6 ms·

In the $19 plan, I've been able to reverse engineer both an android APK and firmware (in Ghidra and Radre) for a baby rocker and build a quick PoC application i

In the $19 plan, I've been able to reverse engineer both an android APK and firmware (in Ghidra and Radre) for a baby rocker and build a quick PoC application in my session limit. And then further refined the app in another session at another point in time without leaving Opus. I dont consider that to be a tiny task. How are you blowing through your usage?

SwellJoe 2mo ago
I have no idea. Seems like normal stuff. I used Kimi Code with K3 to add support for Kimi Code to flar (https://swelljoe.com/post/i-let-every-agent-implement-its-own-flar-backend/ https://swelljoe.com/post/i-let-every-agent-implement-its-ow...), a task I've done with almost every major model/agent combo. Most show up as a blip on the usage chart...it's basically usually one file, a README update, and adding the agent name to the CLI. Then, I added it to my benchmark of security vulnerability auditing capability, and it burned a bazillion tokens, burned through the 5-hour limit, burned through $100 in extra usage I'd allocated, and was only 11% finished. That's more expensive than any model I've tested other than GPT 5.5 Pro on this task. These are things I've done with a bunch of other models, I feel like I have a notion of what they ought to cost, and with K3, they end up being crazy expensive. (And it seems to be a function of how many tokens it burns accomplishing the tasks.)
- lukan 2mo ago
  I guess the problem is, that claude's 5 h/weekly limit is not consistent, but depends how many other people are using it/how much ressources Antrophic currently has. I did huge amounts of work without hitting the limit - and small tasks at some other times that hit the limit before it completed. Those who pay for the expensive direct API, get served first.
  - Barbing 2mo ago
    Not surprising given the way they served super low-quality inference before they acquired compute from Musk. And not convinced they couldn’t have instead tried the It’s A Wonderful Life strategy (“fam we’re oversold, would some of y’all be OK to limit your usage? We’ll get you back one day!”)
- port11 2mo ago
  I wonder if the harness itself is not token-efficient? It would be fairer to compare K3 using the same generic harness, such as a Pi setup with some sane extensions for token optimisation.

SwellJoe 2mo ago

I have no idea. Seems like normal stuff. I used Kimi Code with K3 to add support for Kimi Code to flar (https://swelljoe.com/post/i-let-every-agent-implement-its-own-flar-backend/ https://swelljoe.com/post/i-let-every-agent-implement-its-ow...), a task I've done with almost every major model/agent combo. Most show up as a blip on the usage chart...it's basically usually one file, a README update, and adding the agent name to the CLI. Then, I added it to my benchmark of security vulnerability auditing capability, and it burned a bazillion tokens, burned through the 5-hour limit, burned through $100 in extra usage I'd allocated, and was only 11% finished. That's more expensive than any model I've tested other than GPT 5.5 Pro on this task. These are things I've done with a bunch of other models, I feel like I have a notion of what they ought to cost, and with K3, they end up being crazy expensive. (And it seems to be a function of how many tokens it burns accomplishing the tasks.)

lukan 2mo ago
I guess the problem is, that claude's 5 h/weekly limit is not consistent, but depends how many other people are using it/how much ressources Antrophic currently has. I did huge amounts of work without hitting the limit - and small tasks at some other times that hit the limit before it completed. Those who pay for the expensive direct API, get served first.
- Barbing 2mo ago
  Not surprising given the way they served super low-quality inference before they acquired compute from Musk. And not convinced they couldn’t have instead tried the It’s A Wonderful Life strategy (“fam we’re oversold, would some of y’all be OK to limit your usage? We’ll get you back one day!”)
port11 2mo ago
I wonder if the harness itself is not token-efficient? It would be fairer to compare K3 using the same generic harness, such as a Pi setup with some sane extensions for token optimisation.