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Offtopic group for casual talking about anything. @rules_for_python still apply (except for the ontopic rule)
4 performance cores with 2 threads each, 8 ecores with one thread. 16 threads.
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It can compile packages, that would have made sense, but it didn't get that far.
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htop was sorted by CPU usage, so I couldn't see. Just that nix, the process I started before it began, was consuming about 20G.
All cores were fully busy, but that was a side effect of the memory being full. As if was doing something special. But somehow I managed to get it full.
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100%, there is something called Caching. When you first talk to the LLM, it needs to know everything about your project.
The context window size doesn't change when you change the model, but most of the context for the first LLM is already cached on the server. When the next LLM is called, the whole thing has to be sent again, and the LLM has to know the proper context.
This is why you see that the amount of tokens used for the newer model is much higher.
Maybe fair amount of token gets burned in the beginning
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They should have compared Claude Code CLI with Claude Code in Cursor.
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No, not really... if you switch from one model to another, you have to send that new model all the context, while if you stick with a single model, it uses loads of cache.
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I mean there's an overhead I'd assume, but it's not 5 times as much.
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And they all work together. The fact my cpu may sucks is another argument.
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repeating activities that lead to utilisation might have some insight. But it could be spontaneous 🤔
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My computer crashed today. I was lucky enough to have been able to open htop before it stopped reacting completely.
To understand repo. It’s like complaints of diminishing returns is being improved
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I’ve seen significant less token usage by Claude cli. Extension is useless.
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Token efficiency matters for cost. Independent testing found Claude Code uses 5.5x fewer tokens than Cursor for identical tasks. Claude Code (Opus) completed a benchmark task with 33K tokens and no errors. The Cursor agent (GPT-5) used 188K tokens and hit errors along the way. Fewer tokens means lower per-task cost even at higher subscription prices.Читать полностью…
— https://www.builder.io/blog/cursor-vs-claude-code
Claude models are good at coding so they gatekeep. No wonder. Their claims
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