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Comment by nullify88 | Hacker News Reader

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?

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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-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.)

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.

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!”)

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.

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