Claude Code Sends 33k Tokens Before Reading Your Prompt; OpenCode Sends 7k
Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
I measured the hidden token costs of Claude Code versus OpenCode, discovering that Claude Code sends roughly 33,000 tokens of system scaffolding before your prompt even arrives, compared to OpenCode's 7,000. While Claude Code rewrites cache tokens aggressively, increasing costs, its ability to batch tool calls can sometimes make it cheaper for complex tasks. However, for simple interactions, the massive baseline overhead of Claude Code significantly inflates your bill and consumes context budget.
By the time a real working setup sends its first request, it is 75,000 to 85,000 tokens deep before the user has typed a word.
- mcv
What really burns tokens is sub agents. I once gave Claude Code a pretty big task, and it immediately launched 7 sub agents which burned through my budget before even one of them was finished. Tried again 5 hours later: same result.
If I let the main agent do the same task sequentially, it was no problem at all. I don't know if it's really just communication and orchestration that makes sub agents so inefficient, or if Anthropic figured that most people using sub agents pay per token on a big corporate account, so this is an easy way to make more money from tokenmaxxers.
- korrectional
My opinion is that claude code uses more tokens simply because Anthropic makes more money that way and forces people into their subscriptions. This is supported by the fact that they won't let you use your sub on a different coding agent. I use pi btw.
- jakozaur
This isn’t limited to large system prompts. Coding-agent harnesses are also becoming more aggressive about using tools, even for trivial requests. In our tests, prompts such as “Hey” or “commit” sometimes triggered 30+ tool calls:
https://quesma.com/blog/the-true-cost-of-saying-hi-to-an-ai-...
Tokenflation seems very real: the number of tokens consumed by simple tasks keeps increasing.
- systima
UPDATE:
After reading PUSH_AX's valid comment:
```
This is like saying contractor (A) asked for $33,000 to undertake the work and contractor (B) asked for $7,000
Are we measuring and caring about the right thing?
```
We will update the post to include:
1) A more in-depth task.
2) Qualitative results comparison.
3) As soon as possible, a reproduction of the inputs and outputs.
- bel8
And pi agent is even less.
The entire agent system prompt can be seen here:
https://github.com/earendil-works/pi/blob/main/packages%2Fco...
- estetlinus
Recently switched to Codex after 6m in Claude. Codex seems more open, it’s easier to follow what the model is doing and the approvals have a better UX. Overall, it just feels more transparent. Cost of switching was close to 0.
I don’t like that Claude became more opaque around February, including the system prompts. 33k feels way too much.
- alex7o
I am forced to use cloude code at work but a good solution is to just use --system-prompt "" and be done with it. I wish they allowed for other harnesses.
- eigenblake
We should discuss cache performance if we haven't already. That 33k tokens may be a cache hit (I am not certain it's automatically a cache hit) but after the first call, it should certainly be a cache hit. Cache hit tokens are billed at 1/10th the price of cache misses. This is quite opaque, but it's necessary when you're asking "is the system prompt worth its stay" if you can save 33k tokens worth of dynamic discovery across the next few turns, the break-even point is quick and if the system prompt makes task performance increase and/or makes the system more autonomous so that it can string together more cache hits in a row, it becomes way way better. On a personal note, I think of things as aa function of 'supervised time to desired result' and 'cost'. because I find it harder to reason about tokens. I do think they could introduce a "minimal" mode (something like this is probably doable with the Claude agent SDK today)
- ramoz
A harness is a part of the intelligence stack. It's no longer about raw access to the model
Also, I have seriously used most harnesses - One feels like it's being built in a place that truly understands AI and where agentic engineering is headed. You might not like it, but peak performance exists in CC when it comes to orchestration of bulk parallel work / subagents. The open source agents are catching up or accell in different way (Im preferable to pi.dev), but I'm not sure they're architecting orchestration the right why.
- mft_
Early on in experimenting with local models, I found that hooking them up to Claude Code worked very well, but it was also really slow.
I used mitmproxy (setup assisted by Claude, natch) to capture Claude Code's entire initial system prompt and the whole thing was (I just double-checked) 162k of JSON.
This led me to start experimenting with Pi, OpenCode, and Hermes...