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I doub't it. The main issue is not cost, though they do get expensive as context grows, but intelligence. A frontier model like fable becomes as dumb as haiku after 200k tokens. They have been stuck at ~1M context/200k useful context for 18 months, now, with little sign of advancement. A model with a 10M context window that retains it's intelligence up to 2M tokens would be a big breakthrough.

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> A model with a 10M context window that retains it's intelligence up to 2M tokens would be a big breakthrough.

so the true next frontier might not be just raw intelligence but rather larger context window?

Or better context curation - less lossy compression saving back to context. Maybe even jettisoning part context into an external semantic store instead of conpression. Or placing less data into context to start with.

Or a combination of all those things.

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