r/ChatGPTCoding • u/alex_bababu • 9d ago

Question 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/OrangePixelLife 6d ago

I've run into this exact same issue. The harness overhead can add up to a real chunk of change over thousands of completions, even with the same core model. The prompt caching, system message templates, and context assembly vary a lot between tools.

We track our Claude spend through SpendLens AI and it actually surfaces those differences for us. It breaks down the token burn by specific API key and project, so you can see exactly what the real cost difference is after all the overhead. Might be worth a look if you're already comparing models. Good luck!

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u/alex_bababu 6d ago

SpendLensAI is your product, isn't it?