Consistent, predictable behavior is valuable, even more so given the nondeterministic nature of LLMs. Nondeterminism combined with unpredictability might as well be randomness.
I'd guess you're deliberately exaggerating here, but still. I've never clocked the actual tokens/second, but I'm on the $20 plan and get ~15M tokens/month for fully utilized weekly quotas (checked couple months ago). Meanwhile the best I've been able to get locally was ~8 tokens/second with Qwen3.6 35B A3B, which is wildly painful for coding sessions and gets a maximum ~20M tokens in a month... if it's going 24/7.
Just wanted to stick some empirical data here, given that statement.
At $1500 that's 75 months of $20/mo Claude which are MUCH better models than you can run locally.
The point raised by this very article is that you can't depend on that. It's Flowers for Algernon As A Service.
One challenge I run into is I run many agents at once, so local resource are a tiny fraction of the total inference we’re using. Every developer with his own Pro 20x, Max, etc. accounts is letting us hit literally trillions of tokens a month.
It was the wrong time for the GP to drop that subscription from $200 to $20, because $200 gets you a metric assload of cognition while $20 gets you nothing beyond what a local model running on your own graphics card can deliver.