alt Hacker News> Furthermore, we observe that input tokens consistently constitute the largest share of consumption for an average of 53.9%
I'm seeing a ratio of around 10:1 in my usage. A vast majority of the tokens consumed are on the input side. The agent will often read a million tokens just to patch one line of code.
I think if you are seeing something closer to 1:1 or more on the output side, there is either a problem with the agent or the codebase is new / empty.
Replies
kolinko • today at 9:29 AM
Did you experiment with giving agent better tools to navigate and document the codebase? Asts, language servers and so on?
A million tokens (not cached) sounds like a lot.
➕ show 1 reply
If input tokens dominate the cost to that extent, this implies that major gains are possible by making better use of caching. You could basically ask the model to do a one-time "compaction" step including a dump of the relevant portions of the code, and use that as the cached prefix for a large amount of "swarm" subagent calls.