It shows why autoregressive decode wastes GPU time and how kernels, batching and quantizationShrinking a model by storing its numbers less precisely — like rounding — so it runs faster and fits on smaller hardware, at a small quality cost.Full definition → together cut GPU needs from four H200s to one. That is useful for anyone costing out inferenceRunning a trained model to get answers — the phase where AI is actually used, as opposed to trained.Full definition →.
Terms in this piece · Glossary
quantization — Shrinking a model by storing its numbers less precisely — like rounding — so it runs faster and fits on smaller hardware, at a small quality cost.
inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
