

Otherwise, this news feels like a tiny incremental improvement on Gemini Flash series to make it more efficient with token usage, subagent and cost. Nothing big.

Regarding their benchmark scores on CyberGym, I wonder why they didn't compare their 3.5 Flash Cyber model with Fable 5. I mean they included Mythos and GPT-Cyber, so why not Fable 5 too?

They also mentioned Gemini 3.5 Pro is in testing and its about to become available very soon. Another thing maybe worth discussing is the announcement of pre-training Gemini 4. Sadly, not much technical details to discuss on. Many comments in here seem to mostly be about how Google is behind the others, but honestly, is it really worth the investment to be #1 in Artifical Analysis every week?

Fable 5 still wins on detail with no visible errors, but it's close. And this isn't a memorized pelican;

https://playcode.io/blog/macbook-svg-benchmark#gemini-3-6-fl...

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

[0] https://artificialanalysis.ai/models/gemini-3-6-flash

It is also cheaper than 3.5:

> This enhanced efficiency is also combined with a lower price than 3.5 Flash. At $1.50/1M input tokens and $7.50/1M output tokens, 3.6 Flash reduces the overall cost per agentic task, making agents more cost-effective to build and run.

Seems like this is mostly a cost play by Google, hoping this doesn't bring 3.5 Flash capabilities to an end of life, and that 3.6 catches up or gets better.

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

If it wasn't for Gemini/Antigravity I'd have to go with a Max Claude plan, as it stands now I can get by with just a Claude Pro plan to get Opus when I need it, whilst using Antigravity as my day-to-day workhorse.

Unfortunately Gemini Flash became too expensive to use as a general purpose model (i.e. for AI features in Apps), luckily there are plenty of cheaper Chinese models to fill that gap now.

gemini-2.5-flash-lite: $0.10 input / $0.40 output

gemini-3.1-flash-lite: $0.25 input / $1.50 output

gemini-3.5-flash-lite: $0.30 input / $2.50 output (a 6.25x increase over 2.5!)

Now watch them deprecate Gemini 2.5 Flash-Lite in the coming months...

Plus they are probably running these things on every Google search so saving tokens is a huge win for them.

Ever frontier lab lived it at least once : missing the frontier by a few months triggers extremly negative reactions, then you take back the lead for 2 weeks, and the hype cycle repeats.

3.5 Flash Lite is only a hair cheaper than 3.0 Flash, but I think 3.0 Flash is a massively more capable model?

Deepseek Pro: 0.435/m 0.87/m

That's wildly ambitious pricing by Google. You can maybe get away with spicy pricing at the SOTA edge but at the lower tiers everything is a lot more price sensitive.

"3.6 Flash delivers higher precision with fewer unwanted code edits and reduced execution loops, as seen in DeepSWE (49% vs. 37%)"

So which one is it? 65% or 49%?

> We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress.

I use 3.1 Flash Lite regularly to classify listings on eCommerce websites. It's great for this task - fast, cheap and accurate.

In fact, it was the single best model we tried in terms of the speed vs accuracy vs price tradeoffs - including the Chinese models.

Of course, 3.5 Flash was more accurate but the 5x cost increase couldn't be justified.

3.5 Flash Lite sounds like it could be a strict upgrade for our use case, without a significant increase in costs or drop in speed.

It's not GPT-6 but it's not trying to be. It's a completely different tool and great at what it does.

My results [0] put Gemini 3.6 Flash at the top.

3.6 Flash high has same $1.5 input price as 3.5 Flash, but output is cheaper from $9.0 to $7.5.

Google said 3.6 Flash is more token efficient, but in my tests it's actually LESS token efficient[1] than 3.5 Flash, so despite the output price reduction, it still costs more.

[0]: https://aibenchy.com/compare/google-gemini-3-6-flash-medium/...

[1]: https://aibenchy.com/compare/google-gemini-3-6-flash-high/go...

Front page is tedious these days.

we are stealing plutocracy from the jaws of emancipation.

i don't want to live in a world where abundance is guarded and shared among politicians and cronies, whilst the rest are left to rot.

1- no comparison with gemini 3.1 pro

2- no comparison with any other model

Google watches over the last few months a flat out assault on the Pareto curve from American and Chinese companies. Release after release pushing the boundaries of frontier intelligence and price/performance.

And the response from arguably the biggest AI research labs in the world by headcount is Flash 3.6.

What do you do when you are given essentially unlimited resources and still find yourself falling behind?

It doesn't matter how good the model is if you're (mostly) forced to use it in Antigravity - which turns any model into crap.

Wake me up when Antigravity doesn't suck.

I'd be low-keying the release if anything, given how lame they are compared to their competition.

What am I missing?

It's time for them to start focusing on open-weight models and efficiency. Otherwise there's just a layer of marketing hype and "will it do this?" that has to be cut through for evaluation of each and every release cycle.

Models are getting easier and easier to create. The money, if there's any here, is in the harness the user interfaces with, and the data centers running them.

Screw your government! US and Israeli governments should get the least access, but of course we all know they'll be the (only) ones to get full unfiltered access.

Gemini 3.6 Flash https://news.ycombinator.com/item?id=48993130

Meaning, its predictable with tool calls, wont spin off a million tools/do weird behavior, its reasonable. Even sonnet in a real world decision making scenario is not reliable, or will reason so long its incredibly expensive.

The benchmarks arent catching all the value, and most people have never actually ran an ai agent in a real context that matters

For me, Gemini models are the most usable. Claude Opus and Mistral always try to turn queries into one-shot enormous commits, which just burns tokens, time and annoys me for something which is still wrong more often than not.

Gemini seems far better at listening to instructions and giving me what I actually want, on top of using far fewer tokens and wasting my time. Fable is the only model that's come close to Gemini Pro for me.

And as this is about Flash, it's exciting, I find Flash can usually get the right answer pretty quickly and without too much nonsense.

you can check by asking "list notable world events in 2025, only list unplanned" on aistudio. or you can ask for Charlie Kirk, it also does not know. I tried it multiple time to ensure that I didn't not get routed to older models!

> but google has search

irrelevant, without deeper knowledge about cutting edge technologies or latest libraries, all of it suggestions are crap. even you ask it to search it will still use outdated keyword thus only getting outdated information.

in other word, what a disaster!