Improving Long-Context Performance in Gemini API

Hi everyone,
I’ve been experimenting with the Gemini API for a project that processes long text documents, and I’ve noticed that the model sometimes loses track of earlier parts of the context.

A few questions for the community:

  • Has anyone found effective prompt structuring techniques to preserve context over many turns?
  • Are there known limits or best practices for chunking large inputs?
  • Have there been any recent updates in August 2025 that improved this behavior?

I’d really appreciate any tips or real-world examples. Thanks!

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