Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
91–100 of 433 posts
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#92Earlier quoted context omitted.
You're making the opposite argument. Anthropic is incentivized to use less tokens in Claude Code because people are paying a fixed monthly fee for subscriptions.
Enterprise users are not paying a fixed fee, though
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#93Earlier quoted context omitted.
Every subagent send the same ~30k system prompts. If you are using fable/opus, that's easily 30% of a 5-hour window for 7 subagent, before doing any work
If it's always the same prompt, can't they have it pre-cached globally for all?
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#94Earlier quoted context omitted.
You're making the opposite argument. Anthropic is incentivized to use less tokens in Claude Code because people are paying a fixed monthly fee for subscriptions.
Nope, that’s not true, because they want you to pay for the higher subscription bracket.
Especially since compute is such a scarce resource.
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#95Is it not a conflict of interest for a model provider to supply the harness? They are not motivated to minimize your costs.
If you don't use a subscription, and pay per token instead, you can easily move to another harness.
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#96Early 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...
This is interesting, because if I start a fresh session of Claude Code right now and run /context, I see the following: Opus 4.8 (1M context) claude-opus-4-8[1m] 23k/1m tokens (2%) Estimated usage by category System prompt: 3.9k tokens (0.4%) System tools: 13.9k tokens (1.4%) Custom agents: 235 tokens (0.0%) Memory files: 28 tokens (0.0%) Skills: 4.9k tokens (0.5%) Messages: 8 tokens (0.0%) Compact buffer: 3k tokens…
I was simply supporting the article's data - their reported 33k tokens is probably roughly 150-165k.
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#97Earlier quoted context omitted.
Nope, that’s not true, because they want you to pay for the higher subscription bracket.
Can confirm — they got me paying $100/mo this way. Also I think it’s well known that OpenAI is the much less expensive option (in tokens and $$). For the same $20 you get a lot more mileage. Curious if folks have strong opinions about the overall UX of OpenCode vs CC…
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#98Recently 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.
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#99UPDATE: 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.
I wonder if a lot of the 33k is context, like from recent conversations.
Re: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k
#100What 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…
Probably because the general purpose subagents inherit the parent model.
I tell Claude explicitly to use Explore subagents, which use Haiku only, now.