With large context windows, is RAG still needed?

Often yes. Even with big context windows, stuffing everything in is expensive (you pay for all those input tokens every call), can bury key facts in the middle where models under-use them, and doesn't scale to large or changing corpora. RAG retrieves only what's relevant, keeping cost down and precision up, and updates instantly as documents change. Long context and RAG are complementary — long context helps within a request; RAG decides what deserves to be in it.