291–300 of 616 posts
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.
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…
Flash Lite: 0.3/m and 2.5/m 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.
Earlier quoted context omitted.
It’s really surprising. When Apple announced the multi-billion dollar deal with Google to power Apple Intelligence I thought great things were coming. Instead we are getting more and more bad news: delayed Pro models and AI leadership leaving. I wonder if Apple know something the rest of us don’t know or if they are already regretting their decision.
What Apple wants out of Google is Siri that runs at 8gb ram and isn’t a horrible embarrassment that feels like a primitive markov chain. Given how good Gemma 4 is, Google can squeeze some serious performance in small models. Whether they can make bleeding edge models is irrelevant to Apple.
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…
It's also very possible that they know their big model underperforms chatgpt 5.6 and fable by too much, so they are focusing on what they can get wins in like speed instead.
For small models (which are probably distilled from their big ones) you can serve them economically all the time and not hemorrhage money.
Gemini 2.5 Flash-Lite has been my go to for cheap document processing at scale (especially with 50% off batch mode), but they are really boiling the frog with pricing increases with each version: 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-Lit…
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…
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,…
Yes, subs like codex are heavily subsidized. But API billing has massive margins and that's what enterprises pay.
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...
Google somehow managed to snatch defeat from the jaws of success with their AI products. 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…
Google's biggest and most important customer for all this AI stuff is google. Do they actually want other customers, or is having other people use their AI just an annoyance at this point, where we use up compute that they'd rather use internally...
It's a bit disheartening to see no comparison to other models here - and I'm not sure this pushes the curve anywhere. 3.6 flash is more expensive than GLM 5.2 - but seemingly worse, although this post is really light (lite?) on details. 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.
It’s really surprising. When Apple announced the multi-billion dollar deal with Google to power Apple Intelligence I thought great things were coming. Instead we are getting more and more bad news: delayed Pro models and AI leadership leaving. I wonder if Apple know something the rest of us don’t know or if they are already regretting their decision.