Claude Code vs GitHub Copilot: Token burn comparison using identical models & repos?
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A developer is evaluating GitHub Copilot against Claude Code for their team, noting a slight difference in cost per token when using Copilot with Anthropic models versus Claude Code directly. They are seeking insights and real-world data regarding token consumption for both tools, specifically when using identical models and repositories, to help inform their decision.
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!