You don't need long context

The paper "You don't need long context" (Muralidharan et al., NVIDIA) argues that because later tokens cost up to 7x more to generate on frontier open-weight models, keeping contexts short through frequent compaction can preserve task accuracy on long-horizon and long-input tasks.