Last stage is moving everyone to their cloud platforms, they deploy everything for you, you don't even get to see the code, just the deployed end product.
Because letting you look at the code would be too dangerous, you could reverse engineer an exploit to another product! Or distill their internet-distilled model!
But don't worry, at least it will be very convenient.
My guess: it's the price at which they make more money than if they rent the TPUs to other companies.
The Gemini team has had trouble securing enough TPUs for their user's needs. They struggle with load and their rate limits are really bad. Maybe at a higher price, they have a better chance at getting more TPUs assigned?
You're probably joking, but this is interesting. If we throw more RAM at AI, it can help us optimize programs to reduce our RAM needs, I haven't thought about it like that
Benchmarks are not interesting in deciding the "size class". Bigger size means more knowledge. Also, the Qwen 3.5 27B is a dense 27B active parameter model. StepFun 3.5 Flash has 11B active parameters.