I'm having the same issue with Gemini as soon as the context length exceeds 50k-ish. At that point, it starts to blurp out random code of terrible quality, even with clear instructions. It would often mix up various APIs. I spend a lot of time instructing it about not writing such code, with plenty of fewshot examples, but it doesn't seem to work. It's like it gets "confused".

The large context length is a huge advantage, but it doesn't seem to be able to use it effectively. Would you say that OpenAI models don't suffer from this problem?