At long context the KV cache, not the weights, fills the GPU. The signal is naming the levers (quantization, token eviction, head sharing, low-rank) and what each one costs in quality.
Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.
At long context the KV cache, not the weights, fills the GPU. The signal is naming the levers (quantization, token eviction, head sharing, low-rank) and what each one costs in quality.
No lesson covers this question directly yet. These teach the surrounding topic from the beginning.
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