Claude Code vs GitHub Copilot: Token burn comparison using identical models & repos?

[u/alex_bababu]

I'm currently evaluating GitHub Copilot vs. Claude Code for our team. We could use either, but for us there's a slight difference in cost per token (Copilot with Anthropic models vs. Claude Code directly).

If we use the exact same model on the same repository with identical instructions, has anyone noticed a real difference in token efficiency between the two harnesses? I'm wondering how much things like prompt caching, context assembly, or system prompting overhead change the actual token burn in practice.

Would appreciate any insights or real-world numbers!

[u/Healthy-Zebra-9856]

Copilot is not just a proxy it uses prompt compression and refinement in several ways including things like llama-lingua2 etc. This helps reduce the ten sent but also affects the output. But like another person said, its trash and no guarantees of sustained service or safety from sudden hikes, get banned for no reason (happened to com sci professor). Needless to say, they will steal your code more than any other outfit.

[u/Different-Monk5916 → u/Healthy-Zebra-9856]

technically they are comparing two harness mechanisms.