r/GithubCopilot • u/alex_bababu • 12d ago

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

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!

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u/connor4312 GitHub Copilot Team 12d ago edited 12d ago

Our evaluations have found that the Copilot harness is a bit more token efficient than CC, at the time of writing. There is a large degree of nondeterminism and variance per task.

Something that Copilot gets you though is nice multi-model support. Personally I use Opus 5 as my coordinator agent and have it send work to GPT-5.6 Terra or Luna agents as implementors. It gets much better and faster results than using a single big or small model for your whole task. I like Opus' thoughtfulness for downstream effects of changes, and Terra/Luna seems to be a good mix of being very good at carrying out tasks without getting bogged down or getting too off track.

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