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Inference-time Compute Examples?

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Inference-Time Compute The practice of letting a model spend extra computation while actually answering a query — longer reasoning chains, multiple sampled attempts, self-checking — rather than only investing compute during training.

Origin:Named directly by AI researchers to distinguish this newer lever (more thinking time per query) from the older assumption that a model's capability was fixed once training finished.
First Seen:2024
Peak Era:2025-2026 (Reasoning Model Era)
Aura Impact:+15 Aura (Understanding Why the Slow Model Is the Smart One) / -10 Aura (Complaining a Reasoning Model Is 'Too Slow' Without Knowing Why)

EXAMPLE USAGE

"The new model is slower because it's burning inference-time compute on a longer reasoning chain before it answers."

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