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Still I don't totally understand how that huge of a context works for Gemini. I guess you don't provide the whole context for every request? So it keeps (but also updates) context for a specific session?


I dont know how the massive context works but Caching is certainly a thing and cheaper: https://ai.google.dev/gemini-api/docs/caching?lang=python

Gemini is better than Sonnet if you have broad questions that concern a large codebase, the context size seems to help there. People also use subagents for specific purposes to keep each context size manageable, if possible.

On a related note I think the agent metaphor is a bit harmful because it suggests state while the LLM is stateless.




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