Shall the better model still have
the upper hand or will the raw speed
compensate?
At 14,000 tokens/sec there's just so much ridiculous stuff that might be possible. Let's assume that this POC proves they can take the next step, and can eventually etch a capable ~27B model into silicon. Let's call it Fred.Ralph loops automatically get real real interesting again. 200x the iteration speed. This is such a clear win I feel like there's hardly anything to talk about. Instead of one stubborn iterating idiot, you could have dozens of idiots competing in parallel, genetic algorithm style.
The other common orchestration pattern I see is "big model for planning, small parallel subagents implementing, big model reviewing" Today it's Sol dispatching a handful of Luna subagents. Tomorrow maybe it's Sol dispatching as many Fred subagents as it could possibly want.
But what patterns have we not even thought about yet in a world where subagents are 200x faster/cheaper?
What if instead of dispatching single Haiku/Luna/etc subagents, we dispatched "teams" of Fred agents? Maybe each team is 8 Freds. Five come up with competing ideas and the other three vote on a winner.
Or what if they were heterogenous teams? One Luna and a bunch of Freds.
What if instead of a two-tier orchestration system (Sol->Luna) it was three-tier or n-tier? (Sol->Luna->Fred->...Fred)
Those ideas overlap a bit, and crazy shit like Gas Town has already explored even wilder ideas I guess. But man, 14000 tk/sec opens up so much stuff.
Yes, imho 14k TPS is just a beginning.
This Gas Town? https://github.com/gastownhall/gastown
At 14,000t/s that's effectively a motor cortex for an android, you no longer need to train the robot to walk, it has a general idea for how to walk (baked into the 1b model), and then just corrects based on sensor input, in real time.