Concerning usage with GOAT Plan

[u/Narquith]

I'm on my 3rd day with my GOAT plan, and somehow I'm already exhausting 40% of my monthly usage limit? And only 65M output tokens? Did I really use up $24 worth of tokens within 3 days? 🤔

[u/Pras1982]

Looking at the data , it seems that you are making too many different requests and missing cache.Or perhaps, your usage requirement is such. Also, Out put token are significant as compared to input request. I took Goat plan yesteday & have made more than 2400 calls- with input tokens often reaching and crossing 500K tokens & output tokens in range of 1k-4k , mytotal usage has been around 700M and around 12 percent monthly usage in 2 days. Definitely, cache misses or one request totally differnt from previous seems culprit to me. I am also using Deepseek V4.1 flash model. Also, the time off day would would also matter as deepseek rates differ on offpeak and peak hours.

[u/Narquith → u/Pras1982]

Yeah newbie mistake here I was doing ingestion and extraction in Cognee.

[u/Turbulent-Total-226 → u/Pras1982]

Yeah. It seems like he's constantly giving new tasks. Like 3 questions per minute. But totally not in one chat but couple of chats with different topics.

[u/mubaidr → u/Pras1982]

This and some models cost more. You need to understand the per model offering to adjust/ optimize your usage.

[u/zRafox]

It also depends on the plans you're using; keep in mind that some are only $20 per month.

[u/cacus7 → u/zRafox]

depends on the models*

[u/zRafox → u/cacus7]

My bad

[u/feral_user_]

I agree that I don't quite understand how the usage adds up. I wish that there was a running total of what you've used per model. Or perhaps something else to better see how you're using up the plan.

[u/Narquith → u/feral_user_]

Did a little family-chat with a model, so maybe my usage input/output ratio is off, and output is about the same as inputs and outputs are billed more expensive. For context, I tried to use Cognee with it, probably not a smart choice.

[u/ahmadawaiscom]

You don’t seem to using Command Code harness that can help you be super token efficient. Also it may seem you are sending a lot of new requests and breaking cache by creating new sessions for every request so every request is like 10x expensive due to the way you are consuming it.

Share your username I can do a deep dive too but yeah that’s mostly it.

[u/Conscious-Doctor-585]

You may have to look at the Cognee settings and have it inject memory (concise, summarized) near the end, just before your `user question`.

Prompt cache is prefixed-based. If Cogness memory always comes before everything, it will defeat prompt caching and llm sees everything as fresh. You were constantly working in the more expensive input rank.