test time compute

The 2025-2026 landscape isn't 'bigger is better' anymore. What matters is knowing why small models and reasoning models exist, the test-time-compute tradeoff, and routing the right model to the right task. Here is the practitioner's view.

Reasoning models are the 2025-2026 frontier. The signal is understanding they are trained (largely via RL on verifiable rewards) to generate long internal reasoning, and that they scale along a second axis: spending more compute at inference.

Most candidates answer 'use the reasoning model for hard problems' and stop. The interviewer wants it framed as an eval and a budget problem: how you prove the extra thinking tokens paid off, and what you do when the model talks itself out of a correct answer.