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Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

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Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#511

Post by zmmmmm »

spyckie2 wrote: post #63

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 ge…

It's probably a mix of things but I do think they are viewing "edge AI" as their strategic play: on-device, small efficient models (Android / iOS) and instant AI summaries in google search etc. So all of their focus is on delivering strong performance in a compute constrained environment.

I do think it's still also simultaneously true that they have an actual problem with competing with current frontier progress. It's just that has gone from an existential threat to something they are willing to defer addressing because they see the long game for them sitting at the smaller end.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#512

Post by tonyhart7 »

reilly3000 wrote: post #471
Miraste wrote: post #448

Earlier quoted context omitted.

That's the only explanation that makes sense. If it was frontier but cost or compute were limiting factors, they'd release it at an obscene price for the bragging rights. Google doesn't care that much about alignment, and I don't think it's likely to be significantly different than 3.5 anyway. The only reason it would need to be soft-canceled is if it's terrible, and has to end up in a ditch like Llama 4 to avoid sha…

3.5 pro was clearly a miss. It should have been in prod mid may, not MIA in late July. The brain drain at deep mind is a clear indicator that the people who know the most think that they can’t stay at the frontier. Antigravity NEEDED to be game-changing. Without the stream of data that Claude, Codex, and Cursor enjoy there is little chance of getting an effective reinforcement learning loop. For the first time in its…

"Without the stream of data that Claude, Codex, and Cursor enjoy there is little chance of getting an effective reinforcement learning loop"

Google literally giving everyone + student 18 month free subscription, those are source of cheap gemini + sonet,opus model that people selling/use with rotator proxy with thousands of account

they didn't lack the data

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#513

Post by do_anh_tu »

Man I love Gemini models but these kind of pricing increase is just insanse. I have a little product and I have to keep increasing the price and reduce the limits because of this non-sense, and they did not even let us use the old models in near future, so I forced to update to the new model with basically no to little improvement because I don't even need that much. Google if you can read this, it okay to release new models and change the price for them, but please please don't kill the old ones like gemini-2.5-flash-lite, because that all I ever need for my little apps with only few thousands of users.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#514

Post by mdasen »

maxloh wrote: post #191
armarr wrote: post #89

Earlier quoted context omitted.

GLM was twice as verbose running the Artificial Analysis benchmark. So it ends up being more expensive

Not really. Gemini 3.6 Flash actually cost $0.01 more per task, compared to GLM 5.2. https://artificialanalysis.ai/models/gemini-3-6-flash

But to run the entire benchmark it cost $727 with Gemini 3.6 Flash and $925 with GLM-5.2, $198 (21.4%) less. I tend to look at the cost to run the whole index rather than the weighted average cost per task.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#515

Post by cheesecakegood »

rescbr wrote: post #336
ngrilly wrote: post #150

Earlier quoted context omitted.

I'm in the same situation. But I was shocked discovering it goes both ways: many new Gemini functionalities are only accessible using a consumer account instead of a Workspace account. Also, Gemini is now the only major AI assistant with no support for MCP connectors. Instead of adding this to the core product, like ChatGPT and Claude did, somebody at Google decided that it was smarter to add this fundamental feature…

I currently have a free trial AI Pro subscription that will run out next month. If it weren't for the $10 GCP credit, I'd straight away cancel it. I don't see enough value in Gemini to justify the $20 subscription.

Similar here. I saw an email wanting the 20 bucks to continue and I outright laughed. There’s no planet on which that plan offers equivalent value to the OpenAI or Anthropic equivalents.

They might have success if they tried maybe a 12-15 dollar tier.

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#516

Post by tobias2014 »

dudeinhawaii wrote: post #505
dismalaf wrote: post #93

With all the naysayers on Gemini models I'm curious how many people actually use Gemini regularly? 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…

I use all of the major providers daily and I tend to go to Gemini for "fast lookups" where a good enough answer is probably OK. I use ChatGPT and Claude for anything where it matters and generally when I invoke all three -- Gemini is the most surface level with responses, and also sycophantic. It gets worse from there. Gemini is terrible at agentic coding, primarily because Agy is terrible. I noticed Google updated A…

I agree, I see how Gemini itself with a usable harness can be excellent. But in agy with forced eager compaction (~125k with 3.1-pro, ~200k with flash) a kind of laziness and forgetting shows through that leads to an endless sequence of stopgap instructions, even with rigorous GEMINI.md and isolated task delegation and a good task tracking system. Agy is basically useless for more complex problems as far as I am concerned, at least when used somewhat autonomously as one could expect from claude. For strictly mechanical one-shot tasks it might be fine. I've spent way too much time working around these limitations instead of just continuing to use claude. Hoping that things would have improved with flash 3.6 I feel that it's actually worse in following instructions, and always acts even when just asked a question. If just agy offered a better experience and got rid of the terrible forced automatic eager compaction.

PS: That opus-4.6 via agy works so much better points in another direction though!

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#517

Post by steve-atx-7600 »

postalcoder wrote: post #53

I wonder how big the Pro model is that Google is using behind the scenes to train these smaller ones. 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…

Artificial analysis always seemed sketchy as hell. If you read some of there methodology you’ll see a lot of <=3 repetitions on a particular pass for a given model. So low for calling a frontier model over the public internet ????

Re: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

#518

Post by usef- »

redox99 wrote: post #297
awongh wrote: post #193

Earlier quoted context omitted.

It seems like there are some credible rumors that Google is actually winning in terms of actually building models that work and don't lose money- between how they're able to price them, the TPU advantage and their capex advantage (being able to raise debt + just having a lot of cash - well I said not lose money... more like not go bankrupt). From the outside they look like they're behind in terms of frontier models,…

They basically don't exist in the currently most profitable LLM market (coding). Yes, subs like codex are heavily subsidized. But API billing has massive margins and that's what enterprises pay.

On the other hand, the consumer side of the market seems to be less competitive right now.

OpenAI's new Mac app doesn't even have a normal "Chat" option now. OpenAI might be chasing coding and b2b sales more now that they realise very few regular consumers pay for subscriptions.

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