Implementing Pi-Attention: 50% Memory Reduction for Long-Context LLMs

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The Problem: Quadratic Attention Standard transformer attention is O(n^2) in sequence length. For an 8K context window: 8,192 x 8,192 = 67 million attention computations per head 32 heads x 32 layers = 68 billion operations per forward pass This is why running long-context models on consumer GPUs is painful–you’re not running out of compute, you’re running out of memory for…

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