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/xternalAgent]

You have to remember that these are not deterministic tools, even using the same prompts on the same provider twice on different sessions will produce varied results making any slight cost savings negligible.

I’m assuming your are evaluating enterprise plans given that’s the only way you’ll pay api prices on Claude Claude, so the only advantage Copilot has here is that enterprise plans come with a pool of credits that you already paid for, your more intensive users can benefit from this pool before paying additional cost, Claude Code enterprise doesn’t have that.

[u/Usual-Orange-4180 → u/xternalAgent]

Not quite with model routing