Small AI models outperform larger ones by thinking longer during inference

Recent AI research has identified test-time compute, where models spend more processing time reasoning after a prompt, as a key factor for performance. A 2024 study found that a model four times smaller, using advanced reasoning strategies, could match or beat models up to 14 times its size on complex tasks without extra training. This has led major AI releases to incorporate 'thinking' modes as a standard feature. The primary methods include letting the model write longer internal reasoning, taking majority votes from multiple attempts, and using verifiers to score and select the best solution.