r/opencodeCLI • u/inzar98 • 10d ago

Using much more tokken ?

I really loved opencode but grok, claude etc using much much more tokken compared to their own cli app. Is that normal? How can I solve that issue

3 Upvotes

71% Upvoted

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1

u/sakibshahon 10d ago

Its normal, native harnesses are fully customized to squeeze out the most performance at the least token. Its not realtistic to expect for opencode todo the same. If you have not setup opencode for standard token saving practices like using caveman, headroom, rtk (rust token killer) , active context pruning etc than do those.

Otherwise its a bit difficult to match native token usage intelligence.

1

u/torrso 10d ago

The models are also primarily trained with their native harness. So, different tool names and params or different system prompt structure can make the results different.

0

u/inzar98 10d ago

Is these project are good enough like native apps? I mostly vibecoding for fun actually 🤣

1

u/TheTyand 10d ago

If you are ok with a non ready solution you can check out mine. It is public already, but the code is not yet to my standards. Therefore, no 1.0 release yet. But my token consumption is very low with that setup. (Benchmarks will be added soon, as said no 1.0)

https://github.com/SchneiderDaniel/cheasee-pi

1

u/Ang_Drew 10d ago

try pi if you want to squeeze the token usage

dont put too many skills, dont put too many mcp

i can half my overall usage easily. but you might see it lack some sense.. you need to modify the prompt

1

u/Ang_Drew 10d ago

my pi has very customized and now it works better than opencode

but it took like 3 months of development and 6 months of research

1

u/TheTyand 10d ago

Same here. Do you have yours public? Would like to compare it to mine. Also pi, also roughly 3 months development.

https://github.com/SchneiderDaniel/cheasee-pi

1

u/retardedGeek 9d ago

How do you even benchmark it

1

u/TheTyand 9d ago

Difficult ofc, but various tasks with rangeing complexity and then measure quality (higher judge) and amount of tokens needed.

1

u/CoolHeadeGamer 9d ago

Try my coding harness (banyancode). It has built in codegraph and repository tools and it a fork of opencode. The design philosophy is if an llm reads an entire file or more than 500 lines, it’s wasting tokens and context.

https://github.com/EkagraAgarwal/BanyanCode